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Journal articles on the topic 'Geophysical data interpretation'
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İsgаndаrov, E., and A. Rzabayli. "INTERPRETATION OF GRAVITY DATA BY CORRELATION METHODS." Danish scientific journal, no. 69 (February 24, 2023): 5–10. https://doi.org/10.5281/zenodo.7688727.
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<strong>Abstract</strong> The article is devoted to the issue of interpretation of gravimetric data by correlation methods. As you know, there can be a correlation between geological and geophysical data, or, as they say, a statistical relationship. This connection can be studied by methods of mathematical statistics. Thus, correlations are established between geophysical and geological parameters, for example, between gravity anomalies and the depth of the geological boundary of interest. Such a correlation analysis is first carried out on a reference area with known values of geophysical and geological parameters. On the basis of the analogy principle, using the correlation links established on the standard, geological characteristics are predicted by geophysical parameters within a certain (forecast) territory. Statistical methods for constructing structural maps based on gravity data are mainly used in the modification of multidimensional regression analysis (MRA) and correlation methods for transforming anomalies (COMT). Software for the correlation analysis of gravity data has been developed at the Department of Geophysics of the ASOIU. The article presents the mathematical foundations and results of the forecast of the structural scheme of the surface of the Upper Cretaceous deposits of the Northern Saatly area of the Middle Kura depression of Azerbaijan.
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Dugan, Brandon, Sebastian Krastel, Laurie Whitesell, et al. "Workshop Review: Joint DGG-SEG Scientific Drilling Workshop a success." Leading Edge 40, no. 11 (2021): 837–38. http://dx.doi.org/10.1190/tle40110837.1.
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SEG and the German Geophysical Society (DGG) held their first joint workshop in early March at DGG's 2021 Annual Meeting. The workshop was part of a new cooperative aim between DGG and SEG to promote engagement between the societies, to foster growth in geophysics, and to expand the community of scientists and engineers tackling important geophysical problems. The 2021 workshop theme, “Scientific Drilling,” was chosen because scientific drilling provides access to rocks and fluids in the subsurface that are essential for ground truthing interpretations from geophysical data and geologic interpretation, for providing samples and in-situ data for detailed characterization, and for providing inputs to models. Consequently, the workshop aimed to attract interest across many subfields of geophysics.
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Lozada Aguilar, Miguel Ángel, Andrei Khrennikov, Klaudia Oleschko, and María de Jesús Correa. "Quantum Bayesian perspective for intelligence reservoir characterization, monitoring and management." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 375, no. 2106 (2017): 20160398. http://dx.doi.org/10.1098/rsta.2016.0398.
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The paper starts with a brief review of the literature about uncertainty in geological, geophysical and petrophysical data. In particular, we present the viewpoints of experts in geophysics on the application of Bayesian inference and subjective probability. Then we present arguments that the use of classical probability theory (CP) does not match completely the structure of geophysical data. We emphasize that such data are characterized by contextuality and non-Kolmogorovness (the impossibility to use the CP model), incompleteness as well as incompatibility of some geophysical measurements. These characteristics of geophysical data are similar to the characteristics of quantum physical data. Notwithstanding all this, contextuality can be seen as a major deviation of quantum theory from classical physics. In particular, the contextual probability viewpoint is the essence of the Växjö interpretation of quantum mechanics. We propose to use quantum probability (QP) for decision-making during the characterization, modelling, exploring and management of the intelligent hydrocarbon reservoir . Quantum Bayesianism (QBism), one of the recently developed information interpretations of quantum theory, can be used as the interpretational basis for such QP decision-making in geology, geophysics and petroleum projects design and management. This article is part of the themed issue ‘Second quantum revolution: foundational questions’.
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Archer, C. T. "Integrated interpretation of SPECTREM geophysical data." Exploration Geophysics 29, no. 1-2 (1998): 83–86. http://dx.doi.org/10.1071/eg998083.
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Ruslan Malikov, Gulam Babayev, Ruslan Malikov, Gulam Babayev. "THE ROLE OF ARTIFICIAL INTELLIGENCE IN GEOSCIENCES: CONCEPTUAL REVIEW." PAHTEI-Procedings of Azerbaijan High Technical Educational Institutions 43, no. 08-01 (2024): 500–512. http://dx.doi.org/10.36962/pahtei4308012024-56.
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Geophysics is the branch of Earth science that applies the principles and methods of physics to the study of the Earth. Recent advances in artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), are transforming the field by providing powerful tools for data processing, analysis, and prediction. Traditional geophysical methods are often challenged by data complexity, non-unique solutions, and human interpretation limitations. AI algorithms trained on large datasets can identify intricate patterns and relationships within the data, leading to improved accuracy and efficiency. In this review, we provide an overview of the development of AI in the geophysical field such as seismic exploration. Specific examples illustrate the application of AI in geophysical workflows, highlighting the results achieved in areas such as seismic data processing, reservoir characterization, and automated seismic interpretation. Keywords: geophysics, seismic prospecting, exploration geophysics, artificial intelligence, machine learning, deep learning
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Chauhan, Mahak Singh, Abhey Ram Bansal, and V. P. Dimri. "Scaling Laws and Fractal Geometry: Insights into Geophysical Data Interpretations." Journal Of The Geological Society Of India 101, no. 6 (2025): 983–89. https://doi.org/10.17491/jgsi/2025/174196.
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ABSTRACT Fractals, characterised by self-similarity and scale invariance, have emerged as powerful tools for understanding complex systems in geophysics. This paper highlights the applications of fractal geometry in geophysical data interpretation. For instance, fractal analysis is used in seismology to understand the fault systems, earthquake distribution, and the scaling laws governing seismic events. In potential fields, fractals are used to find the source depth, to design the optimum grid size of the survey, to detect the source and to separate signal from noise. In this paper, we first highlight the basics of fractal theory and then show how fractals are useful in various geophysical studies by showing examples from potential fields and seismology and reservoir characterisation.
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Paembonan, Andri Yadi, Asido Saputra Sigalingging, Putu Pradnya Andika, Selvi Misnia Irawati, Edlyn Yoadan Nathania, and Muhammad Rendi Jaya. "C-RIA: RESISTIVITY DATA INTERPRETATION AND ANALYSIS IN CLOUD MODE." JGE (Jurnal Geofisika Eksplorasi) 10, no. 1 (2024): 65–77. http://dx.doi.org/10.23960/jge.v10i1.389.
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Geophysical methods generally require one or several processes before interpretation is carried out. This process usually requires software that requires fast computer technology. The better the computer device, the faster data can be processed. We propose a new approach in processing and interpreting and integrating geophysical data, especially resistivity data, using cloud technology. This technology is generally able to increase the speed of processing and interpreting geophysical data, which really requires devices with fast capabilities. Not to mention, if there is a lot of data being processed, it will take a long time just to process the data. Therefore, by using cloud technology the work can be done efficiently because it uses computers with modern and fast technology. In this research we apply this technology to geophysical data that is most often used for shallow exploration, namely the resistivity geoelectric method. With this research, we hope that data processing and geophysical data inversion will be more efficient and effective and the data will be safer.
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Dell'Aversana, Paolo. "Listening to geophysics: Audio processing tools for geophysical data analysis and interpretation." Leading Edge 32, no. 8 (2013): 980–87. http://dx.doi.org/10.1190/tle32080980.1.
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Li, Yaoguo, Aline Melo, Cericia Martinez, and Jiajia Sun. "Geology differentiation: A new frontier in quantitative geophysical interpretation in mineral exploration." Leading Edge 38, no. 1 (2019): 60–66. http://dx.doi.org/10.1190/tle38010060.1.
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Geophysics aims to image subsurface geologic structure and identify different geologic units. While the former has dominated the interpretation of applied geophysical data, the latter has received much less attention. This appears to have persisted despite applications such as those in mineral exploration that inherently rely on the inference of geologic units from geophysical and geologic observations. In practice, such activities are routinely carried out in a qualitative manner. Thus, it is meaningful to examine this aspect and to develop a system of quantitative approaches to identify different geologic units. The development of geophysical inversions in the last three decades makes such interpretation tools possible. We refer to this newly emerging direction as geology differentiation and the resultant representation of geology model as a quasi-geology model. In this article, we will provide an overview of the historical background of geology differentiation and the current developments based on physical property inversions of geophysical data sets. We argue that integrating multiple physical property models to differentiate and characterize geologic units and work with the derived quasi-geology model may lead to a step change in maximizing the value of geophysical inversions.
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Lyrio, Julio Cesar S. O., Paulo T. L. Menezes, Jorlivan L. Correa, and Adriano R. Viana. "Multiphysics anomaly map: A new data fusion workflow for geophysical interpretation." Interpretation 8, no. 2 (2020): B35—B43. http://dx.doi.org/10.1190/int-2018-0178.1.
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When collecting and processing geophysical data for exploration, the same geologic feature can generate a different response for each rock property being targeted. Typically, the units of these responses may differ by several orders of magnitude; therefore, the combination of geophysical data in integrated interpretation is not a straightforward process and cannot be performed by visual inspection only. The multiphysics anomaly map (MAM) that we have developed is a data fusion solution that consists of a spatial representation of the correlation between anomalies detected with different geophysical methods. In the MAM, we mathematically process geophysical data such as seismic attributes, gravity, magnetic, and resistivity before combining them in a single map. In each data set, anomalous regions of interest, which are problem-dependent, are selected by the interpreter. Selected anomalies are highlighted through the use of a logistic function, which is specially designed to clip large magnitudes and rescale the range of values, increasing the discrimination of anomalies. The resulting anomalies, named logistic anomalies, represent regions of large probabilities of target occurrence. This new solution highlights areas where individual interpretations of different geophysical methods correlate, increasing the confidence in the interpretation. We determine the effectiveness of our MAM with application to real data from onshore and offshore Brazil. In the onshore Recôncavo Basin, the MAM allows the interpreter to identify a channel where a drilled well found the largest sandstone thickness on the area. In a second example, from offshore Sergipe-Alagoas Basin, the MAM helps differentiate between a dry and an oil-bearing channel previously outlined in seismic data. Therefore, these outcomes indicate that the MAM is a valid interpretation tool that we believe can be applied to a wide range of geologic problems.
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Loginov, D. S. "Cartographic support of geophysical research: current situation and prospects." Geodesy and Cartography 950, no. 8 (2019): 32–44. http://dx.doi.org/10.22389/0016-7126-2019-950-8-32-44.
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The features of cartographic supporting geophysical research at the present stage of cartography and exploration geophysics development are discussed. The current situation and prospects of using GIS and web technologies are characterized basing on the analysis of scientific and industrial experience of domestic and foreign public as well as private geological and geophysical organizations. The analysis was performed at key stages of geophysical research, including the analysis of geological and geophysical studying the work area, designing geophysical works, field works, processing and interpretation of geophysical observations results, compilation of reporting materials, as well as the accumulation and storage of information. The examples of modern geoportals that provide quick access to geological and geophysical infor-mation in various forms of presentation, including cartographic data, are presented in article. The conclusions and recommendations were formulated according to results of the study. They are aimed at improving the efficiency of cartographic supporting geophysical research and the development of inter-sectoral interaction between cartography and geophysics.
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Singh, Ramesh P., Anupma Rastogi, and A. Adam. "Combined interpretation of MAGSAT and surface geophysical data." Advances in Space Research 13, no. 11 (1993): 43–50. http://dx.doi.org/10.1016/0273-1177(93)90200-u.
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Wang, Shunji, Guanwen Gu, Ye Wu, et al. "A Comprehensive Geophysical Exploration of Sedimentary Exhalative Deposits: An Example from the Huaniushan Lead–Zinc–Silver Polymetallic Deposit in Gansu, China." Minerals 14, no. 11 (2024): 1066. http://dx.doi.org/10.3390/min14111066.
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The Huaniushan lead–zinc–silver deposit is a hydrothermal sedimentary exhalative deposit (SEDEX), and the mining area has complex geological conditions, with the main tectonic structure being the Huaheitan–Shuangfengshan Fault (F3), which controls the distribution of strata and magmatic rocks. Since the discovery of the Huaniushan lead–zinc–silver deposit, diverse interpretations of its genesis and metallogeny have been proposed, making it challenging to establish a definitive geological explanation. Moreover, using a single geophysical exploration method relies on limited rock physical parameters, making it difficult to effectively characterize underground structures. The combined use of multiple geophysical methods can effectively integrate the geophysical characteristics of different rock physical parameters, reducing the multiplicity and uncertainty of the inverse interpretation of geophysical data. The comprehensive interpretation of three-dimensional inversion based on various geophysical data, the construction of geological–geophysical models on geological grounds, the establishment of hidden ore exploration and positioning, and the rapid evaluation of geophysical technological systems are the current research trends in mineral exploration. In light of this, in this study, we conducted research on the three-dimensional inversion interpretation of gravity and magnetoelectric exploration data of the Huaniushan sedimentary exhalative lead–zinc–silver polymetallic deposit and constructed a three-dimensional geological–geophysical model of the study area based on the obtained three-dimensional physical structure of the underground density, magnetization intensity, resistivity, and polarizability of the study area, in combination with related geological and drilling hole data. Finally, we comprehensively interpreted the favorable mineralization sites in the study area.
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Keating, P. B., and D. J. Crossley. "The inversion of time‐domain airborne electromagnetic data using the plate model." GEOPHYSICS 55, no. 6 (1990): 705–11. http://dx.doi.org/10.1190/1.1442882.
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Airborne electromagnetic (EM) methods were developed in the early 1950s, mostly by Canadian mining exploration companies as a means of economically carrying out prospecting for sulfide deposits associated with volcanics in resistive shield areas. Present interpretation techniques are based on the use of nomograms but the approach is easily amenable to digital processing. For highly accurate interpretation, however, it is necessary to develop quantitative interpretation techniques that can make full use of all the data available. Inverse theory has been used for interpretation with great success in most geophysical disciplines; however, in airborne EM surveying, inversion has only been used for the interpretation of airborne EM data using half‐space and one‐layer models. By introducing some approximations to the rectangular thin‐plate model, it is now possible to apply inverse theory to the interpretation of time‐domain EM data. This approach provides estimates of the parameter errors, the correlation matrix, and a means of assessing the validity of the model. Synthetic profile data are used to demonstrate the validity of the method. The results of the inversion of real anomalies are compared with ground geophysical survey interpretation and drillhole data. The inversion results agree with the known geology of the area and the ground geophysical survey interpretation.
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Tzanis, Andreas. "A MATLAB PROGRAM FOR THE ANALYSIS AND INTERPRETATION OF TRANSIENT ELECTROMAGNETIC SOUNDING DATA." Bulletin of the Geological Society of Greece 43, no. 4 (2017): 1941. http://dx.doi.org/10.12681/bgsg.11385.
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Herein we present a software system, written in MATLAB, to interpret TEM sounding data. The program, dubbed maTEM, is designed to process, model and invert multiple soundings, either individually, or simultaneously along profiles. The latter capability allows for laterally constrained inversion, so as to generate pseudo-2D or 2D resistivity sections based on the program EM1DINV v2.13 by the Hydro-Geophysics Group of the University of Aarhus, Denmark. Using maTEM, the analyst may import and display data multiple data sets, denoise and smooth the data, perform approximate inversions, design 1-D model(s) graphically, perform forward modelling and inversion and generate/ update data base in which to store the results. Finally, the analyst may use the data base to create 2-D and 3-D displays of the geoelectric structure with built-in graphical functions. maTEM is highly modular so that additional functions can be added at any time, at minimal programming cost. Although the software presented herein is focused on the analysis of TEM data, the maTEM concept has been designed ready to incorporate additional electrical and EM geophysical sounding methods and to mutually constrained analysis of different geophysical data sets.
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Senchina, Nataliya P., and Tatyana A. Mingaleva. "Multi-feature petrophysical classification of rocks as a basis for interpretation of geophysical data." Izvestiya of Saratov University. Earth Sciences 22, no. 3 (2022): 208–18. http://dx.doi.org/10.18500/1819-7663-2022-22-3-208-218.
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The work is carried out approbation of the algorithm for the complex interpretation of geophysical data using data classification algorithm. Distributions by class are obtained and compared with petrophysical materials from published sources. This data is compared and geological composition of the studied area is obtained. The applicability of this approach for the integrated interpretation of geophysical data is shown, including low-level studied areas with a complex geological structure.
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Anderson-Mayes, Ann-Marie, and Gregory J. Street. "A conceptual framework for interpretation of airborne geophysical data." ASEG Extended Abstracts 2003, no. 2 (2003): 1–5. http://dx.doi.org/10.1071/aseg2003ab002.
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Song, Yu-Chen, Hai-Dong Meng, Michael J. O’Grady, and Gregory M. P. O’Hare. "The application of cluster analysis in geophysical data interpretation." Computational Geosciences 14, no. 2 (2009): 263–71. http://dx.doi.org/10.1007/s10596-009-9150-1.
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Kussainova, А. Т., Z. O. Oralbekova, M. G. Zhartybayeva, and N. Serik. "THE INTERPRETATION TECHNIQUE OF GEOPHYSICAL DATA BY USING IT." Bulletin D. Serikbayev of EKTU, no. 4 (December 2023): 267–73. http://dx.doi.org/10.51885/1561-4212_2023_4_267.
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Қазіргі уақытта өнімділігі жоғары есептеуіш технологияларды пайдалана отырып, геофизиканың қолданбалы есептерін шешу үшін алгоритмдер мен бағдарламалық қамтамасыз етуді әзірлеудің өзекті қажеттілігі туындап отыр. Осыны ескере отырып, бұл жұмыстың мақсаты геологиялық қималар деректерінің репозиторийін және таңдау әдісіне ыңғайлы веб-қосымшаны құру болып табылады. Бұл қолданба академик А.Н. Тихонов ұсынған үйлестіре таңдау әдісін қолдана отырып, мақсатты класстар мен пайдаланылатын орта үлгілеріне негізделген деректерге оңай қол жеткізуді қамтамасыз етеді. Авторлар әртүрлі техникалық сипаттамалары бар заманауи радиолокациялық жүйелерді пайдалана отырып, бірқатар эксперименттерді сәтті жүргізді. Бұдан басқа, олар аймақта бұрыннан бар үлгілерден шағылысқан сигналдарды тіркеп, қосымша өлшеулер жүргізілді. Теориялық болжамдарды эксперименттік бақылауларға қарсы қоя отырып, жан-жақты салыстырмалы талдау жүргізілді. Бұл талдау геологиялық кескіндердің деректер қорында сақталған қазіргі заманғы радиолокациялық деректердің үлкен көлеміне негізделген.
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Paasche, Hendrik, and Jens Tronicke. "Cooperative inversion of 2D geophysical data sets: A zonal approach based on fuzzy c-means cluster analysis." GEOPHYSICS 72, no. 3 (2007): A35—A39. http://dx.doi.org/10.1190/1.2670341.
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In many near-surface geophysical applications, it is now common practice to use multiple geophysical methods to explore subsurface structures and parameters. Such multimethod-based exploration strategies can significantly reduce uncertainties and ambiguities in geophysical data analysis and interpretation. We propose a novel 2D approach based on fuzzy [Formula: see text]-means cluster analysis for the cooperative inversion of disparate data sets. We show that this approach results in a single zonal model of subsurface structures in which each zone is characterized by a set of different parameters. This finding implies that no further structural interpretation of geophysical parameter fields is needed, which is a major advantage compared with conventional inversions that rely on a single input data set and cooperative inversion approaches.
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Guo, Zhenwei, Xiangping Hu, Jianxin Liu, Chunming Liu, and Jianping Xiao. "Geophysical Field Data Interpolation Using Stochastic Partial Differential Equations for Gold Exploration in Dayaoshan, Guangxi, China." Minerals 9, no. 1 (2018): 14. http://dx.doi.org/10.3390/min9010014.
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In a geophysical survey, one of the main challenges is to estimate the physical parameter using limited geophysical field data with noise. Geophysical datasets are measured with sparse sampling in a survey. However, the limited data constrain the geophysical interpretation. Traditionally, the field data has been interpolated using mathematical algorithm. In many cases, the estimated field data uncertainties are required to determine which earth models are consistent with the observations. A model-based data-estimation method can provide precise information for imaging and interpretation. The approach used in this paper is based on a stochastic partial differential equation, and it is employed to predict the geophysical data. With this statistical model-based approach, the sparse sample from a survey is used to estimate the underlying spatial surface, and it is assumed that the predicted geophysical data have the same probability density function as the observed data. Furthermore, this method can return the uncertainties of the prediction. Both the synthetic data and the gold mineral exploration field data cases illustrate that this approach leads to better results than traditional methods.
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Alcolea Rodríguez, Andrés, Paul Marschall, Christophe Nussbaum, and Jens Karl Becker. "Automatic interpretation of geophysical well logs." Geological Society, London, Special Publications 482, no. 1 (2018): 25–38. http://dx.doi.org/10.1144/sp482.9.
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AbstractStratigraphic sequences in boreholes are commonly estimated by interpreting combinations of well logs. The interpretation is generally tedious and is made some time after log completion, which often leads to a loss of valuable first-hand information gathered on-site. This may lead to delayed or potentially poor on-site decisions. To make things worse, the standard interpretation of well logs is, at least to a certain degree, subjective and based on the manipulation of data, which may be difficult to trace in the long term. Small changes in lithology are often disregarded and alternating thin layers presenting different lithologies are often combined in one single (notably thicker) stratigraphic unit. Therefore an automatic parameter-based and thus traceable and objective quick look at the lithology immediately after log completion represents both a valuable tool to help with on-site decisions and a solid, mathematically based starting point for further physically based interpretations carried out by log analysts. We present a workflow for the interpretation of well logs defined as an optimization problem. The workflow is applied to the characterization of metre- to decametre-scale stratigraphic units along 13 boreholes in northern Switzerland (one-dimensional resolution) and to millimetre-scale features over a wall at the Mont Terri underground rock laboratory in Switzerland (two-dimensional resolution). The results show that: (1) the workflow accurately maps lithological changes; (2) the interaction with the analyst is minimized, which reduces the subjectivity of the interpretation; and (3) outputs are available for on-site decisions.
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Miller, H. G. "A geophysical interpretation of the onshore and offshore geology of the southern Avalon Terrane, Newfoundland." Canadian Journal of Earth Sciences 24, no. 1 (1987): 60–69. http://dx.doi.org/10.1139/e87-006.
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This paper presents new land and underwater gravity data for the southern portion of the Avalon Terrane of Newfoundland. These gravity data are combined with existing airborne and marine magnetic data to produce a detailed geophysical interpretation of the geology of the southern Avalon Peninsula and the adjacent portions of Placentia and St. Mary's bays.Qualitative interpretation of the geophysical data in conjunction with the known geology reveals that the major faults previously mapped only on land and inferred beneath St. Mary's Bay can be traced offshore geophysically. In addition, the previously unknown offshore limits of a small sedimentary basin in the southeast part of the area can be delineated.Quantitative modelling demonstrates that (1) Precambrian mafic to ultramafic rocks underlie the whole area, (2) thrust faulting in the St. Mary's Peninsula and elsewhere has led to the juxtaposition of Bull Arm volcanic rocks over Harbour Main volcanic rocks, and (3) the evolution of the area may be explained by a combination of earlier volcanic island and extensional models.The mapping has also revealed the presence of previously unknown northwest–southeast lineations in the geophysical patterns, which may be related to the late wrench faulting.
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Janakiraman, Kalyan Kumar, and Masao Konno. "Cross‐borehole geological interpretation model based on a fuzzy neural network and geotomography." GEOPHYSICS 67, no. 4 (2002): 1177–83. http://dx.doi.org/10.1190/1.1500379.
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This paper demonstrates a method of predicting subsurface geological characteristics in the region between boreholes using a fuzzy neural network (FNN), inverted geophysical data (geotomogram), and fuzzy geological knowledge. Traditionally, geological interpretations are often of inadequate reliability in cross‐borehole regions because of the scarcity of quantitative data. Hence, geological interpretation has been a subjective process. Although there is a paucity of data, a fair amount of information exists in the form of human perception, summarized as either “rough maps” or “vague descriptions.” Here, a method based on fuzzy set theory that can extract rough information from conventional geological interpretations is described. The extracted data can be used with geophysical tomography data in a FNN to improve geological interpretation. The proposed method was applied to the geological evaluation of a site where construction of an underground hydroelectric power‐generation facility was being considered. The site was roughly 500 m below the surface and is generally composed of Mesozoic sedimentary rock. The results indicate that a significantly superior geologic interpretation is obtained by incorporating rough information and by using the proposed FNN model.
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Uieda, Leonardo, Vanderlei C. Oliveira, and Valéria C. F. Barbosa. "Geophysical tutorial: Euler deconvolution of potential-field data." Leading Edge 33, no. 4 (2014): 448–50. http://dx.doi.org/10.1190/tle33040448.1.
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In this tutorial, we will talk about a widely used method of interpretation for potential-field data called Euler de-convolution. Our goal is to demonstrate its usefulness and, most important, to call attention to some pitfalls encountered in interpretation of the results. The code and synthetic data required to reproduce our results and figures can be found in the accompanying IPython notebooks ( ipython.org/notebook ) at dx.doi.org/10.6084/m9.figshare.923450 or github.com/pinga-lab/paper-tle-euler-tutorial . The note-books also expand the analysis presented here. We encourage you to download the data and try them on your software of choice. For this tutorial, we will use the implementation in the open-source Python package Fatiando a Terra ( fatiando.org ).
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Sholpanbaev, B. B., Zh O. Oralbekova, l. Karchevsky, and N. T. Aziyeva. "Interpretation of georadar data to search for hidden isolated objects." Bulletin of the National Engineering Academy of the Republic of Kazakhstan 90, no. 4 (2023): 148–55. http://dx.doi.org/10.47533/2023.1606-146x.42.
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This article considered the possibilities of using a radar device in archeology. A geophysical method has been chosen that makes it possible to find underground archaeological sites without excavations. GPR signals are recorded as a radargram. Interpretation of radargrams makes it possible to make a predictive image of underground objects. However, the interpretation of radargrams is of a commercial nature. Therefore, the task of developing its own methods for interpreting radargrams is relevant. With the help of a geophysical GPR instrument, mounds, located far from settlements in the Kyzylorda region, were investigated. Three objects were chosen for the study: two barrows and a strip of land between the barrows. The latter has been investigated to determine if there is a connection between the two burial mounds. A marking scheme for the study area has been created. The problem under study requires the use of a non-destructive method. In order to significantly save time and money compared to existing methods of visual inspection of these objects with subsequent archaeological excavations, experimental studies were carried out with a step of 0.2 m using a geophysical instrument with 0.15 m antennas. Continuous areal surveys of three squares were made. Tests, monitoring, and scientific measurements were carried out. GPR data for predicting hidden isolated objects were processed using special built-in software. Recommendations to archaeologists are given.
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Шевченко, В. А., А. М. Красникова, И. Н. Модин, С. А. Ерохин, and А. Д. Скобелев. "GEOPHYSICAL STUDIES OF SELTSO KURGAN NECROPOLIS." ГЕОФИЗИКА, no. 6 (December 29, 2023): 58–64. http://dx.doi.org/10.34926/geo.2023.41.49.009.
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Геофизические методы изучения невыраженных на поверхности курганных некрополей Суздальского Ополья позволили впервые увидеть планографическую структуру этих памятников. Настоящая работа посвящена результатам исследований некрополя Сельцо-8 от обнаружения до определения его структуры и создания 3D-реконструкции. Построенная геофизическая интерпретация данных съемки некрополя Сельцо-8 может быть использована для планирования археологических раскопок и археологической интерпретации в комплексе с результатами раскопок. Сельцо-8 – третий некрополь в ряду покрытых геофизической съемкой, что дало возможность провести сравнительную интерпретацию геофизических данных. Структура некрополей различается, изучение выявленных закономерностей обладает потенциалом для повышения информативности геофизической и археологической интерпретации. Using geophysical methods, we’ve been able to uncover the structure of burial mounds in the Suzdal Opolye region that aren’t visible on the surface. This study focuses on the Sel’tso-8 necropolis, tracing its discovery, understanding its structure, and culminating in a 3D reconstruction. The geophysical data interpretation from the Sel’tso-8 site can guide future archaeological excavations and provide context when combined with excavation findings. Sel’tso-8 is the third necropolis we’ve examined using geophysical surveys, allowing us to compare and interpret data across sites. While each necropolis has its unique structure, identifying common patterns can enhance our understanding and interpretation, both geophysically and archaeologically.
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Berezko, Аlexandr, Anatoly Soloviev, Roman Krasnoperov, and Alena Rybkina. "INTELLECTUAL ANALYTICAL GEOINFORMATION SYSTEM “EARTH SCIENCE DATA FOR THE TERRITORY OF RUSSIA”." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 1 (August 3, 2015): 215. http://dx.doi.org/10.17770/etr2009vol1.1122.
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The present study is aimed at the integration of data on geography, geology, geophysics, geoecology and other Earth sciences in the comprehensive problem-oriented geoinformation system (GIS) including the intellectual superstructure for geoinformation analysis. At the present time GIS provide only limited opportunities for general analysis of geodata handled. At the same time, among the scientific community, dealing with the Earth sciences data, the requirement of more profound and comprehensive data analyzing and processing is constantly growing. The theory and methods of artificial intellect (AI) must become not only an integral, but the main core of a modern GIS. The methods of fuzzy mathematics correlate with a fuzzy character of geophysical data. The AI methods, developed by the authors, and presently applied to volcanic activity monitoring, search and interpretation of anomalies in geophysical fields, solving environmental, geodynamic and other problems, turned out to be a success.
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Cooper, Gordon R. J. "A Semi-automatic Procedure for the Interpretation of Geophysical Data." Exploration Geophysics 35, no. 3 (2004): 182–87. http://dx.doi.org/10.1071/eg04182.
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Orlando, Luciana. "Joint Interpretation of Geophysical Data for Archaeology: A Case Study." Subsurface Sensing Technologies and Applications 6, no. 2 (2005): 235–50. http://dx.doi.org/10.1007/s11220-005-0010-3.
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Morozov, Igor, Glenn Chubak, and Shannon Blyth. "Interactive 3D/2D visualization for geophysical data processing and interpretation." Computers & Geosciences 35, no. 7 (2009): 1397–408. http://dx.doi.org/10.1016/j.cageo.2008.10.005.
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Obiora, Daniel N., Mirianrita N. Ossai, Francisca N. Okeke, and Andrew I. Oha. "Interpretation of airborne geophysical data of Nsukka area, southeastern Nigeria." Journal of the Geological Society of India 88, no. 5 (2016): 654–67. http://dx.doi.org/10.1007/s12594-016-0532-4.
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Kulikov, V. A., A. G. Yakovlev, and V. A. Polikarpova. "SOME PROBLEMS OF ELECTRICAL GEOPHYSICAL PROSPECTING METHODS USED FOR EXPLORATION OF ORE DEPOSITS." Geodynamics & Tectonophysics 12, no. 3S (2021): 731–47. http://dx.doi.org/10.5800/gt-2021-12-3s-0550.
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Electrical geophysical prospecting methods are widely used at different stages of geological exploration. In the last two decades, new computer technologies and satellite navigation systems were successfully introduced in the geophysical industry. As a result, exploration technologies have improved, and new geophysical methods have been developed, such as electrical resistivity tomography (ERT) and spectral induced polarization (SIP) methods. An important role in ore geophysics is played by magnetotelluric (MT) methods. In this article, we focus on the issues of methodology and interpretation of electrical prospecting data for solving ore exploration problems. Special attention is paid to the induced polarization (IP) method that is most widely used in mineral exploration and mining industry as one of the most important and most dynamically developing techniques of ore geophysics. In addition, the issues of correct choices of survey scales and the use of automatic 2D and 3D inversion programs are considered.
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Khasanov, I. M., A. V. Tkachev, A. V. Koshurnikov, and A. P. Ganov. "CHARACTERISTICS OF GEOPHYSICAL FIELDS OF THE PAVLIKOVSKOE GOLD ORE DEPOSIT (YANO-KOLYMA METALLOGENIC BELT)." Tikhookeanskaya Geologiya 41, no. 1 (2022): 110–20. http://dx.doi.org/10.30911/0207-4028-2022-41-1-110-120.
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The presented work provides the results of the analysis of the geophysical fields of the gold deposit, as well as some of their characteristic features. A set of geophysical studies and data processing techniques for solving the problems of gold mineralization forecast within the Yano-Kolyma metallogenic belt are presented. Based on the interpretation of the complex of geophysical data, geological and geophysical indications of gold mineralization are proposed in the following hierarchic sequence: ore cluster – ore field – mineralized zone – ore body. One of the main interpretation techniques in determining prospecting indicators of potential ore bodies (or high-grade intervals) is to study induced polarization frequency responses.
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Ghaib, Fadhil A., and Sirwa Q. Gardi. "Re-interpretation of Geophysical Data for the Archaeological Hill “Malta” at Duhok City – Iraqi Kurdistan Region." Journal of Zankoy Sulaimani - Part A 16, no. 4 (2014): 123–38. http://dx.doi.org/10.17656/jzs.10352.
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Sivarajah, Yathunanthan, Eun-Jung Holden, Roberto Togneri, and Michael Dentith. "Identifying effective interpretation methods for magnetic data by profiling and analyzing human data interactions." Interpretation 1, no. 1 (2013): T45—T55. http://dx.doi.org/10.1190/int-2013-0002.1.
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Geoscientific data interpretation is a highly subjective and complex task because human intuition and biases play a significant role. Based on these interpretations, however, the mining and petroleum industries make decisions with paramount financial and environmental implications. To improve the accuracy and efficacy of these interpretations, it is important to better understand the interpretation process and the impact of different interpretation techniques, including data processing and display methods. As a first step toward this goal, we aim to quantitatively analyze the variability in geophysical data interpretation between and within individuals. We carried out an experiment to analyze how individuals interact with magnetic data during the process of identifying prescribed targets. Participants performed two target spotting exercises where the same magnetic image was presented at different orientations. The task was to identify the magnetic response from porphyry-style intrusive systems. The experiment involved analyzing the data observation pattern during the interpretation process using an eye tracker system that captures the interpreter’s eye gaze motion and the target-spotting performance. The time at which targets were identified was also recorded. Fourteen participants with varying degrees of experience and expertise participated in this study. The results show inconsistencies within and between the interpreters in target-spotting performance. The results show a correlation between a systematic data observation pattern and target-spotting performance. Improved target-spotting performance was obtained when the magnetic image was observed from multiple orientations. These findings will help to identify and quantify the effective interpretation practices, which can provide a roadmap for the training of geoscientific data interpreters and contribute toward the understanding of the uncertainties in the data interpretation process.
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Abbassi, Bahman, Li-Zhen Cheng, Michel Jébrak, and Daniel Lemire. "3D Geophysical Predictive Modeling by Spectral Feature Subset Selection in Mineral Exploration." Minerals 12, no. 10 (2022): 1296. http://dx.doi.org/10.3390/min12101296.
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Several technical challenges are related to data collection, inverse modeling, model fusion, and integrated interpretations in the exploration of geophysics. A fundamental problem in integrated geophysical interpretation is the proper geological understanding of multiple inverted physical property images. Tackling this problem requires high-dimensional techniques for extracting geological information from modeled physical property images. In this study, we developed a 3D statistical tool to extract geological features from inverted physical property models based on a synergy between independent component analysis and continuous wavelet transform. An automated interpretation of multiple 3D geophysical images is also presented through a hybrid spectral feature subset selection (SFSS) algorithm based on a generalized supervised neural network algorithm to rebuild limited geological targets from 3D geophysical images. Our self-proposed algorithm is tested on an Au/Ag epithermal system in British Columbia (Canada), where layered volcano-sedimentary sequences, particularly felsic volcanic rocks, are associated with mineralization. Geophysical images of the epithermal system were obtained from 3D cooperative inversion of aeromagnetic, direct current resistivity, and induced polarization data sets. The recovered cooperative susceptibilities allowed locating a magnetite destructive zone associated with porphyritic intrusions and felsic volcanoes (Au host rocks). The practical implementation of the SFSS algorithm in the study area shows that the proposed spectral learning scheme can efficiently learn the lithotypes and Au grade patterns and makes predictions based on 3D physical property inputs. The SFSS also minimizes the number of extracted spectral features and tries to pick the best representative features for each target learning case. This approach allows interpreters to understand the relevant and irrelevant spectral features in addition to the 3D predictive models. Compared to conventional 3D interpolation methods, the 3D lithology and Au grade models recovered with SFSS add predictive value to the geological understanding of the deposit in places without access to prior geological and borehole information.
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Laizer, Peter, and Gabriel D. Mulibo. "Geophysical delineation of the geology and subsurface features of the Iramba area, central Tanzania, using aero-geophysical data with implications for mineral deposits." Tanzania Journal of Science 51, no. 1 (2025): 102–14. https://doi.org/10.4314/tjs.v51i1.8.
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The Iramba area, known for its gold, base metal, and metallic mineral deposits, is not geophysically well exploited. The research presents an in-depth geophysical interpretation of the geology and the subsurface geological features and delineates hydrothermal alteration zones related to mineralisation in the area. The study involved detailed analysis and interpretations of high-resolution aero–geophysical data. Results from radiometric data have identified new granitic rocks and revealed a unique prominent feature in the region, which was previously not mapped. The identified new xenolith and foliated granites are characterised by high concentrations of all radiometric elements. The revealed prominent ring-like, NE trending feature is characterised by a high K concentration with moderate to high Th concentration. The feature shows significantly lower values of the Th/U ratios at the centre than the surrounding with intermediate magnetic signatures at the centre surrounded by high magnetic signatures. The study has also delineated zones of high K that coincide with low Th and Th/K ratio, indicating hydrothermally altered rocks and mineralisation in the area. The practical implications of this study are the future exploration and development of mineral resources for small-scale miners or larger-scale industrial mining in areas where mineralisations have been proposed.
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Hasan, Mohammad Nurul, Md Noor Islam, and Salma Begum. "Geophysical interpretation of tectonic features in Bangladesh." Journal of Nepal Geological Society 18 (December 1, 1998): 135–41. http://dx.doi.org/10.3126/jngs.v18i0.32205.
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Bangladesh occupies the major part of the Bengal basin. It is mainly a plain fluvi-dieltaic land. Except the eastern and northeastern Tertiary hilly region, the whole country is covered with thick Quaternary sediments.
 Tectonic features in Bangladesh, except the eastern and northeastern hilly structures, are hidden under thick cover of sediments. Gravity anomalies dearly show the locations of major subsurface tectonic features of the country, namely a) Himalayan foredeep, b) Rangpur platform, c) Hinge zone, d) Surma basin and e) Bengal foredeep. Magnetic anomalies and the seismic sections also support the gravity results.
 Shape, extent and depth of the tectonic features in Bangladesh are interpreted from geophysical data, particularly from the gravity data supported by available geological and drilling information. Interpretation shows that the Rangpur platform, situated in the northwestern Bangladesh, is the shallowest subsurface tectonic feature in the country. The northern part of the Rangpur platform slopes down to the Himalayan foredeep and the southern part to the Hinge zone. The Surma Basin, containing very thick sediments, lies in north-east corner of the country; and the Bengal foredeep, the most extended tectonic feature, occupies the southern deltaic part of the country. The Fold Belt, the only exposed tectonic feature, lies in the eastern and northeastern hilly region of the country.
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Starodub, Y. P., V. V. Karabyn, A. P. Havrys, V. M. Kovalchuk, A. O. Rogulia, and S. O. Yemelyanenko. "Geophysical research in the pre-Carpathian hydrosphere situation for the environmental civil protection purposes." Geofizicheskiy Zhurnal 44, no. 4 (2022): 171–82. http://dx.doi.org/10.24028/gj.v44i4.264847.
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Object of research is to develop and carry out a methodology investigation of the regional ecological changes in the Pre-Carpathian hydro-lithosphere in a state of emergency caused by flooding. Method involves obtaining the results by integrating experimental field-path studies and theoretical model research, laboratory scientific comparison, the analysis and synthesis of final results. The studied model is the flooding in the Carpathian region east of the Carpathian arc in Ukraine, flooding parts of Pre-Carpathians Lviv region — industrially and recreationally important regions: Stebnyk, Borislav and Drohobych cities. Scientific novelty: the article aims to develop a method for an integrated approach to study of the territory in the question of flooding through a combined interpretation of geophysical, geological, and chemical data when considering a strategically important Pre-Carpathian region. The theoretical and practical significance of the results obtained is substantiating the feasibility and possibility of the complex application of geophysical-geological and chemical data for the practical interpretation of geoinformation data. Results will be of use to applied research in geophysics and ecology and contribute to improving of the ecological situation in selected regions. Obtained results contribute to the development of geoinformation technologies for complex geophysical-geological and chemical research in the environmental safety of territories in the event of emergencies.
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Nobes, David C. "Interpretation pitfalls to avoid in void interpretation from ground-penetrating radar imaging." Interpretation 6, no. 4 (2018): SL21—SL28. http://dx.doi.org/10.1190/int-2018-0049.1.
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Voids are features that occur commonly in near-surface geophysical imaging. They are usually readily identified in ground penetrating radar (GPR) imaging because of the strong reflection amplitudes, akin to the “bright spot” in oil and gas exploration. However, voids are often misidentified. Some voids are missed, and other anomalous features are misinterpreted as voids, when in fact they are not. We evaluate s ome examples of features will be presented from glacial imaging and engineering geophysics that were misinterpreted as voids, compare them with real voids, and we determine the differences that separate them. Another example from archaeology was identified as a void based on incomplete data, and was only coincidentally coincident with a void. In particular, in addition to strong top and bottom reflections, voids may have multiple reflections but will not have internal reflections. Voids will also tend to be limited in extent, and won’t, in general, underlie an entire GPR profile.
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Olaniyan, Oladele, Richard S. Smith, and Bill Morris. "Qualitative geophysical interpretation of the Sudbury Structure." Interpretation 1, no. 1 (2013): T25—T43. http://dx.doi.org/10.1190/int-2012-0010.1.
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The Sudbury Structure is one of the most studied geologic structures in the world due to its enigmatic nature and mineral wealth. The available geologic work from the literature and mining industry operations accumulated for more than a century was recently assessed and compiled into a bedrock geologic map. Most regional geophysical investigations of the Sudbury Structure have been quantitative — modeling and depth estimation without a clear definition of surface control. Airborne total magnetic intensity data over the Sudbury Structure were compiled, processed, and interpreted, to define magnetic stratigraphy boundaries and near-surface lineaments. Traditional directional and normalized derivatives were computed to enhance the high-frequency information in the magnetic field. Available airborne frequency-domain electromagnetic (EM) data were also interactively interpreted along profiles and in a gridded format to isolate conductive structures. On-screen geographic information system-based information extraction from multiple derivatives was used to interpret the magnetic contacts, dykes, and lineaments. The magnetic interpretation was compared with published bedrock maps of the Sudbury Structure. Magnetic contacts based on the qualitative classification of the magnetic texture did not always correspond to the geologic boundaries on the existing maps. Some magnetic lineaments corresponded with well-defined geologic structures, some were further extensions of partially mapped structures, and others are newly identified linear structures. Conductive locations identified from the EM profiles were probably due to responses from conductive ore bodies, faults, dykes, lithological contacts, and cultural objects.
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Zagranovskaya, D. E., S. I. Isaeva, and O. A. Zakharova. "Fundamentals of well logging data interpretation for determining prospective Frasnian-Famennian Domanik deposits." Proceedings of higher educational establishments. Geology and Exploration 63, no. 2 (2020): 61–72. http://dx.doi.org/10.32454/0016-7762-2020-63-2-61-72.
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Background. In the process of studying productive Domanik deposits of the Frasnian-Famennian, numerous uncertainties arise in identifying their effective thickness. Although several approaches have been recently proposed for identifying promising intervals in Domanik sediments, e.g. determination of the effective thickness using gas logging during geological and technical studies, the use of the interpretation method presented in the article and other methods continue to develop. Therefore, studies aimed at increasing their efficiency remain to be relevant.Aim. To develop basic methodological approaches to interpretation of well logging data with the purpose of identifying promising Domanik deposits rich in mobile hydrocarbons.Materials and methods. Geological and geophysical data obtained when investigating the wells of the according to published data of geological and geophysical resources of drilled wells in the Buzuluk depression were used to build the main well logging dependencies. In addition, the materials of core and geophysical studies of wells in the Volga-Ural oil and gas basin conducted by Gazprom Neft (PJSC) were used. Extended well logging data were collected for the wells under consideration. A number of tests and core studies, including geochemical experiments, which were carried out in deposits of Fran age, the density of resources of 5—10 samples per 1 meter of core.Results. For the first time, basic methodological approaches for identifying effective oil-saturated strata in Domanik sediments according to well logging data were developed. The developed approaches are based on the integration of geological-geophysical and geochemical data characterizing the material and mineralogical composition of rocks, the content of organic matter, the group composition of hydrocarbons and the genesis of reservoirs. In the section under study, rocks saturated with hydrocarbons were identified. The hydrocarbons were different in terms of group composition, which determined their mobility. Boundary values were obtained when interpreting data obtained by well logging methods for Domanik rocks containing mobile and stationary hydrocarbons. The proposed methodological approaches were tested on other wells in the Domanik deposits in the Orenburg region. As a result of repeated practical application and testing of the developed methodology, its effectiveness was confirmed.Conclusions. The proposed basic methodological approaches for interpretation of well logging data when identifying effective oil-saturated strata were substantiated by the geological-geophysical and geochemical properties of Domanik deposits.
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Chen, Qiang, Sheng Zhang, Suoliang Chang, Bo Liu, Jun Liu, and Jianhui Long. "Geophysical Interpretation of a Subsurface Landslide in the Southern Qinshui Basin." Journal of Environmental and Engineering Geophysics 24, no. 3 (2019): 433–49. http://dx.doi.org/10.2113/jeeg24.3.433.
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A subsurface landslide is the key problem to a large affordable home program in the southern Qinshui Basin, China. A geophysical survey integrated with seismic refraction tomography (SRT), seismic scattered wave imaging (SSI), and electrical resistivity tomography (ERT) was performed along five profiles over the landslide body. The bedrock surface was a crucial interface, represented by a relatively high velocity, high density, and high resistivity in contrast to the unconsolidated soil and landslide material above it. Based on the most comparable geophysical features, several problems were uncovered such as a “sandwich velocity structure” in the SRT results, velocity trap in the SSI results, and rapid variations in the local topography in all three methods. Aiming to improve the comprehensive interpretation of the ERT, SRT, SSI data, the vertical gradient extremum in the ERT and SRT data and tracing the target wave group according to the velocity sensitivity in the SSI data were analyzed. Moreover, a joint interpretation of the three geophysical survey datasets as well as 32 geological wells and 73 geotechnical boreholes helped to determine one undulating bedrock surface, delineate two types of failure surface geometry (landslide surface and collapse surface), and identify three external shapes in the ex situ body (ancient river channel, landslide body and collapse body). The results showed that the integrated geophysical survey not only provided detailed evidence for the existing of landslide but also presented meaningful evidence for the sliding mechanism. These results were difficult to fully describe and to apply to understanding landslide processes. Furthermore, for near-surface landslide events, the joint interpretation of geologic, geotechnical and geophysical data was necessary to reduce problems with any single geophysical survey.
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Kettle, Robert W. "Fifty years of case histories." GEOPHYSICS 50, no. 12 (1985): 2431–42. http://dx.doi.org/10.1190/1.1441874.
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Fifty years of case histories naturally reflect different and ever‐changing technology, but the underlying theme remains unchanged: to show that careful surface measurements can reveal physical properties of the subsurface. Finding a salt dome with a torsion balance in the 1920s and defining reservoir properties with shear waves in the 1980s involve different techniques, but in both the physical properties of the rocks are interpreted from geophysical measurements to solve geologic problems. Most early case histories attempted to establish the validity of geophysical tools; an example would be attempting to show the usefulness of refraction fan shooting by comparing its results with drill hole information. Later tools would in turn be compared with established tools. Reflection seismic interpretations were compared with torsion balance and refraction fan shooting results. As the science of geophysics became more accepted, case histories focused on more detailed aspects of technology and on discovery of subtle traps. Early papers dwelt at length on the application of geophysics to large features and on comparison of results with drill information. Later case histories continued to use geologic information to test geophysical interpretation, but they emphasized the subtle and hidden aspects rather than the obvious. The most recent case histories seldom deal with large structures. Instead they demonstrate the source wavelet required to resolve a stratigraphic trap or the effect that changing the reservoir fluid has on the reflection character so that hydrocarbons can be identified, or inferred, directly from the seismic data. Geophysical exploration has evolved and case histories reflect that evolution.
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Gulbrandsen, Mats Lundh, Lyndsay B. Ball, Burke J. Minsley, and Thomas Mejer Hansen. "Automatic mapping of the base of aquifer — A case study from Morrill, Nebraska." Interpretation 5, no. 2 (2017): T231—T241. http://dx.doi.org/10.1190/int-2016-0195.1.
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When a geologist sets up a geologic model, various types of disparate information may be available, such as exposures, boreholes, and (or) geophysical data. In recent years, the amount of geophysical data available has been increasing, a trend that is only expected to continue. It is nontrivial (and often, in practice, impossible) for the geologist to take all the details of the geophysical data into account when setting up a geologic model. We have developed an approach that allows for the objective quantification of information from geophysical data and borehole observations in a way that is easy to integrate in the geologic modeling process. This will allow the geologist to make a geologic interpretation that is consistent with the geophysical information at hand. We have determined that automated interpretation of geologic layer boundaries using information from boreholes and geophysical data alone can provide a good geologic layer model, even before manual interpretation has begun. The workflow is implemented on a set of boreholes and airborne electromagnetic (AEM) data from Morrill, Nebraska. From the borehole logs, information about the depth to the base of aquifer (BOA) is extracted and used together with the AEM data to map a surface that represents this geologic contact. Finally, a comparison between our automated approach and a previous manual mapping of the BOA in the region validates the quality of the proposed method and suggests that this workflow will allow a much faster and objective geologic modeling process that is consistent with the available data.
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Klose, Christian D. "Self-organizing maps for geoscientific data analysis: geological interpretation of multidimensional geophysical data." Computational Geosciences 10, no. 3 (2006): 265–77. http://dx.doi.org/10.1007/s10596-006-9022-x.
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Meleshkina, Diana. "Optimization of linear structure extraction process from magnetic field data using geological modeling." E3S Web of Conferences 402 (2023): 12004. http://dx.doi.org/10.1051/e3sconf/202340212004.
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This article discusses optimizing the process of extracting linear structure from magnetic field data through the modeling of geological bodies. Lineament analysis is an important tool for geophysical fields interpretation, but the results can be ambiguous and dependent on many factors, including the geological features of the area, analysis method and interpreter’s opinion. The article reviews the methods of lineament analysis and types of linear structure extraction, as well as conducting modeling of geological objects such as quartz veins and dikes. The results highlight the influence of geological objects on line structures of geophysical data and help choose the best way to interpret geophysical fields.
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Orfanos, C., and G. Apostolopoulos. "Multiparameter analysis of geophysical methods for target detection: The unified geophysical model approach." GEOPHYSICS 78, no. 6 (2013): IM1—IM13. http://dx.doi.org/10.1190/geo2012-0285.1.
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Void detection is a difficult task for geophysical methods. The main disadvantage is the uncertainty of the final interpretation and the need for verification of the results with direct methods of underground investigation. A good way to reduce this uncertainty, apart from drilling, is through the implementation of more than one geophysical method in the same area. An integrated approach of geophysical methods can be achieved by using multiparameter statistical techniques, such as cluster analysis. Firstly, the effectiveness of multiparameter analysis on synthetic data is studied and then on real data from a controlled test site. In addition, a new approach for the creation of a unified geophysical model (UGM) is suggested to optimize target detection. Finally, the UGM approach is implemented and is evaluated in a real case study for void detection in an urban environment. The UGM offers the integrated information of the geophysical methods that are used without the need for predefined relationships. It is a model resulting from a specific statistical procedure, free of subjective precautions, and easily understood even by nonexperts in geophysics. Finally, it offers an additional tool for the better understanding of the subsurface as far as the difficult task of void detection is concerned.
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Suprayogi, Slamet, Wikan Jaya Prihantarto, Totok Gunawan, Sigit Heru Murti, and Masrur Alatas. "Grand Design Plan For Irrigation Channel System Using Watershed And River Basin Approaches Based On Community Development In Yogyakarta, Indonesia." ASEAN Journal on Science and Technology for Development 39, no. 1 (2022): 1–6. http://dx.doi.org/10.29037/ajstd.740.
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This paper proposes a grand design plan for Mataram Channel II, an irrigation channel system spanning from Turi to Cangkringan District in Yogyakarta, Indonesia. It is based on research aiming to assess the system’s feasibility from two aspects: geophysics using site selection approaches (watershed and river region) and community aspirations, analyze potential water resource availability to support its sustainability, and construct a grand design plan. Primary data acquired from IKONOS image interpretation were used to collect geophysical and field data for parameter mapping, and spatial data were modeled using Geographic Information System technology to determine paths, directions, and routes. Community aspirations were obtained by structured interviews with key informants and focus group discussions with community groups in village units. The results showed that, geophysically, the land carrying capacity allowed Krasak-Bedog rivers as permanent discharge of 123.78 m3/s of water, in line with community aspirations for higher irrigation water discharge in traversed districts. In total, 19 rivers and nine artificial retention in the channel system produced maximum discharges of 123.78 m3/s and 12 m3/s. Based on geophysical characteristics and community aspirations, the grand design plan included constructing 41km-long Mataram Channel II from Turi (specifically Wonokerto Village) at 500 msal to Cangkringan (Glagaharjo) at 450 masl.