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1
de Matos, Marcílio Castro, Paulo Léo Osorio, and Paulo Roberto Johann. "Unsupervised seismic facies analysis using wavelet transform and self-organizing maps." GEOPHYSICS 72, no. 1 (January 2007): P9—P21. http://dx.doi.org/10.1190/1.2392789.
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Unsupervised seismic facies analysis provides an effective way to estimate reservoir properties by combining different seismic attributes through pattern recognition algorithms. However, without consistent geological information, parameters such as the number of facies and even the input seismic attributes are usually chosen in an empirical way. In this context, we propose two new semiautomatic alternative methods. In the first one, we use the clustering of the Kohonen self-organizing maps (SOMs) as a new way to build seismic facies maps and to estimate the number of seismic facies. In the second method, we use wavelet transforms to identify seismic trace singularities in each geologically oriented segment, and then we build the seismic facies map using the clustering of the SOM. We tested both methods using synthetic and real seismic data from the Namorado deepwater giant oilfield in Campos Basin, offshore Brazil. The results confirm that we can estimate the appropriate number of seismic facies through the clustering of the SOM. We also showed that we can improve the seismic facies analysis by using trace singularities detected by the wavelet transform technique. This workflow presents the advantage of being less sensitive to horizon interpretation errors, thus resulting in an improved seismic facies analysis.
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Saraswat, Puneet, and Mrinal K. Sen. "Artificial immune-based self-organizing maps for seismic-facies analysis." GEOPHYSICS 77, no. 4 (July 1, 2012): O45—O53. http://dx.doi.org/10.1190/geo2011-0203.1.
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Seismic facies, combined with well-log data and other seismic attributes such as coherency, curvature, and AVO, play an important role in subsurface geological studies, especially for identification of depositional structures. The effectiveness of any seismic facies analysis algorithm depends on whether or not it is driven by local geologic factors, the absence of which may lead to unrealistic information about subsurface geology, depositional environment, and lithology. This includes proper identification of number of classes or facies existing in the data set. We developed a hybrid waveform classification algorithm based on an artificial immune system and self-organizing maps (AI-SOM), that forms the class of unsupervised classification or automatic facies identification followed by facies map generation. The advantage of AI-SOM is that, unlike, a stand-alone SOM, it is more robust in the presence of noise in seismic data. Artificial immune system (AIS) is an excellent data reduction technique providing a compact representation of the training data; this is followed by clustering and identification of number of clusters in the data set. The reduced data set from AIS processing serves as an excellent input to SOM processing. Thus, facies maps generated from AI-SOM are less affected by noise and redundancy in the data set. We tested the effectiveness of our algorithm with application to an offshore 3D seismic volume from F3 block in the Netherlands. The results confirmed that we can better interpret an appropriate number of facies in the seismic data using the AI-SOM approach than with a conventional SOM. We also examined the powerful data-reduction capabilities of AIS and advantages the of AI-SOM over SOM when data under consideration were noisy and redundant.
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Geluk, M. C. "Late Permian (Zechstein) carbonate-facies maps, the Netherlands." Netherlands Journal of Geosciences - Geologie en Mijnbouw 79, no. 1 (March 2000): 17–27. http://dx.doi.org/10.1017/s0016774600021545.
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AbstractThe Late Permian Zechstein carbonates in the Southern Permian Basin were deposited under marine conditions. The carbonates form part of a largely progradational infill, with a gradual northward facies shift. The paleogeography of the Zechstein carbonate deposits has been reviewed recently on the base of well data, cores and publications. This has resulted in three updated maps of the carbonate units. These maps reflect the increase in knowledge of the palaeogeography of the Zechstein as a result of several decades of subsurface exploration. It is found that deposition of the carbonates was controlled by various factors, i.e., rifting during deposition of the basal Zechstein, sea-level fluctuations and basin subsidence. This resulted in an overall E-W orientated facies distribution in the Zechstein carbonates, and in the gradual northward shift of the various facies belts in time.Reefs in the Zl Carbonate Member and off-platform highs and turbidites in the Z2 Carbonate Member have been identified as potential future exploration targets.
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Marroquín, Iván Dimitri, Jean-Jules Brault, and Bruce S. Hart. "A visual data-mining methodology for seismic facies analysis: Part 2 — Application to 3D seismic data." GEOPHYSICS 74, no. 1 (January 2009): P13—P23. http://dx.doi.org/10.1190/1.3046456.
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A visual data-mining approach to unsupervised clustering analysis can be an effective tool for visualizing and understanding patterns inherent in seismic data (i.e., seismic facies). The unsupervised clustering analysis is completely data-driven, requiring no external information (e.g., well logs) to guide the seismic-trace classification. We demonstrate the application of the visual data-mining approach to seismic facies analysis on a real 3D seismic data volume. We select two stratigraphic intervals, the first including a Devonian pinnacle reef system and the second containing a Jurassic siliciclastic channel system. Both analyses show major stratigraphic features that can be defined in horizon slices or other types of visualization. However, the visual data-mining approach creates seismic facies maps with improved visual detail, distinguishing seismic trace-shape variability in the data. We also compare the facies maps with those obtained from a commercial package for seismic facies classification. Both approaches created similar facies maps, but the visual strategy better depicts subtle stratigraphic changes in the bodies being imaged, offering insight into the nature of these features.
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Dixit, Nilesh, Paul McColgan, and Kimberly Kusler. "Machine Learning-Based Probabilistic Lithofacies Prediction from Conventional Well Logs: A Case from the Umiat Oil Field of Alaska." Energies 13, no. 18 (September 17, 2020): 4862. http://dx.doi.org/10.3390/en13184862.
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A good understanding of different rock types and their distribution is critical to locate oil and gas accumulations in the subsurface. Traditionally, rock core samples are used to directly determine the exact rock facies and what geological environments might be present. Core samples are often expensive to recover and, therefore, not always available for each well. Wireline logs provide a cheaper alternative to core samples, but they do not distinguish between various rock facies alone. This problem can be overcome by integrating limited core data with largely available wireline log data with machine learning. Here, we presented an application of machine learning in rock facies predictions based on limited core data from the Umiat Oil Field of Alaska. First, we identified five sandstone reservoir facies within the Lower Grandstand Member using core samples and mineralogical data available for the Umiat 18 well. Next, we applied machine learning algorithms (ascendant hierarchical clustering, self-organizing maps, artificial neural network, and multi-resolution graph-based clustering) to available wireline log data to build our models trained with core-driven information. We found that self-organizing maps provided the best result among other techniques for facies predictions. We used the best self-organizing maps scheme for predicting similar reservoir facies in nearby uncored wells—Umiat 23H and SeaBee-1. We validated our facies prediction results for these wells with observed seismic data.
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Raggatt, Jim, Tim Gibbons, James Stockley, and Ian Deighton. "Browse Basin sequence stratigraphic study." APPEA Journal 52, no. 2 (2012): 703. http://dx.doi.org/10.1071/aj11117.
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In addition to the large gas fields already discovered in the Browse Basin, there is considerable scope for further exploration success because this basin holds an estimated recoverable reserve of 30 tcf gas. TGS has completed the Browse Basin Sequence stratigraphic study to specifically understand the many depositional environments of this basin by a comprehensive analysis of 75 key wells all tied to extensive 2D seismic interpretation. With a standardized lithostratigraphic and chronostratigraphic interpretation, each well has a full 3rd order sequence boundary record across all logged sections, and was subsequently assigned detailed gross depositional environments (GDE). Tied to the GDE’s are specific and highly detailed facies associations, displayed in 26 facies maps, thereby building a robust multi-sequence geological model constrained by sequences. These basin-wide facies maps delineate known source, reservoir and seal and propose where—within the robust geological model—potentially similar facies have been deposited and preserved. This extended abstract is delivered by the Facies Map Browser (FMB), a unique product, containing all data and interpreted maps. The Browse Basin FMB allows users to quickly understand the basin-wide depositional history and interpreted facies. With the multi-well and multi-source background database, the FMB product has proven to shorten the exploration cycle by its sheer level of detail and wide ranging interpretation.
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Zhao, Tao, Fangyu Li, and Kurt J. Marfurt. "Constraining self-organizing map facies analysis with stratigraphy: An approach to increase the credibility in automatic seismic facies classification." Interpretation 5, no. 2 (May 31, 2017): T163—T171. http://dx.doi.org/10.1190/int-2016-0132.1.
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Pattern recognition-based seismic facies analysis techniques are commonly used in modern quantitative seismic interpretation. However, interpreters often treat techniques such as artificial neural networks and self-organizing maps (SOMs) as a “black box” that somehow correlates a suite of attributes to a desired geomorphological or geomechanical facies. Even when the statistical correlations are good, the inability to explain such correlations through principles of geology or physics results in suspicion of the results. The most common multiattribute facies analysis begins by correlating a suite of candidate attributes to a desired output, keeping those that correlate best for subsequent analysis. The analysis then takes place in attribute space rather than ([Formula: see text], [Formula: see text], and [Formula: see text]) space, removing spatial trends often observed by interpreters. We add a stratigraphy layering component to a SOM model that attempts to preserve the intersample relation along the vertical axis. Specifically, we use a mode decomposition algorithm to capture the sedimentary cycle pattern as an “attribute.” If we correlate this attribute to the training data, it will favor SOM facies maps that follow stratigraphy. We apply this workflow to a Barnett Shale data set and find that the constrained SOM facies map shows layers that are easily overlooked on traditional unconstrained SOM facies map.
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Zhao, Tao, Jing Zhang, Fangyu Li, and Kurt J. Marfurt. "Characterizing a turbidite system in Canterbury Basin, New Zealand, using seismic attributes and distance-preserving self-organizing maps." Interpretation 4, no. 1 (February 1, 2016): SB79—SB89. http://dx.doi.org/10.1190/int-2015-0094.1.
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Recent developments in seismic attributes and seismic facies classification techniques have greatly enhanced the capability of interpreters to delineate and characterize features that are not prominent in conventional 3D seismic amplitude volumes. The use of appropriate seismic attributes that quantify the characteristics of different geologic facies can accelerate and partially automate the interpretation process. Self-organizing maps (SOMs) are a popular seismic facies classification tool that extract similar patterns embedded with multiple seismic attribute volumes. By preserving the distance in the input data space into the SOM latent space, the internal relation among data vectors on an SOM facies map is better presented, resulting in a more reliable classification. We have determined the effectiveness of the modified algorithm by applying it to a turbidite system in Canterbury Basin, offshore New Zealand. By incorporating seismic attributes and distance-preserving SOM classification, we were able to observe architectural elements that are overlooked when using a conventional seismic amplitude volume for interpretation.
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Sahoo, Tusar, Peter King, Kyle Bland, Dominic Strogen, Richard Sykes, and Francois Bache. "Tectono-sedimentary evolution and source rock distribution of the mid to Late Cretaceous succession in the Great South Basin, New Zealand." APPEA Journal 54, no. 1 (2014): 259. http://dx.doi.org/10.1071/aj13026.
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The Great South Basin, off New Zealand’s southeast coast, has attracted renewed exploration interest from major petroleum companies since 2005. The distribution of the mid Cretaceous to Paleocene source rocks (coals and coaly mudstones) is a critical component in evaluating basin prospectivity. This paper delineates source rock distribution from seismic facies characterisation, and presents a series of updated paleogeographic maps over the initial (Cretaceous) phases of basin evolution. Basin evolution has been analysed from mapped sequence stratigraphic boundaries and isochron maps. Seismic facies were characterised based on the amplitude, continuity, and stacking pattern of the reflection packages. The identified facies were calibrated with well data for age, gross lithology, and gross depositional environment. Areas of source rock deposition were demarcated using seismic attribute interval maps, from which a series of updated paleogeographic maps was prepared. Four second-order sequences have been identified within the Cretaceous succession. The lower two sequences are mainly fault bounded and were deposited in a syn-rift phase. In contrast, the upper two sequences reflect a change in basin character from rifting to a post-rift thermal sag phase. Source facies within both the syn- and post-rift sequences were deposited in mainly non-marine to marginal marine settings, although there is also the possibility of lacustrine source rocks in isolated syn-rift depocentres. The wide geographic spread of source rock intervals within the Cretaceous sequences allows for a variety of petroleum generation and exploration play scenarios.
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Qian, Feng, Miao Yin, Xiao-Yang Liu, Yao-Jun Wang, Cai Lu, and Guang-Min Hu. "Unsupervised seismic facies analysis via deep convolutional autoencoders." GEOPHYSICS 83, no. 3 (May 1, 2018): A39—A43. http://dx.doi.org/10.1190/geo2017-0524.1.
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One of the most important goals of seismic stratigraphy studies is to interpret the elements of the seismic facies with respect to the geologic environment. Prestack seismic data carry rich information that can help us get higher resolution and more accurate facies maps. Therefore, it is promising to use prestack seismic data for the seismic facies recognition task. However, because each identified object changes from the poststack trace vectors to a prestack trace matrix, effective feature extraction becomes more challenging. We have developed a novel data-driven offset-temporal feature extraction approach using the deep convolutional autoencoder (DCAE). As an unsupervised deep learning method, DCAE learns nonlinear, discriminant, and invariant features from unlabeled data. Then, seismic facies analysis can be accomplished through the use of conventional classification or clustering techniques (e.g., K-means or self-organizing maps). Using a physical model and field prestack seismic surveys, we comprehensively determine the effectiveness of our scheme. Our results indicate that DCAE provides a much higher resolution than the conventional methods and offers the potential to significantly highlight stratigraphic and depositional information.
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Ozhgibesov, Vladimir Petrovich. "Rules and experience of using lithological triangle for constructing facies maps." Interactive science, no. 3 (May 25, 2016): 18–23. http://dx.doi.org/10.21661/r-79458.
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Pondrelli, M., A. P. Rossi, T. Platz, A. Ivanov, L. Marinangeli, and A. Baliva. "Geological, geomorphological, facies and allostratigraphic maps of the Eberswalde fan delta." Planetary and Space Science 59, no. 11-12 (September 2011): 1166–78. http://dx.doi.org/10.1016/j.pss.2010.10.009.
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Kourki, Meysam, and Mohammad Ali Riahi. "Seismic facies analysis from pre-stack data using self-organizing maps." Journal of Geophysics and Engineering 11, no. 6 (November 6, 2014): 065005. http://dx.doi.org/10.1088/1742-2132/11/6/065005.
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Chang, Yuqing, Andreas S. Stordal, and Randi Valestrand. "Integrated Work Flow of Preserving Facies Realism in History Matching: Application to the Brugge Field." SPE Journal 21, no. 04 (August 15, 2016): 1413–24. http://dx.doi.org/10.2118/179732-pa.
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Summary Data assimilation with ensemble-based inversion methods was successfully applied for parameter estimation in reservoir models. However, in certain complex-reservoir models, it remains challenging to estimate the model parameters and to preserve the geological realism simultaneously. In particular, when handling special-reservoir model parameters such as facies types concerning fluvial channels, one must realize that geological realism becomes one of the key concerns. The main objective of this work is to address these issues for a complex field with a newly extended version of a recently proposed facies-parameterization approach coupled with an ensemble-based data assimilation method. The proposed workflow combines the new facies parameterization and the adaptive gaussian mixture (AGM) filter into the data assimilation framework for channelized reservoirs. To handle discrete-facies parameters, we combine probability maps and truncated Gaussian fields to obtain a continuous parameterization of the facies fields. For the data assimilation, we use the AGM filter, which is an efficient history matching approach that incorporates a resampling routine that allows us to regenerate facies fields with information from the updated probability maps. This work flow is evaluated, for the first time, on a complex field case—the Brugge field. This reservoir model consists of layers with complex channelized structures and layers characterized by reservoir properties generated with variograms. With limited prior knowledge on the facies model, this work flow is shown to be able to preserve the channel continuity while reducing the reservoir model uncertainty with AGM. When applied to a complex reservoir, the proposed work flow provides a geologically consistent and realistic reservoir model that leads to improved capability of predicting subsurface flow behaviors.
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Tomkins, Andrew G., Tim E. Johnson, and Jennifer T. Mitchell. "A review of the chondrite–achondrite transition, and a metamorphic facies series for equilibrated primitive stony meteorites." Meteoritics & Planetary Science 55, no. 4 (April 2020): 857–85. http://dx.doi.org/10.1111/maps.13472.
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Lemberger, Marcus, James Stockley, and Tim Gibbons. "Browse to Bonaparte stratigraphic evaluation." APPEA Journal 53, no. 2 (2013): 483. http://dx.doi.org/10.1071/aj12094.
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After an initial 2010 stratigraphic, depositional environment and facies determination study of 75 wells in the Browse Basin, TGS has pushed this high-resolution project north into the Bonaparte Basin area. The study incorporates a further 165 wells located across the Ashmore Platform, Vulcan Sub-basin, Londonderry High, Malita and Calder Grabens, Sahul and Flamingo synclines, Laminara and Flamingo highs, Sahul Platform, Troubadour Terrace, and offshore Petrel Sub-basin areas. This multi-basin project has combined all the selected relevant public data into one interpretation study and is delivered in an integrated environment—wells are standardised and sequences interpreted. Once depositional environment and facies are allocated, multi-element maps are produced showing how the basin environments change through time and structural evolution. Stratigraphic interpretation has determined 37 sequences and 32 associated facies maps. Both Browse Basin (140,000 km2) and Bonaparte Basin (270,000 km2) are relatively less explored and at different ages in their exploration life-cycle. Both have proved to be oil and gas bearing across numerous different stratigraphic ages with a wide range of trapping and reservoir methods. This study aims to further aid North West Shelf exploration by delineating, among other facets, the presence or otherwise of rocks with reservoir and seal potential and by identifying structural elements such as the Petrel Sub-basin salt diapirs. This regional well data stratigraphic approach has been used across all the UK and Norway continental shelf hydrocarbon provinces. TGS sees the Australian North West Shelf as a province where this approach will further assist sub-surface understanding, and hence exploration success.
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Wang, Zhen, Yan Kun Wang, Man Luo, Kong Hong Ling, and Ya Ping Lin. "Carbonate Depositional Facies Analysis and Reservoir Prediction for Central Block in Pre-Caspian Basin." Advanced Materials Research 734-737 (August 2013): 305–10. http://dx.doi.org/10.4028/www.scientific.net/amr.734-737.305.
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In waveform classification for which abundant seismic data are fully used, neural network algorithm is applied to compare and classify the actual seismic waveforms by traces for one specific formation, so as to delineate the lateral variation of seismic signal in details and thus acquire the seismic facies maps corresponding to geologic characteristics. Moreover, through analysis of drilling data, logging data and depositional facies, the depositional facies belts are further divided for formation and lithologic reservoir prediction. Carbonate reservoir in the Central Block in the east margin of Pre-Caspian Basin is discussed as an example to introduce the application of waveform classification and depositional facies demarcation in the Carboniferous Carbonate reservoir. Favorable reservoir beds are also predicted, contributing to a big breakthrough for risk exploration in this area.
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Hu, Yu Shuang, Jiao Zhang, Shu Fen Liu, and Xi Chen. "Research and Application on Model of Dynamic Controlling Sand in Surennuoer Area." Advanced Materials Research 734-737 (August 2013): 418–21. http://dx.doi.org/10.4028/www.scientific.net/amr.734-737.418.
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Time-space-source dynamic controlling sand theory emphasized the size, supply and distribution of the source changes with time and space. Based on this theory, ramp-type, half-graben type and slots, grooves parallel-type sand control modes were established at Surennuoer oil field. According to the attribute maps and the sandstone thickness maps, the sand scope of nantun group can be determined, after identified the sand control point by using the fault throw statistic and 3D visualization technology. Sedimentary facies and the single well integrated histogram were used to verify the accuracy of the sand body divided. The results showed that: the sand control scope divide very accurately,and the sand control scope dovetail nicely with turbidite fan, braided channel and other sand-rich sedimentary facies.
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Park, No-Wook, and Dong-Ho Jang. "Comparison of Geostatistical Kriging Algorithms for Intertidal Surface Sediment Facies Mapping with Grain Size Data." Scientific World Journal 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/145824.
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This paper compares the predictive performance of different geostatistical kriging algorithms for intertidal surface sediment facies mapping using grain size data. Indicator kriging, which maps facies types from conditional probabilities of predefined facies types, is first considered. In the second approach, grain size fractions are first predicted using cokriging and the facies types are then mapped. As grain size fractions are compositional data, their characteristics should be considered during spatial prediction. For efficient prediction of compositional data, additive log-ratio transformation is applied before cokriging analysis. The predictive performance of cokriging of the transformed variables is compared with that of cokriging of raw fractions in terms of both prediction errors of fractions and facies mapping accuracy. From a case study of the Baramarae tidal flat, Korea, the mapping method based on cokriging of log-ratio transformation of fractions outperformed the one based on cokriging of untransformed fractions in the prediction of fractions and produced the best facies mapping accuracy. Indicator kriging that could not account for the variation of fractions within each facies type showed the worst mapping accuracy. These case study results indicate that the proper processing of grain size fractions as compositional data is important for reliable facies mapping.
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Zhao, Xianzheng, Fengming Jin, Lihui Liu, Yang Xiao, and Li Wang. "Improve impedance inversion by adopting seismic sedimentary-guided a priori model." Interpretation 4, no. 3 (August 1, 2016): T313—T322. http://dx.doi.org/10.1190/int-2015-0221.1.
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We have developed an innovative procedure for model-based seismic inversion in areas with sparse or clustered and biased well control, where lithofacies and geobodies cannot be adequately sampled in wells and correctly represented in a priori acoustic impedance (AI) models constructed with conventional kriging methods. We have applied seismic sedimentology for facies mapping before the model building process. Lithology-calibrated seismic stratal slices contain rich information for analyzing sedimentary geomorphology and dispersal patterns of depositional systems, providing independent geologic knowledge to constrain a priori models. The new information can be incorporated by directional kriging that properly addresses facies types, orientations, and facies boundary conditions. Finally, the improved a priori model can be applied in Bayesian inversion for an updated inverted AI volume. This procedure was applied in a 3D project in Saidong Depression, Erlian Basin, China, with promising results, achieving inverted AI maps with a more complete facies representation, a more reasonable sediment dispersal pattern (orientation), and clearer facies boundaries.
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Zeng, Hongliu, Yawen He, and Leo Zeng. "Impact of sedimentary facies on machine learning of acoustic impedance from seismic data: Lessons from a geologically realistic 3D model." Interpretation 9, no. 3 (August 1, 2021): T1009—T1024. http://dx.doi.org/10.1190/int-2021-0035.1.
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We have developed a new machine-learning (ML) workflow that uses random forest (RF) regression to predict sedimentary-rock properties from stacked and migrated 3D seismic data. The training, validation, and testing are performed with 40 features extracted from a geologically realistic 46 × 66-trace model built in the Miocene Powderhorn Field in South Texas. We focus on the responses of the RF model to sedimentary facies and the strategies adopted to achieve better prediction with various data conditions. We apply explained variation (R2) and root-mean-square (rms) prediction errors to map the relationship between the quality of prediction and the sedimentary facies. In the single-well model, R2 and rms error maps highly resemble sand-percentage maps, or lithofacies maps, showing the facies control on the quality of the ML model. We observe that training with a small well data set (1–10 wells) leads to low and unstable test scores (R2 = 0.2–0.7). The R2 score increases and stabilizes with more (as many as 1000) training wells (R2 = 0.7–0.9), realizing the effective correction of facies bias. The stratigraphic and spatial features are useful and should be used. Weak to moderate random noise (−20 to −15 dB) slightly lowers the training score (R2 < 0.05) and should not be a major concern. Sparse well-supported models can outperform linear regression and model-based inversion and can be useful if caution is exercised. In the best-case scenario (500 wells), the predicted model largely duplicates the true model with a significant improvement in accuracy (R2 = 0.85) and stability. Such results can be applied in most, if not all, exploration and production practices.
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Mudge, W. J., and A. B. Thomson. "THREE-DIMENSIONAL GEOLOGICAL MODELLING IN THE KINGFISH AND WEST KINGFISH OIL FIELDS: THE METHOD AND APPLICATIONS." APPEA Journal 30, no. 1 (1990): 342. http://dx.doi.org/10.1071/aj89022.
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RESMAP is an Exxon proprietary program that makes possible the building of three-dimensional geological models. The models consist of millions of tabular cells contained within a stratigraphic framework. The models are generated by the integration of log analysis, seismic interpretation and the geologist's well picks and interpretation.RESMAP models are easy to access for generating structural and stratigraphic geological cross-sections. Maps such as structure, top of porosity and net sand percentage can be generated as well as subcrop and supercrop maps. Hydrocarbon-in-place estimates are also made from the model.The Kingfish and West Kingfish fields each possess a complex stratigraphic framework and exhibit rapid facies changes in the nearshore marine sediments. Techniques available in RESMAP enable the integration of the well data and seismic maps to produce an accurate stratigraphic framework containing the geometries of truncation onlap and downlap. The interpolation of porosity data from the wells successfully captures the facies distribution. This is due to the excellent well spacing in the vicinity of the facies changes and the ability to place geological constraints on the interpolation.The model provides a valuable communication tool for the mass of data present in a field. The model can also be updated quickly upon receipt of new data, providing a dynamic reservoir description on which to base future field management.
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Liu, Jinlin, Xiaofeng Dai, Lideng Gan, Lei Liu, and Wenkai Lu. "Supervised seismic facies analysis based on image segmentation." GEOPHYSICS 83, no. 2 (March 1, 2018): O25—O30. http://dx.doi.org/10.1190/geo2015-0539.1.
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Seismic facies analysis aims to characterize the seismic expression of a reservoir by placing seismic attributes into classes that are presumably related to geologic heterogeneities. Supervised seismic facies analysis can be used to classify the seismic expression of reservoirs in oil field development using well control as the training samples. Manual seismic facies analysis is often subjective, and it is usually time-consuming. Pattern recognition techniques such as support vector machine and neural networks have been used to automate seismic facies analysis. However, they often do not produce satisfactory spatial continuity in their results. The spurious spatial discontinuities are usually caused by the so-called “over-fitting” problem inherent in these methods. To avoid this issue, we have developed a supervised seismic facies analysis method based on image segmentation that promotes spatial continuity of the classified seismic facies. The seed region growing technique borrowed from image segmentation is used to segment attribute maps outward from points of well control. In addition, we calculate the seismic facies probability distribution at every grid point in the seismic image. We use this probability distribution as a weighting coefficient to allow regions to grow anisotropically. As demonstrated by the results on a field data set, this approach improves spatial continuity and indicates promising results.
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Qi, Jie, Bo Zhang, Bin Lyu, and Kurt Marfurt. "Seismic attribute selection for machine-learning-based facies analysis." GEOPHYSICS 85, no. 2 (January 9, 2020): O17—O35. http://dx.doi.org/10.1190/geo2019-0223.1.
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Interpreters face two main challenges in seismic facies analysis. The first challenge is to define, or “label,” the facies of interest. The second challenge is to select a suite of attributes that can differentiate a target facies from the background reflectivity. Our key objective is to determine which seismic attributes can best differentiate one class of chaotic seismic facies from another using modern machine-learning technology. Although simple 1D histograms provide a list of candidate attributes, they do not provide insight into the optimum number or combination of attributes. To address this limitation, we have conducted an exhaustive search whereby we represent the target and background training facies by high-dimensional Gaussian mixture models (GMMs) for each potential attribute combination. The first step is to choose candidate attributes that may be able to differentiate chaotic mass-transport deposits and salt diapirs from the more conformal, coherent background reflectors. The second step is to draw polygons around the target and background facies to provide the labeled data to be represented by GMMs. Maximizing the distance between all GMM facies pairs provides the optimum number and combination of attributes. We use generative topographic mapping to represent the high-dimensional attribute data by a lower dimensional 2D manifold. Each labeled facies provides a probability density function on the manifold that can be compared to the probability density function of each voxel, providing the likelihood that a given voxel is a member of each of the facies. Our first example maps chaotic seismic facies associated with the development of salt diapirs and minibasins. Our second example successfully delineates karst collapse underlying a shale resource play from north Texas.
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Elisheva, Olga. "RECOGNIZING AND CHARACTERIZING THE TYPES OF THE SECTIONS OF CONTINENTAL DEPOSITS AS THE FRAMEWORK FOR BUILDING FACIES MODELS ACCORDING TO THE AMPLITUDE INTERPRETATION OF 3D SEISMIC DATA." Interexpo GEO-Siberia 2, no. 1 (2019): 58–65. http://dx.doi.org/10.33764/2618-981x-2019-2-1-58-65.
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The article is devoted to the prediction of reservoirs in continental sediments on the basis of combining the results of dynamic interpretation of 3D seismic data and facies modeling. It is believed that the direct carrier of information about the petrophysical properties of reservoirs and their power are the results of drilling. However, in the territory of the Uvat district at the prospecting stage of exploration drilling volume is very limited and maps of effective thicknesses are calculated based on the results of dynamic interpretation of seismic data. Often such maps have errors of up to 5 m or more, so this forecast is always controlled by facies conditions, built according to the core and geophysical studies of wells. In order to correctly compare the forecast of reservoirs according to geological and seismic data, the article proposes an approach to the typification of continental sediment sections, which shows that each type of section is characterized not only by a certain set of sand lithotypes with different filtration and capacitive properties, but also by certain total reservoir thicknesses. The use of this approach allows us to construct facies models of continental sediments adequate to the texture data, and to correctly compare the distribution of reservoirs by seismic data.
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Avseth, P., T. Mukerji, A. Jørstad, G. Mavko, and T. Veggeland. "Seismic reservoir mapping from 3‐D AVO in a North Sea turbidite system." GEOPHYSICS 66, no. 4 (July 2001): 1157–76. http://dx.doi.org/10.1190/1.1487063.
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We present a methodology for estimating uncertainties and mapping probabilities of occurrence of different lithofacies and pore fluids from seismic amplitudes, and apply it to a North Sea turbidite system. The methodology combines well log facies analysis, statistical rock physics, and prestack seismic inversion. The probability maps can be used as input data in exploration risk assessment and as constraints in reservoir modeling and performance forecasting. First, we define seismic‐scale sedimentary units which we refer to as seismic lithofacies. These facies represent populations of data (clusters) that have characteristic geologic and seismic properties. In the North Sea field presented in this paper, we find that unconsolidated thick‐bedded clean sands with water, plane laminated thick‐bedded sands with oil, and pure shales have very similar acoustic impedance distributions. However, the [Formula: see text] ratio helps resolve these ambiguities. We establish a statistically representative training database by identifying seismic lithofacies from thin sections, cores, and well log data for a type well. This procedure is guided by diagnostic rock physics modeling. Based on the training data, we perform multivariate classification of data from other wells in the area. From the classification results, we can create cumulative distribution functions of seismic properties for each facies. Pore fluid variations are accounted for by applying the Biot‐Gassmann theory. Next, we conduct amplitude‐variation‐with‐offset (AVO) analysis to predict seismic lithofacies from seismic data. We assess uncertainties in AVO responses related to the inherent natural variability of each seismic lithofacies using a Monte Carlo technique. Based on the Monte Carlo simulation, we generate bivariate probability density functions (pdfs) of zero‐offset reflectivity [R(0)] versus AVO gradient (G) for different facies combinations. By combining R(0) and G values estimated from 2‐D and 3‐D seismic data with the bivariate pdfs estimated from well logs, we use both discriminant analysis and Bayesian classification to predict lithofacies and pore fluids from seismic amplitudes. The final results are spatial maps of the most likely facies and pore fluids, and their occurrence probabilities. These maps show that the studied turbidite system is a point‐sourced submarine fan in which thick‐bedded clean sands are present in the feeder‐channel and in the lobe channels, interbedded sands and shales in marginal areas of the system, and shales outside the margins of the turbidite fan. Oil is most likely present in the central lobe channel and in parts of the feeder channel.
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Lu, Le, and Dongxiao Zhang. "Assisted History Matching for Fractured Reservoirs by Use of Hough-Transform-Based Parameterization." SPE Journal 20, no. 05 (October 20, 2015): 942–61. http://dx.doi.org/10.2118/176024-pa.
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Summary Successful production in fractured reservoirs is significantly dependent on knowledge of the location, orientation, and conductivity of the fractures. Early water breakthrough can be prevented and sweep efficiency can be improved with the help of comprehensive and accurate information of fracture distributions. However, it is a challenge to estimate fracture distributions by conventional-history-matching methods because of the complexity of such reservoirs. Although there has been great progress in assisted-history-matching techniques during the last 2 decades, estimating fracture distributions in fractured reservoirs is still inefficient because of the strong heterogeneity and spatial discontinuity of model parameters. The performance of assisted-history-matching methods, such as the ensemble Kalman filter, can be significantly degraded by the non-Gaussian distributions of the parameters, such as effective permeability and porosity. On the other hand, although the geometric shapes of fractures may be generated properly at the initial step, they are difficult to preserve after updating, which results in geologically unrealistic fracture-distribution maps. In this study, we develop an assisted-history-matching method for fractured reservoirs with a Hough-transform-based parameterization. The facies maps of fractured reservoirs are parameterized into Hough-function fields in a discrete Hough space, whereas each gridblock in the Hough domain represents a fracture defined by its two Cartesian coordinates: angle θ of its normal and ρ of its algebraic distance from the origin in the flow domain. The length and axial position of the fractures are defined by two additional parameters on the same grid. The Hough-function value of each gridblock in the Hough domain is used as the indicator of the existence of the fracture in the facies map. When this parameterization is implemented in assisted history matching, the parameter fields in the Hough space, instead of the facies maps, are updated conditional on the production history. An inverse transform is performed to generate facies maps for the reservoir simulator. Pointwise prior information, such as known fractures discovered from well-log data, as well as the statistics of fracture orientation, can be honored by the inverse transform throughout the history-matching process. Applications and the effectiveness of this method are demonstrated by 2D synthetic-waterflooding examples. The fracture distributions in reference fields are identified by this method, and updated models are capable of providing improved predictions for prolonged periods of production.
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Yenwongfai, Honore Dzekamelive, Nazmul Haque Mondol, Jan Inge Faleide, and Isabelle Lecomte. "Prestack simultaneous inversion to predict lithology and pore fluid in the Realgrunnen Subgroup of the Goliat Field, southwestern Barents Sea." Interpretation 5, no. 2 (May 31, 2017): SE75—SE96. http://dx.doi.org/10.1190/int-2016-0109.1.
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An integrated multidisciplinary workflow has been implemented for quantitative lithology and fluid predictions from prestack angle gathers and well-log data within the Realgrunnen Subgroup in the Goliat Field, southwestern Barents Sea. We have first performed a qualitative amplitude-variation-with-angle (AVA) attribute analysis to assess the spatial distribution of lithology and fluid anomalies from the seismic data. A simultaneous prestack elastic inversion was then carried out for quantitative estimates of the P-impedance and [Formula: see text] ratio. Probability density functions, a priori lithology, and fluid class proportions extracted from well-log training data are further applied to the inverted P-impedance and [Formula: see text] seismic volumes. The AVA qualitative analysis indicates a class IV response for the top of the reservoir, whereas anomalies from the AVA attribute maps agree largely with the clean sand probabilities predicted from the Bayesian facies classification. The largest misclassification in the lithology classification occurs between shaly sands and shales. A mixed lithology and fluid classification indicates a smaller degree of overlap and allows for the discrimination of hydrocarbon sands. Integration of a qualitative AVA analysis and a quantitative Bayesian probability approach helps in constraining the depositional facies variability within the Realgrunnen Subgroup. Finally, a possible influence of tectonic activity during the deposition of the Realgrunnen reservoir is inferred based on the facies distribution maps.
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Khodabakhshi, Morteza, and Behnam Jafarpour. "Adaptive Conditioning of Multiple-Point Statistical Facies Simulation to Flow Data with Probability Maps." Mathematical Geosciences 46, no. 5 (April 4, 2014): 573–95. http://dx.doi.org/10.1007/s11004-014-9526-1.
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Pendrel, John, and Henk Schouten. "Facies — The drivers for modern inversions." Leading Edge 39, no. 2 (February 2020): 102–9. http://dx.doi.org/10.1190/tle39020102.1.
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It is common practice to make facies estimations from the outcomes of seismic inversions and their derivatives. Bayesian analysis methods are a popular approach to this. Facies are important indicators of hydrocarbon deposition and geologic processes. They are critical to geoscientists and engineers. The application of Bayes’ rule maps prior probabilities to posterior probabilities when given new evidence from observations. Per-facies elastic probability density functions (ePDFs) are constructed from elastic-log and rock-physics model crossplots, over which inversion results are superimposed. The ePDFs are templates for Bayesian analysis. In the context of reservoir characterization, the new information comes from seismic inversions. The results are volumes of the probabilities of occurrences of each of the facies at all points in 3D space. The concepts of Bayesian inference have been applied to the task of building low-frequency models for seismic inversions without well-log interpolation. Both a constant structurally compliant elastic trend approach and a facies-driven method, where models are constructed from per-facies trends and initial facies estimates, have been tested. The workflows make use of complete 3D prior information and measure and account for biases and uncertainties in the inversions and prior information. Proper accounting for these types of effects ensures that rock-physics models and inversion data prepared for reservoir property analysis are consistent. The effectiveness of these workflows has been demonstrated by using a Gulf of Mexico data set. We have shown how facies estimates can be effectively used to build reasonable low-frequency models for inversion, which obviate the need for well-log interpolation and provide full 3D variability. The results are more accurate probability-based net-pay estimates that correspond better to geology. We evaluate the workflows by using several measures including precision, confidence, and probabilistic net pay.
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Kelly, Colter J., Daniel E. Harlov, David A. Schneider, Simon E. Jackson, and Renelle Dubosq. "Experimental fluid-mediated alteration of zircon under lower greenschist facies conditions." Canadian Mineralogist 58, no. 2 (March 1, 2020): 247–65. http://dx.doi.org/10.3749/canmin.1900041.
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ABSTRACT The use of zircon in the dating of geological processes and tectonic events has become a standard approach in many aspects of Earth science research. As a result, understanding how zircon interacts with aqueous fluids during metasomatism has become increasingly important. The alteration of natural zircon is driven primarily by coupled dissolution–reprecipitation or by ion-exchange with an aqueous fluid. In this study, whole and intact, euhedral light-brown zircon crystals (100–250 μm in length; 2 mg) from the Oligocene Fish Canyon Tuff (FCT) were experimentally reacted with an alkali-bearing reactive fluid and a REE + P source (0.5 mg CePO4 or 0.5 mg YPO4). Experiments were conducted in sealed Au metal capsules at 350 °C and 100 MPa for 182 days. During the experiment, the zircon became colorless, indicating annealing of the radiation damage in the crystal. Two-dimensional element maps of the outermost 3 μm of unpolished zircon crystal surfaces were produced using a grind of contiguous 7 μm analytical spots via laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). The chemical maps indicate that the surface of the zircon crystals from each experiment heterogeneously reacted with the fluid, such that the Ce and Y concentration of chemically modified areas increased (by an order of magnitude) in the CePO4-bearing and YPO4-bearing experiments, respectively, when compared with the chemical maps of unaltered zircon grain surfaces. Helium ion microscopy of polished crystals revealed discontinuous micron-scale altered domains at the crystal margin, consistent with the findings of the unpolished mapping technique. Interestingly, the Th and U concentration of the altered zircon grain surfaces were consistent with the unaltered zircon regardless of the experiment. Incorporation of REEs on the zircon grain surface likely occurred via the coupled substitution REE3+ + P5+ ↔ Zr4+ + Si4+. The results from these experiments imply that the surfaces of minimally metamict zircon can be chemically modified by alkali-bearing fluids via ion exchange under lower greenschist pressures and temperatures over relatively short time periods with respect to the geological time scale.
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Levitan, M. A., T. A. Antonova, and A. V. Koltsova. "Facies structure and quantitative parameters of the Fiji sea pleistocene sediments." Геохимия 64, no. 11 (December 5, 2019): 1206–12. http://dx.doi.org/10.31857/s0016-752564111206-1212.
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Lithological-facies zonality of Neo- and Eopleistocene sediments from the Fiji Sea is described firstly. Processing of corresponding maps and isopachite schemes by volumetric method of A.B. Ronov gave us an opportunity to calculate quantitative parameters of sedimentation for revealed different types of Pleistocene sediments. Carbonate sediments dominate among other groups of sediments. In Neopleistocene carbonate plankton sediments have been accumulated more intensively than in Eopleistocene. The highest volcanic-tectonic activity is typical for Eopleistocene.
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Xie, Tao, Xiaodong Zheng, and Yan Zhang. "Seismic facies analysis based on speech recognition feature parameters." GEOPHYSICS 82, no. 3 (May 1, 2017): O23—O35. http://dx.doi.org/10.1190/geo2016-0121.1.
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Seismic facies analysis plays an important role in seismic stratigraphy. Seismic attributes have been widely applied to seismic facies analysis. One of the most important steps is to optimize the most sensitive attributes with regard to reservoir characteristics. Using different attribute combinations in multidimensional analyses will yield different solutions. Acoustic waves and seismic waves propagating in an elastic medium follow the same law of physics. The generation process of a speech signal based on the acoustic model is similar to the seismic data of the convolution model. We have developed the mel-frequency cepstrum coefficients (MFCCs), which have been successfully applied in speech recognition, as feature parameters for seismic facies analysis. Information about the wavelet and reflection coefficients is well-separated in these cepstrum-domain parameters. Specifically, information about the wavelet mainly appears in the low-domain part, and information about the reflection coefficients mainly appeared in the high-domain part. In the forward model, the seismic MFCCs are used as feature vectors for synthetic data with a noise level of zero and 5%. The Bayesian network is used to classify the traces. Then, classification accuracy rates versus different orders of the MFCCs are obtained. The forwarding results indicate that high accuracy rates are achieved when the order exceeds 10. For the real field data, the seismic data are decomposed into a set of MFCC parameters. The different information is unfolded in the parameter maps, enabling the interpreter to capture the geologic features of the target interval. The geologic features presented in the three instantaneous attributes and coherence can also be found in the MFCC parameter maps. The classification results are in accordance with the paleogeomorphy of the target interval as well as the known wells. The results from the synthetic data and real field data demonstrate the information description abilities of the seismic MFCC parameters. Therefore, using the speech feature parameters to extract information may be helpful for processing and interpreting seismic data.
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García-Chinchilla, Daniel Alejandro, and Silvio Roberto Farias Vlach. "Geological mapping of intrusive rocks: a case study in the Garzón region, the Eastern Cordillera of the Colombian Andes." Geologia USP. Série Científica 19, no. 4 (December 20, 2019): 43–62. http://dx.doi.org/10.11606/issn.2316-9095.v19-158365.
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Jurassic granites (sensu lato) and related rocks are the most abundant rocks cropping out in the Eastern Cordillera of Colombia in the northern Andes. We present an attempt to map and characterize in detail the petrographic diversity of the Jurassic granites and related subvolcanic rocks emplaced in the Garzón region, southernmost the Eastern Cordillera. We also provide new geological maps for the Algeciras and Altamira Plutonic Massifs based on descriptive concepts of the petrographic facies and facies associations and detailed petrographic and mineralogical characterizations of the observed granite types. Eight plutonic and three subvolcanic petrographic facies or facies associations were mapped in the Algeciras Plutonic Massif, and another five in the Altamira Plutonic Massif. Hornblende biotite granites (syeno- and monzogranites) are the main plutonic types constituting the first massif, while leucogranites prevail in the second massif; a zoned facies distribution was mapped in the Algeciras Plutonic Massif. Felsic porphyries (dacite and rhyolite) crop out as minor irregular intrusive bodies or dikes and mafic-intermediate syn-plutonic dikes (mostly microdiorites) cross cut the main plutonic rocks in both massifs. Geological and petrographic characteristics (e.g. micrographic textures) suggest relatively shallow emplacement levels for the plutonic rocks as well as slightly high uplift and erosion rates at the north of the studied area. Local penetrative solid-state planar structures and dike orientations conform with dextral strike-slip movements along the SSW-NNE trending Algeciras Fault System in a transpressional regime associated with a major compressive and oblique convergence in Jurassic ages.
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Roy, Atish, Araceli S. Romero-Peláez, Tim J. Kwiatkowski, and Kurt J. Marfurt. "Generative topographic mapping for seismic facies estimation of a carbonate wash, Veracruz Basin, southern Mexico." Interpretation 2, no. 1 (February 1, 2014): SA31—SA47. http://dx.doi.org/10.1190/int-2013-0077.1.
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Seismic facies estimation is a critical component in understanding the stratigraphy and lithology of hydrocarbon reservoirs. With the adoption of 3D technology and increasing survey size, manual techniques of facies classification have become increasingly time consuming. Besides, the numbers of seismic attributes have increased dramatically, providing increasingly accurate measurements of reflector morphology. However, these seismic attributes add multiple “dimensions” to the data greatly expanding the amount of data to be analyzed. Principal component analysis and self-organizing maps (SOMs) are popular techniques to reduce such dimensionality by projecting the data onto a lower order space in which clusters can be more readily identified and interpreted. After dimensional reduction, popular classification algorithms such as neural net, K-means, and Kohonen SOMs are routinely done for general well log prediction or analysis and seismic facies modeling. Although these clustering methods have been successful in many hydrocarbon exploration projects, they have some inherent limitations. We explored one of the recent techniques known as generative topographic mapping (GTM), which takes care of the shortcomings of Kohonen SOMs and helps in data classification. We applied GTM to perform multiattribute seismic facies classification of a carbonate conglomerate oil field in the Veracruz Basin of southern Mexico. The presence of conglomerate carbonates makes the reservoir units laterally and vertically highly heterogeneous, which are observed at well logs, core slabs, and thin section scales. We applied unsupervised GTM classification to determine the “natural” clusters in the data set. Finally, we introduced supervision into GTM and calculated the probability of occurrence of seismic facies seen at the wells over the reservoir units. In this manner, we were able to assign a level of confidence (or risk) to encountering facies that corresponded to good and poor production.
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Levitan, M. A., T. A. Antonova, and A. V. Kol'tsova. "Facies structure and quantitative parameters of pleistocene sediments from the east australian continental margin." Геохимия 64, no. 6 (June 26, 2019): 634–43. http://dx.doi.org/10.31857/s0016-7525646634-643.
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Lithological and facies zonality of Neopleistocene and Eopleistocene sediments of Australian seas is described firstly. Processing of these maps and isopach schemes by A.B. Ronov volumetric method gave us an opportunity to calculate quantitative parameters of sedimentation for different types of Pleistocene sediments. It was revealed the dominance of carbonate sediments comparatively to other sediment groups. In Neopleistocene carbonate planktic sediments and lithogenic sediments accumulated more intensively than in Eopleistocene.
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Wallet, Bradley C., and Robert Hardisty. "Unsupervised seismic facies using Gaussian mixture models." Interpretation 7, no. 3 (August 1, 2019): SE93—SE111. http://dx.doi.org/10.1190/int-2018-0119.1.
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As the use of seismic attributes becomes more widespread, multivariate seismic analysis has become more commonplace for seismic facies analysis. Unsupervised machine-learning techniques provide methods of automatically finding patterns in data with minimal user interaction. When using unsupervised machine-learning techniques, such as [Formula: see text]-means or Kohonen self-organizing maps (SOMs), the number of clusters can often be ambiguously defined and there is no measure of how confident the algorithm is in the classification of data vectors. The model-based probabilistic formulation of Gaussian mixture models (GMMs) allows for the number and shape of clusters to be determined in a more objective manner using a Bayesian framework that considers a model’s likelihood and complexity. Furthermore, the development of alternative expectation-maximization (EM) algorithms has allowed GMMs to be more tailored to unsupervised seismic facies analysis. The classification EM algorithm classifies data vectors according to their posterior probabilities that provide a measurement of uncertainty and ambiguity (often called a soft classification). The neighborhood EM (NEM) algorithm allows for spatial correlations to be considered to make classification volumes more realistic by enforcing spatial continuity. Corendering the classification with the uncertainty and ambiguity measurements produces an intuitive map of unsupervised seismic facies. We apply a model-based classification approach using GMMs to a turbidite system in Canterbury Basin, New Zealand, to clarify results from an initial SOM and highlight areas of uncertainty and ambiguity. Special focus on a channel feature in the turbidite system using an NEM algorithm shows it to be more realistic by considering spatial correlations within the data.
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Medvedev, I. F., D. I. Gubarev, S. S. Derevyagin, M. Yu Nesvetaev, A. Yu Verin, and N. V. Mishchenko. "DIFFERENTIATION OF STRUCTURE LANDSCAPE AND ENVIRONMENTAL INDICATORS." South of Russia: ecology, development 14, no. 1 (April 4, 2019): 94–104. http://dx.doi.org/10.18470/1992-1098-2019-1-94-104.
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Aim.To identify the degree of influence of the morphological heterogeneity of the territory on the ecological state of the agricultural landscape.MethodsThe study was conducted on an area of 608.5 hectares and a horizontal dissection factor of 8.36 km/km2. For the observations, distributed test pads measuring 10 m2 were used. On each type of facies, test sites were laid on arable land in triplicate. We used standard research methods using GIS. Existing thematic terrain maps were digitized and a digital elevation model based on a topographic survey of the terrain was created. Calculations and visualization of data are made using and based on the ArcGIS and Microsoft Excel software.Results.The degree of influence of the types of facies of the landscape area on individual criteria and indicators of arable land productivity (microclimatic indicators, water properties of the soil, elements of fertility) has been established. Spatial ecologically justified differentiation of types of tracts into facies types has been carried out.Main conclusions.The slopes of the northern exposure (I-IVn) have the highest ecological stability. They lead in the content of productive moisture, mobile phosphorus and potassium. The facies of the slopes of the southern exposure (I-IVs) lead by insolation, the content of humus and nitrate nitrogen. The content of heavy metals in the soils and wheat yield is higher on the southern slopes and second-order watersheds (IVn). The maximum productivity of 2.9 t/ha was obtained on the watershed type of facies (V). A close relationship was established (r = -0.72) between productivity and pH of soil, medium – with mobile forms of phosphorus (r = 0.59) and potassium (r = 0.84).
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Eidsvik, Jo, Per Avseth, Henning Omre, Tapan Mukerji, and Gary Mavko. "Stochastic reservoir characterization using prestack seismic data." GEOPHYSICS 69, no. 4 (July 2004): 978–93. http://dx.doi.org/10.1190/1.1778241.
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Reservoir characterization must be based on information from various sources. Well observations, seismic reflection times, and seismic amplitude versus offset (AVO) attributes are integrated in this study to predict the distribution of the reservoir variables, i.e., facies and fluid filling. The prediction problem is cast in a Bayesian setting. The a priori model includes spatial coupling through Markov random field assumptions and intervariable dependencies through nonlinear relations based on rock physics theory, including Gassmann's relation. The likelihood model relating observations to reservoir variables (including lithology facies and pore fluids) is based on approximations to Zoeppritz equations. The model assumptions are summarized in a Bayesian network illustrating the dependencies between the reservoir variables. The posterior model for the reservoir variables conditioned on the available observations is defined by the a priori and likelihood models. This posterior model is not analytically tractable but can be explored by Markov chain Monte Carlo (MCMC) sampling. Realizations of reservoir variables from the posterior model are used to predict the facies and fluid‐filling distribution in the reservoir. A maximum a posteriori (MAP) criterion is used in this study to predict facies and pore‐fluid distributions. The realizations are also used to present probability maps for the favorable (sand, oil) occurrence in the reservoir. Finally, the impact of seismic AVO attributes—AVO gradient, in particular—is studied. The approach is demonstrated on real data from a turbidite sedimentary system in the North Sea. AVO attributes on the interface between reservoir and cap rock are extracted from 3D seismic AVO data. The AVO gradient is shown to be valuable in reducing the ambiguity between facies and fluids in the prediction.
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Aleksandrov, Vadim, Marsel Kadyrov, Andrey Ponomarev, Denis Drugov, and Olga Veduta. "Specific Features of the Geological Structure of the Formations YUS11 and YUS12 of the Sredne-Ugutskoye Oil Field and their Influence on the Effectiveness of Pay Zones Completion." Key Engineering Materials 785 (October 2018): 52–63. http://dx.doi.org/10.4028/www.scientific.net/kem.785.52.
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The choice of the most effective technology for reservoir completion depends mainly on the conditions for the formation of its constituent deposits and the specific features of their geological structure. This circumstance makes it possible to predict the productivity of newly drilled wells, transferred to the pay zone, as well as to plan the necessary geological and technical interventions with maximum efficiency. The research objective is to assess the influence of specific features of the geological structure of the production zone on the effectiveness of pay zones completion. Facies maps for productive formations were constructed with the help of paleogeographic and facies methods of analysis; a detailed geological and routine analysis made it possible to numerically assess the tightness of the connection between the development indices and the geological and geophysical characteristics of the objects under investigation.
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Stanmore, P. J., and E. M. Johnstone. "THE SEARCH FOR STRATIGRAPHIC TRAPS IN THE SOUTHERN PATCHAWARRA TROUGH, SOUTH AUSTRALIA." APPEA Journal 28, no. 1 (1988): 156. http://dx.doi.org/10.1071/aj87014.
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A seismic stratigraphic study of the Early Permian Patchawarra Formation has been undertaken to delineate zones of reservoir sandstone development and to identify stratigraphic hydrocarbon traps in the western Patchawarra Trough region. In this intracratonic basinal setting, the Patchawarra Formation is dominated by paludal and lacustrine sediments with fluvial sandstones. The Patchawarra Formation in the Patchawarra Trough is a prolific, liquids-rich gas producer with discovered-in-place resources approaching 28 x 109 cubic metres (1 TCF).With minimal well control in the study area, seismically defined increments of strata (SIS units) have been mapped areally away from nearby fields. The occurrence of sand-prone facies has been predicted through the development of a palaeogeographic model for each unit.Integration of facies and structural maps has led to the identification of a suite of intraformational and basin edge stratigraphic plays.
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Roy, Atish, Benjamin L. Dowdell, and Kurt J. Marfurt. "Characterizing a Mississippian tripolitic chert reservoir using 3D unsupervised and supervised multiattribute seismic facies analysis: An example from Osage County, Oklahoma." Interpretation 1, no. 2 (November 1, 2013): SB109—SB124. http://dx.doi.org/10.1190/int-2013-0023.1.
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Seismic interpretation is based on the identification of reflector configuration and continuity, with coherent reflectors having a distinct amplitude, frequency, and phase. Skilled interpreters may classify reflector configurations as parallel, converging, truncated, or hummocky, and use their expertise to identify stratigraphic packages and unconformities. In principal, a given pattern can be explicitly defined as a combination of waveform and reflector configuration properties, although such “clustering” is often done subconsciously. Computer-assisted classification of seismic attribute volumes builds on the same concepts. Seismic attributes not only quantify characteristics of the seismic reflection events, but also measure aspects of reflector configurations. The Mississippi Lime resource play of northern Oklahoma and southern Kansas provides a particularly challenging problem. Instead of defining the facies stratigraphically, we need to define them either diagenetically (tight limestone, stratified limestone and nonporous chert, and highly porous tripolitic chert) or structurally (fractured versus unfractured chert and limestone). Using a 3D seismic survey acquired in Osage County Oklahoma, we use Kohonen self-organizing maps to classify different diagenetically altered facies of the Mississippi Lime play. The 256 prototype vectors (potential clusters) reduce to only three or four distinct “natural” clusters. We use ground truth of seismic facies seen on horizontal image logs to fix three average attribute data vectors near the well locations, resulting in three “known” facies, and do a minimum Euclidean distance supervised classification. The predicted clusters correlate well to the poststack impedance inversion result.
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Zhong, Guangfa, Yalin Li, and Dingjin Liu. "Seismic sequence stratigraphy and sedimentary evolution of carbonate reservoirs in the Sinian Dengying Formation, Middle Sichuan Basin, Southwest China." Interpretation 1, no. 1 (August 1, 2013): SA21—SA34. http://dx.doi.org/10.1190/int-2013-0032.1.
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The Sinian Dengying Formation in the Sichuan Basin, southwest China, mainly consisting of dolomites, is one of the most ancient gas-producing series in the world. During the past half-century, gas exploration in the formation has been largely based on the lithostratigraphic correlation, but a regional correlation scheme of time significance is usually insufficient, resulting in the difficulty of lateral correlation of strata between gas fields. Aiming to overcome the problem, we completed an interpretation of about 2500-km 2D regional seismic lines by using the seismic sequence analysis method. As a result, a sequence stratigraphic framework was successfully constructed, which consists of two sequences and five systems tracts. By integrating analysis of isopatch maps with stratal stacking patterns, we identify three depositional facies belts within the formation, which are a shallow-water platform facies belt in the eastern and southern regions, a relatively deep-water (intraplatform) basin facies belt in the northwestern region, and a northwest-dipping slope facies belt between them. During the development of sequence one in the lower of the Dengying Formation, retrogradation and aggradation dominated in the eastern and southern platform region whereas depositional condensation prevailed in the northwestern basin region. At that time, the depocenter was located on the eastern and southern platform region. However, sequence two in the upper of the Dengying Formation is dominated by the northwest-dipping sigmoid, oblique and shingled prograding packages of the platform-margin slope facies belt, indicating that the depositional center was shifted to the previous basin region in the northwest. As a result, the basin was filled gradually, and the platform-slope-basin topography was finally evolved into a northwest-dipping ramp. Our study suggests that the Late Sinian Sichuan Basin would consist of a series of shallow-water platforms separated by relatively deep-water depressions or (intraplatform) basins, which provides important clues for gas exploration.
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Wilson, A. O. "Chapter 7 Exploration implications." Geological Society, London, Memoirs 53, no. 1 (2020): 187–96. http://dx.doi.org/10.1144/m53.7.
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AbstractExploration of the Jurassic hydrocarbon system in the Arabian Intrashelf Basin area is in a mature state. Given the scale of the present day anticlinal structures and the adjacent synclines, all of the supergiant conventional fields trapped in huge anticlines have already been discovered. The theme throughout this Memoir has been to present the evolution of the self-contained Callovian–Tithonian Arabian Intrashelf Basin hydrocarbon system. Its size, c. 1200 × 450 km, is greater than that of the UK, larger than the Black Sea and almost as large as Turkey or the area of Texas and New Mexico in the USA. It is geologically much simpler than these regions, both in the exceptionally remarkable continuity of facies within the sequences that developed and filled the intrashelf basin and its relative tectonic simplicity, including up to the present day. The cross-sections, facies maps, depositional profiles and other data and interpretations presented in this Memoir have documented this remarkable continuity. The source rock interval is well-defined everywhere it occurs and is mature; enough oil has been generated and migrated so that every sealed trap with reservoir facies will have oil. Around and within the basin, shallow water ramp facies in each sequence are in the reservoir facies and the early-formed porosity has been preserved. The carbonate seals and, even more so, the evaporite seals are remarkably laterally continuous. Therefore the big issue in future exploration is finding a sealed trap with potential reserves large enough to be worth drilling when compared to known reserves and estimates of future production. This chapter discusses some possibilities for stratigraphic traps and unconventional plays. Potential plays have been and/or can be identified, but finding them in the present day structural setting is likely to be very difficult.
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Chen, Pan Pan, Jun Xie, Cun Lei Li, Meng Qi Wang, Yi Dan Liu, and Bai Chuan Li. "Application of Facies-Controlled Physical Property Modeling in Oubei Block, Jinhu Depression." Applied Mechanics and Materials 522-524 (February 2014): 1359–62. http://dx.doi.org/10.4028/www.scientific.net/amm.522-524.1359.
Full textAbstract:
Three dimensional (3D) models provide insights into the distribution, external and internal geometry of the reservoirs. The core description shows that the fourth segment of Funing Formation (E1f4), Oubei Block, Jinhu Depression mainly develop delta front subfacies which included underwater distributary channel, mouth bar, sand sheet and so on. Well data and structural maps were integrated to build 3D structure model and sedimentary microfacies model of Oubei reservoirs using stochastic simulations with geometry data. The result of facies-controlled property model can reasonably reflect reservoir characteristics in detail, providing a reliable geological model for late reservoir adjustment and valuable reference for numerical reservoir simulation as well.
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McMechan, George A., Robert G. Loucks, Paul Mescher, and Xiaoxian Zeng. "Characterization of a coalesced, collapsed paleocave reservoir analog using GPR and well‐core data." GEOPHYSICS 67, no. 4 (July 2002): 1148–58. http://dx.doi.org/10.1190/1.1500376.
Full textAbstract:
The three‐dimensional architecture, spatial complexity, and pore‐type distribution are mapped in a near‐surface analog of a coalesced, collapsed paleocave system in the Lower Ordovician Ellenburger Group near the city of Marble Falls in central Texas. The surface area of the site has dimensions of about 350 × 1000 m. The data collected include about 12 km of 50‐MHz ground‐penetrating radar (GPR) data arranged in a grid of orthogonal lines, 29 cores of about 15‐m length, and detailed facies maps of an adjacent quarry face. Electrical property measurements along with detailed core descriptions were the basis of integrated interpretation of the GPR data. Three main GPR facies are defined on the basis of degree of brecciation in the corresponding cores: undisturbed host rock, disturbed host rock, and paleocave breccia. This GPR facies division defined the major paleocave trends and the distribution of porosity types, which correlate with reservoir quality. Highly brecciated zones are separated by disturbed and undisturbed host rock. The breccia bodies that outline the trend of collapsed cave passages are up to 300 m wide; the intervening intact areas between breccias are up to 200 m wide. Understanding the breccia distribution in a reservoir analog will help in defining strategies for efficient development of coalesced, collapsed paleocave reservoirs.
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Zhao, Tao, Vikram Jayaram, Atish Roy, and Kurt J. Marfurt. "A comparison of classification techniques for seismic facies recognition." Interpretation 3, no. 4 (November 1, 2015): SAE29—SAE58. http://dx.doi.org/10.1190/int-2015-0044.1.
Full textAbstract:
During the past decade, the size of 3D seismic data volumes and the number of seismic attributes have increased to the extent that it is difficult, if not impossible, for interpreters to examine every seismic line and time slice. To address this problem, several seismic facies classification algorithms including [Formula: see text]-means, self-organizing maps, generative topographic mapping, support vector machines, Gaussian mixture models, and artificial neural networks have been successfully used to extract features of geologic interest from multiple volumes. Although well documented in the literature, the terminology and complexity of these algorithms may bewilder the average seismic interpreter, and few papers have applied these competing methods to the same data volume. We have reviewed six commonly used algorithms and applied them to a single 3D seismic data volume acquired over the Canterbury Basin, offshore New Zealand, where one of the main objectives was to differentiate the architectural elements of a turbidite system. Not surprisingly, the most important parameter in this analysis was the choice of the correct input attributes, which in turn depended on careful pattern recognition by the interpreter. We found that supervised learning methods provided accurate estimates of the desired seismic facies, whereas unsupervised learning methods also highlighted features that might otherwise be overlooked.
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D’Orefice, Maurizio, Piero Bellotti, Adele Bertini, Gilberto Calderoni, Paolo Censi Neri, Letizia Di Bella, Domenico Fiorenza, et al. "Holocene Evolution of the Burano Paleo-Lagoon (Southern Tuscany, Italy)." Water 12, no. 4 (April 1, 2020): 1007. http://dx.doi.org/10.3390/w12041007.
Full textAbstract:
The study of Burano paleo-lagoon—Wetland of International Value, has allowed us to better define and extend the reconstruction of the Holocene paleoenvironmental evolution of the paleo-lagoons previously studied, located on the Tyrrhenian coast in central Italy. The investigated area is located in Southern Tuscany near the Burano Lake. The area was investigated by means of field surveys, historical maps, 16 coring, sedimentological, palynological and microfaunal analyses (foraminifera and ostracods), combined with robust geochronological control provided by 52 datings (14C and OSL). The study allowed us to reconstruct the environmental and morphological evolution of the Burano paleo-lagoon during the last 8000 years and to hypothesize a Rise Sea Level (RSL) curve. In this context, 5 main evolutionary phases have been recognized. (1) before 7.5 ka BP in the southern-eastern part, an open lagoon developed; (2) ~6 ka BP a barrier-lagoon system develops throughout the entire area and the lagoon progressively changed from open to closed one; (3) ~5 ka BP the width of the lagoon increases and a lacustrine facies appears along the entire axis of the coastal basin; (4) ~4 ka BP the lacustrine facies shows a discontinuous distribution respect to the previous phase; (5) during the last 4 ka the lacustrine facies disappear and the lagoon turns into a wetland area.
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Apak, S. N., W. J. Stuart, and N. M. Lemon. "COMPRESSIONAL CONTROL ON SEDIMENT AND FACIES DISTRIBUTION SW NAPPAMERRI SYNCLINE AND ADJACENT MURTEREE HIGH, COOPER BASIN." APPEA Journal 35, no. 1 (1995): 190. http://dx.doi.org/10.1071/aj94013.
Full textAbstract:
The northeast-trending Nappamerri Syncline and its flanking high to the southeast, the Murteree-Nappacoongee (NM) Trend, show structural development throughout the deposition of the Permo-Triassic Cooper Basin sequences. Pre-existing topography, such as around Moomba, influenced early depositional patterns within the area. Rates of sedimentation were influenced by the rate of uplift of source areas around the basin, largely as a consequence of buckling. Periods of active tectonism resulted in non-deposition and stripping of sediments from uplifted blocks while deposition continued in deeper areas. Hangingwall blocks, pushed up along reverse faults, strongly influenced the areas of sedimentation and the facies being deposited. This is particularly evident along the NM Trend. Phases of uplift were immediately followed by increased sedimentation where fluvial deposition dominated. The effect of displacement along the northwest-trending basement lineaments was to subdivide the northeast trends into compartments which contain similar facies within each time slice. Adjacent compartments may display different facies and different tectonic histories. An inversion episode, particularly evident in the Big Lake/Moomba area, resulted in a reversal of the depocentre and was related to phases of Sakmarian compression.Facies distribution and sandstone percentage maps of the chronostratigraphic units of the Patchawarra Formation suggest that a northeast-trending major channel system entered this part of basin along the NW edge of the Murteree area.
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Dawes, P. R. "Topographical and geological maps of Hall Land, North Greenland. Description of a computer- supported photogrammetrical research programme for production of new maps, and the Lower Palaeozoic and surficial geology." Bulletin Grønlands Geologiske Undersøgelse 155 (January 1, 1987): 1–88. http://dx.doi.org/10.34194/bullggu.v155.6697.
Full textAbstract:
Topographical and geological map sheets covering the northern part of Hall Land (81-82°N) are presented – an area of about 3000 km2. The maps are the products of a research programme in which newly developed photogrammetric techniques have been used in the interpretation and compilation of the topography and the geology (both solid and surficial). The topographical map has been constructed with a minimum of geodetic ground control. The topographic contours have been calculated from a digital elevation model using computer programmes, and automatically plotted out. The geological map has been hand-drawn from 74 manuscript sheets compiled from aerial photograph models on second-order analog stereo-plotting instruments with computer facilities. The maps, the photogrammetric programme and the solid and surficial geology are described in seven chapters. The first two provide an introductory background that explains the motivation for the research, summarises the history of cartographic, geodetic and geologic work and provides a status of research at the start of the programme. The third chapter discusses the various aspects of the photogrammetric programme, instrumentation and the on-line computer facilities utilised, and is followed by a chapter dealing with compilation method, map presentation and assessment of cartographic accuracy compared to previous maps and modern geodetic ground data. The next chapter describes the topography and geomorphology and relates the three main physiographic provinces to the solid and surficial geology. The penultimate chapter outlines the stratigraphy and structure of the Upper Ordovician-Silurian (Llandovery-Pridoli) section through the E-W trending Franklinian basin. In Ordovician-earliest Silurian time, the map area was part of the carbonate platform; in the Llandovery a major shift southwards of the deep-water basin occurred. The Silurian succession displays a regional facies change from platform carbonates in the south, through a major reef belt on the shelf and upper slope to, in the north, clastic turbidites of the lower slope and trough. Facies transitions and interdigitation of shelf-slope-trough lithologies are complex. The northern part of the map exposes the autochthonous margin of the mid-Palaeozoic North Greenland fold belt characterised by E-W folds. The regional structure is an asymmetric synclinorium; a decollement zone probably occurs in the shale sequence that overlies the Lower Silurian carbonate platform. The final chapter describes eight groups of Quaternary deposits and features: moraine, fluviatile-glaciofluvial, marine, lacustrine, colluvial, solifluction, aeolian and periglacial. Hall Land was formerly entirely ice covered, and deposits of several ice advances are preserved; six major marginal moraine systems are defined. Marine deposits are prominent and terrace levels and raised shorelines are well preserved; the Holocene marine limit is at least 125 m above present sea level. Major events are placed within a Pleistocene-Holocene chronostratigraphic framework. Comments on place names are given in an appendix.