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1
Yogi, Ade. "Petrophysics Analysis for Reservoir Characterization of Cretaceous Clastic Rocks: A Case Study of the Arafura Basin." Jurnal Geologi dan Sumberdaya Mineral 21, no. 3 (August 28, 2020): 129. http://dx.doi.org/10.33332/jgsm.geologi.v21i3.527.
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This study presents petrophysics analysis results from two wells located in the Arafura Basin. The analysis carried out to evaluate the reservoir characterization and its relationship to the stratigraphic sequence based on log data from the Koba-1 and Barakan-1 Wells. The stratigraphy correlation section of two wells depicts that in the Cretaceous series a transgression-regression cycle. The petrophysical parameters to be calculated are the shale volume and porosity. The analysis shows that there is a relationship between stratigraphic sequences and petrophysical properties. In the study area, shale volumes used to make complete rock profiles in wells assisted by biostratigraphic data, cutting descriptions, and core descriptions. At the same time, porosity shows a conformity pattern with the transgression-regression cycle.Keywords: petrophysics, reservoir characterization, Cretaceous, transgressive-regressive cycle
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Grana, Dario, and Ernesto Della Rossa. "Probabilistic petrophysical-properties estimation integrating statistical rock physics with seismic inversion." GEOPHYSICS 75, no. 3 (May 2010): O21—O37. http://dx.doi.org/10.1190/1.3386676.
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A joint estimation of petrophysical properties is proposed that combines statistical rock physics and Bayesian seismic inversion. Because elastic attributes are correlated with petrophysical variables (effective porosity, clay content, and water saturation) and this physical link is associated with uncertainties, the petrophysical-properties estimation from seismic data can be seen as a Bayesian inversion problem. The purpose of this work was to develop a strategy for estimating the probability distributions of petrophysical parameters and litho-fluid classes from seismics. Estimation of reservoir properties and the associated uncertainty was performed in three steps: linearized seismic inversion to estimate the probabilities of elastic parameters, probabilistic upscaling to include the scale-changes effect, and petrophysical inversion to estimate the probabilities of petrophysical variables andlitho-fluid classes. Rock-physics equations provide the linkbetween reservoir properties and velocities, and linearized seismic modeling connects velocities and density to seismic amplitude. A full Bayesian approach was adopted to propagate uncertainty from seismics to petrophysics in an integrated framework that takes into account different sources of uncertainty: heterogeneity of the real data, approximation of physical models, measurement errors, and scale changes. The method has been tested, as a feasibility step, on real well data and synthetic seismic data to show reliable propagation of the uncertainty through the three different steps and to compare two statistical approaches: parametric and nonparametric. Application to a real reservoir study (including data from two wells and partially stacked seismic volumes) has provided as a main result the probability densities of petrophysical properties and litho-fluid classes. It demonstrated the applicability of the proposed inversion method.
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Bosch, Miguel, Carla Carvajal, Juan Rodrigues, Astrid Torres, Milagrosa Aldana, and Jesús Sierra. "Petrophysical seismic inversion conditioned to well-log data: Methods and application to a gas reservoir." GEOPHYSICS 74, no. 2 (March 2009): O1—O15. http://dx.doi.org/10.1190/1.3043796.
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Hydrocarbon reservoirs are characterized by seismic, well-log, and petrophysical information, which is dissimilar in spatial distribution, scale, and relationship to reservoir properties. We combine this diverse information in a unified inverse-problem formulation using a multiproperty, multiscale model, linking properties statistically by petrophysical relationships and conditioning them to well-log data. Two approaches help us: (1) Markov-chain Monte Carlo sampling, which generates many reservoir realizations for estimating medium properties and posterior marginal probabilities, and (2) optimization with a least-squares iterative technique to obtain the most probable model configuration. Our petrophysical model, applied to near-vertical-anglestackedseismic data and well-log data from a gas reservoir, includes a deterministic component, based on a combination of Wyllie and Wood relationships calibrated with the well-log data, and a random component, based on the statistical characterization of the deviations of well-log data from the petrophysical transform. At the petrophysical level, the effects of porosity and saturation on acoustic impedance are coupled; conditioning the inversion to well-log data helps resolve this ambiguity. The combination of well logs, petrophysics, and seismic inversion builds on the corresponding strengths of each type of information, jointly improving (1) cross resolution of reservoir properties, (2) vertical resolution of property fields, (3) compliance to the smooth trend of property fields, and (4) agreement with well-log data at well positions.
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Al-Mamouri, Abdullah, Amer Al-Khafaji, and Ali Al-Musawi. "The Asmari Formation Petrophysical Parameters in the Abu Ghirab Oil Field of the Zagros Fold Belt Basin, Southeastern Iraq, Using Well Log Data Interpretation." Iraqi Geological Journal 55, no. 2E (November 30, 2022): 128–39. http://dx.doi.org/10.46717/igj.55.2e.8ms-2022-11-22.
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The current study represents the evaluation of petrophysical characteristics, lithological analysis, and identification of the Asmari Formation for the main and sub-reservoir units in the Abu Ghirab oil field, Maysan, southeast of Iraq. This petrophysical assessment was accomplished using the interpretations of well log data to know the properties of the Asmari Formation reservoir. The available logs such as resistivity, gamma ray, neutron and density logs were converted to digital data using the Diger Sotware. The lithic properties of the reservoir like porosity, total shale saturation, oil and water saturation were interpreted and calculated using the interactive petrophysics software. The lithic and mineral study was completed and the type of mineral filling was known through the cross-plot of the porosity logs for different wells. The petrophysical properties were calculated and represented on the CPI profile. Depending on the petrophysical characteristics, the Asmari Formation was divided into main and sub units, which are: Jeribe-Euphrates and its sub-units A1, A2, and A3; Upper Kirkuk unit and B1, B2, B3, B4 sub-units; and Middle-Lower Kirkuk unit and C subunit. The results showed that the reservoir has economic oil productivity. The subunits B2, B3 in Upper Kirkuk were characterized by high effective porosity values and high hydrocarbon content, and they are the highest produced units in Upper Kirkuk in studied wells. The vary on lithology represents as dolomites in the Jeribe, Euphrates, limestones in the Kirkuk group, and the mineral components were calcite and dolomite.
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Astic, Thibaut, Lindsey J. Heagy, and Douglas W. Oldenburg. "Petrophysically and geologically guided multi-physics inversion using a dynamic Gaussian mixture model." Geophysical Journal International 224, no. 1 (August 21, 2020): 40–68. http://dx.doi.org/10.1093/gji/ggaa378.
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SUMMARY In a previous paper, we introduced a framework for carrying out petrophysically and geologically guided geophysical inversions. In that framework, petrophysical and geological information is modelled with a Gaussian mixture model (GMM). In the inversion, the GMM serves as a prior for the geophysical model. The formulation and applications were confined to problems in which a single physical property model was sought, and a single geophysical data set was available. In this paper, we extend that framework to jointly invert multiple geophysical data sets that depend on multiple physical properties. The petrophysical and geological information is used to couple geophysical surveys that, otherwise, rely on independent physics. This requires advancements in two areas. First, an extension from a univariate to a multivariate analysis of the petrophysical data, and their inclusion within the inverse problem, is necessary. Secondly, we address the practical issues of simultaneously inverting data from multiple surveys and finding a solution that acceptably reproduces each one, along with the petrophysical and geological information. To illustrate the efficacy of our approach and the advantages of carrying out multi-physics inversions coupled with petrophysical and geological information, we invert synthetic gravity and magnetic data associated with a kimberlite deposit. The kimberlite pipe contains two distinct facies embedded in a host rock. Inverting the data sets individually, even with petrophysical information, leads to a binary geological model: background or undetermined kimberlite. A multi-physics inversion, with petrophysical information, differentiates between the two main kimberlite facies of the pipe. Through this example, we also highlight the capabilities of our framework to work with interpretive geological assumptions when minimal quantitative information is available. In those cases, the dynamic updates of the GMM allow us to perform multi-physics inversions by learning a petrophysical model.
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Ahmed, Rayan. "Geological Model for Mauddud Reservoir Khabaz Oil Field." Iraqi Geological Journal 54, no. 1D (April 30, 2021): 29–42. http://dx.doi.org/10.46717/igj.54.1d.3ms-2021-04-23.
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The Mauddud reservoir, Khabaz oil field which is considered one of the main carbonate reservoirs in the north of Iraq. Recognizing carbonate reservoirs represents challenges to engineers because reservoirs almost tend to be tight and overall heterogeneous. The current study concerns with geological modeling of the reservoir is an oil-bearing with the original gas cap. The geological model is establishing for the reservoir by identifying the facies and evaluating the petrophysical properties of this complex reservoir, and calculate the amount of hydrocarbon. When completed the processing of data by IP interactive petrophysics software, and the permeability of a reservoir was calculated using the concept of hydraulic units then, there are three basic steps to construct the geological model, starts with creating a structural, facies and property models. The reservoirs were divided into four zones depending on the variation of petrophysical properties (porosity and permeability). Nine wells that penetrate the Cretaceous Formation (Mauddud reservoir) are included to construct the geological model. Zone number three characterized as the most important due to it Is large thickness which is about 108 m and good petrophysical properties are about 13%, 55 md, 41% and 38% for porosity, permeability, water saturation and net to gross respectively. The initial oil and gas in place are evaluated to be about 981×106 STB and 400×109 SCF.
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Hassane, Amadou, Chukwuemeka Ngozi Ehirim, and Tamunonengiyeofori Dagogo. "Rock physics diagnostic of Eocene Sokor-1 reservoir in Termit subbasin, Niger." Journal of Petroleum Exploration and Production Technology 11, no. 9 (August 20, 2021): 3361–71. http://dx.doi.org/10.1007/s13202-021-01259-2.
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AbstractEocene Sokor-1 reservoir is intrinsically heterogeneous and characterized by low-contrast low-resistivity log responses in parts of the Termit subbasin. Discriminating lithology and fluid properties using petrophysics alone is complicated and undermines reservoir characterization. Petrophysics and rock physics were integrated through rock physics diagnostics (RPDs) modeling for detailed description of the reservoir microstructure and quality in the subbasin. Petrophysical evaluation shows that Sokor-1 sand_5 interval has good petrophysical properties across wells and prolific in hydrocarbons. RPD analysis revealed that this sand interval could be best described by the constant cement sand model in wells_2, _3, _5 and _9 and friable sand model in well_4. The matrix structure varied mostly from clean and well-sorted unconsolidated sands as well as consolidated and cemented sandstones to deteriorating and poorly sorted shaly sands and shales/mudstones. The rock physics template built based on the constant cement sand model for representative well_2 diagnosed hydrocarbon bearing sands with low Vp/Vs and medium-to-high impedance signatures. Brine shaly sands and shales/mudstones were diagnosed with moderate Vp/Vs and medium-to-high impedance and high Vp/Vs and medium impedance, respectively. These results reveal that hydrocarbon sands and brine shaly sands cannot be distinctively discriminated by the impedance property, since they exhibit similar impedance characteristics. However, hydrocarbon sands, brine shaly sands and shales/mudstones were completely discriminated by characteristic Vp/Vs property. These results demonstrate the robust application of rock physics diagnostic modeling in quantitative reservoir characterization and may be quite useful in undrilled locations in the subbasin and fields with similar geologic settings.
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Il’chenko, Vadim L., and Maria A. Gannibal. "Elastic Anisotropy and Internal Structure of Rocks from the Uranium Ore Occurrences of the Litsa Ore Area (Kola Region, Russia)." Geosciences 9, no. 7 (June 28, 2019): 284. http://dx.doi.org/10.3390/geosciences9070284.
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A relation of uranium mineralization to structural, textural and physical properties of rocks was investigated using two uranium ore occurrences (Beregovoe and Dikoe) in the Litsa ore area (Kola region, Russia) as an example. Study of the rock samples collected on the surface was carried out using X-ray computer tomography (CT), petrography and petrophysics. Petrophysical properties (density and elastic anisotropy index) as well as petrographic characteristics of 25 rock samples were studied; six samples from this collection were studied by CT method. The samples from the Beregovoe site display general positive correlation between magnitude of the elastic anisotropy index and uranium concentration. The samples from the Dikoe ore occurrence, however, do not follow this trend. Comparison of CT data with that obtained from petrophysical measurements shows that the elastic anisotropy index can be low in highly deformed rock, if microfractures and micropores were sealed with secondary (including uranium) minerals; while the uneven distribution of the heavy mineral phases in weakly deformed rock can significantly increase its elastic anisotropy. The CT method combined with petrographic and petrophysical methods has proved to be useful for studying ore deposits. In particular, the CT method allows the influence of spatial variations of minerals of different specific weight on the elastic properties of rocks (elastic anisotropy) to be ascertained. The data obtained for the Litsa area suggest the course of further research involving the construction of geological structural models of the crust blocks with subsequent selection of areas with the most favorable conditions for the formation of uranium ore.
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Li, Kun, Xingyao Yin, Zhaoyun Zong, and Dario Grana. "Estimation of porosity, fluid bulk modulus, and stiff-pore volume fraction using a multitrace Bayesian amplitude-variation-with-offset petrophysics inversion in multiporosity reservoirs." GEOPHYSICS 87, no. 1 (November 18, 2021): M25—M41. http://dx.doi.org/10.1190/geo2021-0029.1.
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The estimation of petrophysical and fluid-filling properties of subsurface reservoirs from seismic data is a crucial component of reservoir characterization. Seismic amplitude-variation-with-offset (AVO) inversion driven by rock physics is an effective approach to characterize reservoir properties. In general, PP-wave reflection coefficients, elastic moduli, and petrophysical parameters are nonlinearly coupled, especially in multiple-type pore-space reservoirs, which makes seismic AVO petrophysics inversion ill-posed. We have developed a new approach that combines Biot-Gassmann’s poroelasticity theory with Russell’s linear AVO approximation, to estimate the reservoir properties including elastic moduli and petrophysical parameters based on multitrace probabilistic AVO inversion algorithm. We first derive a novel PP-wave reflection coefficient formulation in terms of porosity, stiff-pore volume fraction, rock-matrix shear modulus, and fluid bulk modulus to incorporate the effect of pore structures on elastic moduli by considering the soft and stiff pores with different aspect ratios in sandstone reservoirs. Through the analysis of the four types of PP-wave reflection coefficients, the approximation accuracy and inversion feasibility of the derived formulation are verified. Our stochastic inversion method aims to predict the posterior probability density function in a Bayesian setting according to a prior Laplace distribution with vertical correlation and prior Gaussian distribution with lateral correlation of model parameters. A Metropolis-Hastings stochastic sampling algorithm with multiple Markov chains is developed to simulate the posterior models of porosity, stiff-pore volume fraction, rock-matrix shear modulus, and fluid bulk modulus from seismic AVO gathers. The applicability and validity of our inversion method is illustrated with synthetic examples and a real data application.
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Astic, Thibaut, Dominique Fournier, and Douglas W. Oldenburg. "Joint inversion of potential-fields data over the DO-27 kimberlite pipe using a Gaussian mixture model prior." Interpretation 8, no. 4 (October 12, 2020): SS47—SS62. http://dx.doi.org/10.1190/int-2019-0283.1.
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We have carried out petrophysically and geologically guided inversions (PGIs) to jointly invert airborne and ground-based gravity data and airborne magnetic data to recover a quasi-geology model of the DO-27 kimberlite pipe in the Tli Kwi Cho (also referred to as TKC) cluster. DO-27 is composed of three main kimberlite rock types in contact with each other and embedded in a granitic host rock covered by a thin layer of glacial till. The pyroclastic kimberlite (PK), which is diamondiferous, and the volcanoclastic kimberlite (VK) have anomalously low density, due to their high porosity, and weak magnetic susceptibility. They are indistinguishable from each other based upon their potential-field responses. The hypabyssal kimberlite (HK), which is not diamondiferous, has been identified as highly magnetic and remanent. Quantitative petrophysical signatures for each rock unit are obtained from sample measurements, such as the increasing density of the PK/VK unit with depth and the remanent magnetization of the HK unit, and are represented as a Gaussian mixture model (GMM). This GMM guides the PGI toward generating a 3D quasi-geology model with physical properties that satisfies the geophysical data sets and the petrophysical signatures. Density and magnetization models recovered individually yield volumes that have physical property combinations that do not conform to any known petrophysical characteristics of the rocks in the area. A multiphysics PGI addresses this problem by using the GMM as a coupling term, but it puts a volume of the PK/VK unit at a location that is incompatible with geologic information from drillholes. To conform to that geologic knowledge, a fourth unit is introduced, PK-minor, which is petrophysically and geographically distinct from the main PK/VK unit. This inversion produces a quasi-geology model that presents good structural locations of the diamondiferous PK unit and can be used to provide a resource estimate or decide the locations of future drillholes.
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Kim, Guan Woo, Tae Hong Kim, Jiho Lee, and Kun Sang Lee. "Coupled Geomechanical-Flow Assessment of CO2 Leakage through Heterogeneous Caprock during CCS." Advances in Civil Engineering 2018 (2018): 1–13. http://dx.doi.org/10.1155/2018/1474320.
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The viability of carbon capture sequestration (CCS) is dependent on the secure storage of CO2 in subsurface geologic formations. Geomechanical failure of caprock is one of the main reasons of CO2 leakage from the storage formations. Through comprehensive assessment on the petrophysical and geomechanical heterogeneities of caprock, it is possible to predict the risk of unexpected caprock failure. To describe the fracture reactivation, the modified Barton–Bandis model is applied. In order to generate hydro-geomechanically heterogeneous fields, the negative correlation between porosity and Young’s modulus/Poisson’s ratio is applied. In comparison with the homogeneous model, effects of heterogeneity are examined in terms of vertical deformation and the amount of leaked CO2. To compare the effects of heterogeneity, heterogeneous models for both geomechanical and petrophysical properties in coupled simulation are designed. After 10-year injection with petrophysically heterogeneous and geomechanically homogeneous caprock, CO2 leakage is larger than that of the homogeneous model. In contrast, heterogeneity of geomechanical properties is shown to mitigate additional escape of CO2. Vertical displacement of every heterogeneous model is larger than homogeneous model. The model with compressive tectonic stress shows much more stable trapping with heterogeneous caprock, but there is possibility of rapid leakage after homogeneous caprock failure.
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Zeb, Jahan, Sanjeev Rajput, and Jimmy Ting. "Seismic petrophysics focused case study for AVA modelling and pre-stack seismic inversion." APPEA Journal 56, no. 1 (2016): 341. http://dx.doi.org/10.1071/aj15025.
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Hydrocarbon reservoirs are characterised by integrating seismic, well-log and petrophysical information, which are dissimilar in spatial distribution, scale and relationship to reservoir properties. Well logs are essential for amplitude versus offset (AVO) modelling and seismic inversion. The usability of well logs can be determined during wavelet estimation, seismic-to-well ties, background model building, property distribution for inversion, deriving probability density functions and variograms, offset-to-angle conversion of seismic data, and many other processes. For the implementation of seismic inversion workflows, accurate and geologically corrected compressional-sonic, shear-sonic and density logs are necessary. Preparing the logs for quantitative interpretation becomes challenging in a real-field environment because of bad borehole conditions including washouts, uncalibrated and variability of logging tools, invasion effects, missing shear logs and change of borehole size. Conventional petrophysical analysis is usually restricted to the reservoir interval, the calculation of reservoir versus non-reservoir (including sands or shales), and log corrections for smaller intervals; in contrast, seismic petrophysics encompasses the entire geological interval, calculates the volume of multi-minerals, incorporates boundaries between non-reservoir and reservoir, and often includes the prediction of missing compressional and shear-sonic for AVO analysis. A detailed seismic petrophysics analysis was performed for amplitude versus angle (AVA) modelling and attributes analysis. To perform the AVA modelling, a series of forward models in association with rock physics modelled fluid-substituted logs were developed, and associated seismic responses for various pore fluids and rock types studied. The results reveal that synthetic seismic responses together with the AVA analysis show changes for various lithologies. AVA attributes analysis show trends in generated synthetic seismic responses for various fluid-substituted and porosity logs. Reservoir modelling and fluid substitution increases understanding of the observed seismic response. This paper describes detailed data analysis using various techniques to confirm the rock model for petrophysical evaluation, rock physics modelling, AVA analysis, pre-stack seismic inversion, and the scenario modelling applied to the study of an oil field in Australia.
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Alkhayyat, Raniah S., Fadhil S. Kadhim, and Yousif khalaf Yousif. "The Use of Nuclear Magnetic Resonance (NMR) Measurements and Conventional Logs to Predict Permeability for a Complex Carbonate Formation." Journal of Petroleum Research and Studies 11, no. 3 (September 19, 2021): 82–98. http://dx.doi.org/10.52716/jprs.v11i3.534.
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Permeability is one of the most important property for reservoir characterization, and its prediction has been one of the fundamental challenges specially for a complex formation such as carbonate, due to this complexity, log analysis cannot be accurate enough if it’s not supported by core data, which is critically important for formation evaluation. In this paper, permeability is estimated by making both core and log analysis for five exploration wells of Yammama formation, Nasiriyah oil field. The available well logging recorders were interpreted using Interactive Petrophysics software (IP) which used to determine lithology, and the petrophysical properties. Nuclear Magnetic Resonance (NMR) Measurements is used for laboratory tests, which provide an accurate, porosity and permeability measurements. The results show that the main lithology in the reservoir is limestone, in which average permeability of the potential reservoir units’ values tend to range from 0.064275 in zone YA to 20.74 in zone YB3, and averaged porosity values tend to range from 0.059 in zone YA to 0.155 in zoneYB3. Zone YB3 is found to be the best zone in the Yammama formation according to its good petrophysical properties. The correlation of core-log for permeability and porosity produce an acceptable R^2 equal to 0.618, 0.585 respectively
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Wu, Wenting, and Dario Grana. "Integrated petrophysics and rock physics modeling for well log interpretation of elastic, electrical, and petrophysical properties." Journal of Applied Geophysics 146 (November 2017): 54–66. http://dx.doi.org/10.1016/j.jappgeo.2017.09.007.
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Li, Yongyi, Lev Vernik, Mark Chapman, and Joel Sarout. "Introduction to this special section: Rock physics." Leading Edge 38, no. 5 (May 2019): 332. http://dx.doi.org/10.1190/tle38050332.1.
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Rock physics links the physical properties of rocks to geophysical and petrophysical observations and, in the process, serves as a focal point in many exploration and reservoir characterization studies. Today, the field of rock physics and seismic petrophysics embraces new directions with diverse applications in estimating static and dynamic reservoir properties through time-variant mechanical, thermal, chemical, and geologic processes. Integration with new digital and computing technologies is gradually gaining traction. The use of rock physics in seismic imaging, prestack seismic analysis, seismic inversion, and geomechanical model building also contributes to the increase in rock-physics influence. This special section highlights current rock-physics research and practices in several key areas, namely experimental rock physics, rock-physics theory and model studies, and the use of rock physics in reservoir characterizations.
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Pape, Hansgeorg, Christoph Clauser, and Joachim Iffland. "Permeability prediction based on fractal pore‐space geometry." GEOPHYSICS 64, no. 5 (September 1999): 1447–60. http://dx.doi.org/10.1190/1.1444649.
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Estimating permeability from grain‐size distributions or from well logs is attractive but difficult. In this paper we present a new, generally applicable, and relatively inexpensive approach which yields permeability information on the scale of core samples and boreholes. The approach is theoretically based on a fractal model for the internal structure of a porous medium. It yields a general and petrophysically justified relation linking porosity to permeability, which may be calculated either from porosity or from the pore‐radius distribution. This general relation can be tuned to the entire spectrum of sandstones, ranging from clean to shaly. The resulting expressions for the different rock types are calibrated to a comprehensive data set of petrophysical and petrographical rock properties measured on 640 sandstone core samples of the Rotliegend Series (Lower Permian) in northeastern Germany. With few modifications, this new straightforward and petrophysically motivated approach can also be applied to metamorphic and igneous rocks. Permeability calculated with this procedure from industry porosity logs compares very well with permeability measured on sedimentary and metamorphic rock samples.
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Wang, Fred P., F. Jerry Lucia, and Charles Kerans. "Modeling dolomitized carbonate‐ramp reservoirs: A case study of the Seminole San Andres unit—Part I, Petrophysical and geologic characterizations." GEOPHYSICS 63, no. 6 (November 1998): 1866–75. http://dx.doi.org/10.1190/1.1444479.
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Major issues in characterizing carbonate‐ramp reservoirs include geologic framework, seismic stratigraphy, interwell heterogeneity including rock fabric facies and permeability structure, and factors affecting petrophysical properties and reservoir simulation. The Seminole San Andres unit, Gaines County, West Texas, and the San Andres outcrop of Permian age in the Guadalupe Mountains, New Mexico, were selected for an integrated reservoir characterization to address these issues. The paper is divided into two parts. Part I covers petrophysical and geologic characterization, and part II describes seismic modeling, reservoir geostatistics, stochastic modeling, and reservoir simulation. In dolomitic carbonates, two major pore types are interparticle (includes intergranular and intercrystalline) and vuggy. For nonvuggy carbonates the three important petrophysical/rock fabric classes are (I) grainstone, (II) grain‐dominated packstone and medium crystalline dolostone, and (III) mud‐dominated packstone, wackestone, mudstone, and fine crystalline dolostone. Core data from Seminole showed that rock fabric and pore type have strong positive correlations with absolute and relative permeabilities, residual oil saturation, waterflood recovery, acoustic velocity, and Archie cementation exponent. Petrophysical models were developed to estimate total porosity, separate‐vug porosity, permeability, and Archie cementation exponent from wireline logs to account for effects of rock fabric and separate‐vug porosity. The detailed and regional stratigraphic models were established from outcrop analogs and applied to seismic interpretation and wireline logs and cores. The aggradational seismic character of the San Andres Formation at Seminole is consistent with the cycle stacking pattern within the reservoir. In particular, the frequent preservation of cycle‐based mudstone units in the Seminole San Andres unit is taken to indicate high accommodation associated with greater subsidence rates in this region. A model for the style of high‐frequency cyclicity and the distribution of rock‐fabric facies within cycles was developed using continuous outcrop exposures at Lawyer Canyon. This outcrop model was applied during detailed core descriptions. These, together with detailed analysis of wireline log signatures, allowed construction of the reservoir framework based on genetically and petrophysically significant high‐frequency cycles. Petrophysical properties of total and separate‐vug porosities, permeability, water saturation, and rock fabrics were calculated from wireline log data. High‐frequency cycles and rock‐fabric units are the two critical scales for modeling carbonate‐ramp reservoirs. Descriptions of rock‐fabric facies stacked within high‐frequency cycles provide the most accurate framework for constructing geologic and reservoir models. This is because petrophysical properties can be better grouped by rock fabrics than depositional facies. The permeability‐thickness ratios among these rock fabric units can then be used to approximate fluid flow and recovery efficiency.
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Mosch, Stephan, and Siegfried Siegesmund. "Petrophysical and technical properties of dimensional stones: a statistical approach." Zeitschrift der Deutschen Gesellschaft für Geowissenschaften 158, no. 4 (December 1, 2007): 821–68. http://dx.doi.org/10.1127/1860-1804/2007/0158-0821.
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Arismendi Florez, Jhonatan Jair, Jean Vicente Ferrari, Mateus Michelon, and Carina Ulsen. "Construction of synthetic carbonate plugs: A review and some recent developments." Oil & Gas Science and Technology – Revue d’IFP Energies nouvelles 74 (2019): 29. http://dx.doi.org/10.2516/ogst/2019001.
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Plugs are cylindrical rocks with known dimensions that are extracted typically from reservoir formations with representative mineralogical compounds, petrophysical properties and oilfield fluids. They are used in the laboratory to understand the behaviour of oil in reservoirs. One of their applications is to study the screening of chemicals, such as surfactants and polymers, for enhanced oil recovery research before being applied in the reservoir. Many of Brazil’s pre-salt basins are located in ultra-deep waters, and the high heterogeneities of its offshore carbonate reservoirs make the extraction of representative rock samples difficult, risky and expensive. The literature reports the construction of synthetic plug samples that reproduce rocks as an alternative and viable solution for this issue. However, there is a lack of publications that focus on the construction of representative carbonate plugs that considers both the mineralogical composition and petrophysics properties, such as porosity and permeability. In this work, the construction of synthetic plugs is studied, using a combination of published methodologies to achieve an alternative construction of synthetic carbonate plugs for laboratory scale studies. Using a procedure based on the use of pulverized rock matrices with known particle sizes, uniaxial compaction, and probable CaCO3 solubility control by changing temperature and pH, it was possible to obtain synthetic carbonate plugs with a similar mineralogy to the natural carbonate reservoir. However, further studies are necessary to obtain more controlled petrophysical properties of such samples.
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Jabbar, Wria Jihad, Srood Farooq Naqshabandi, and Falah Khalaf Al-Juboury. "Petrophysical properties of the Lower Cretaceous formations in the Shaikhan oilfield, northern Iraq." Earth Sciences Research Journal 22, no. 1 (January 1, 2018): 45–52. http://dx.doi.org/10.15446/esrj.v22n1.66088.
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The current study represents an evaluation of the petrophysical properties in the well Shaikhan-8 for the Garagu, Sarmord and Qamchuqa formations in Shaikhan oilfield, Duhok basin, northern Iraq. The petrophysical evaluation is based on well logs data to delineate the reservoir characteristics. The environmental corrections and petrophysical parameters such as porosity, water saturation, and hydrocarbon saturation are computed and interpreted using Interactive Petrophysics (IP) program. Neutron-density crossplot is used to identify lithological properties. The Qamchuqa Formation in the Shaikhan oilfield consists mainly of dolomite with dolomitic limestone, and the average clay volume is about 13%; while Sarmord Formation composed of limestone and dolomitic limestone, the average clay volume in this formation is about 19%; also the Garagu Formation consists mainly of limestone and dolomitic limestone in addition to sandstone and claystone, the volume of clay in the Garagu Formation is about 20%. Pickett plot method is used to calculate formation water resistivity (Rw), saturation exponent (n) and cementation exponent (m) the values are 0.065ohm, 2, and 2.06 respectively. The porosity ratio (Ø) of the Qamchuqa Formation ranges between 7-15%; this indicates that the lower part of the formation has a poor-fair porosity (7%), while the upper part of the formation has a good porosity (15%). The porosity value decrease toward Sarmord Formation especially in the lower part of the formation, it has a poor porosity (5%), whereas this value reaches to 13% in the upper part of the formation, indicates for fair porosity. Garagu Formation has good porosity, reaches 20% in the lower part, but in the upper part of the formation, this value decreases to 3%. Water saturation (Sw) value which is calculated by Archie equation ranges between 14-33%, while saturation in the flushed zone (Sxo) ranges between 52-73%, these indicate for good movable hydrocarbons are present in the studied interval (840-1320m), and from the total 480m the Early Cretaceous formations in well Shaikhan-8 have 178m pay.
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Lis-Śledziona, Anita, and Weronika Kaczmarczyk-Kuszpit. "A Technique of Hydrocarbon Potential Evaluation in Low Resistivity Gas-Saturated Mudstone Horizons in Miocene Deposits, South Poland." Energies 15, no. 5 (March 4, 2022): 1890. http://dx.doi.org/10.3390/en15051890.
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The petrophysical properties of Miocene mudstones and gas bearing-heteroliths were the main scope of the work performed in one of the multihorizon gas fields in the Polish Carpathian Foredeep. Ten boreholes were the subject of petrophysical interpretation. The analyzed interval covered seven gas-bearing Miocene horizons belonging to Sarmatian and Badenian deposits. The water saturation in shaly sand and mudstone intervals was calculated using the Montaron connectivity theory approach and was compared with Simandoux water saturation. Additionally, the Kohonen neural network was used for qualitative interpretation of four PSUs (petrophysically similar units), which represent the deposits of comparable petrophysical parameters. This approach allowed us to identify the sediment group with the highest probability of hydrocarbon saturation. Then, the spatial distribution of PSUs and reservoir parameters was carried out in Petrel. The resolution of the model was selected to reflect the variability of log-derived parameters. The reconstruction of the spatial distribution of shale volume, porosity, and permeability was performed with standard parametric modeling procedures using the Gaussian random function simulation stochastic algorithm, while PSU distribution and hydrocarbon saturation (SH) required a separate approach. The distribution into PSU groups was carried out by facies classification. Predefined ranges of clay volume, effective porosity, and permeability were used as discriminators to achieve spatial distribution of the PSU groups. The spatial distribution of hydrocarbon saturation was performed by creating the meta-attribute of this parameter and then reducing the derived pseudo-saturation model to physical values. Results included the creation of maps of hydrocarbon saturation that show the preferable areas with the highest hydrocarbon saturation for each gas horizon.
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Ebong, Ebong D., Anthony E. Akpan, and Stephen E. Ekwok. "Stochastic modelling of spatial variability of petrophysical properties in parts of the Niger Delta Basin, southern Nigeria." Journal of Petroleum Exploration and Production Technology 10, no. 2 (October 15, 2019): 569–85. http://dx.doi.org/10.1007/s13202-019-00787-2.
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Abstract Three-dimensional models of petrophysical properties were constructed using stochastic methods to reduce ambiguities associated with estimates for which data is limited to well locations alone. The aim of this study is to define accurate and efficient petrophysical property models that best characterize reservoirs in the Niger Delta Basin at well locations and predicting their spatial continuities elsewhere within the field. Seismic data and well log data were employed in this study. Petrophysical properties estimated for both reservoirs range between 0.15 and 0.35 for porosity, 0.27 and 0.30 for water saturation, and 0.10 and 0.25 for shale volume. Variogram modelling and calculations were performed to guide the distribution of petrophysical properties outside wells, hence, extending their spatial variability in all directions. Transformation of pillar grids of reservoir properties using sequential Gaussian simulation with collocated cokriging algorithm yielded equiprobable petrophysical models. Uncertainties in petrophysical property predictions were performed and visualized based on three realizations generated for each property. The results obtained show reliable approximations of the geological continuity of petrophysical property estimates over the entire geospace.
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LYSAK, Yulia, Yuriy SHPOT, Andriy SHYRA, Zoriana KUCHER, and Ihor KUROVETS. "PETROPHYSICAL MODELS OF TERRIGENOUS RESERVOIRS OF THE CARBONIFEROUS DEPOSITS OF THE CENTRAL PART OF THE DNIEPER-DONETS DEPRESSION." Geology and Geochemistry of Combustible Minerals 1, no. 178 (August 27, 2019): 63–73. http://dx.doi.org/10.15407/ggcm2019.01.063.
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The purpose of the work was to construct petrophysical models of reservoir rocks of different rank: typical and unified. Typical models describe connections between the parameters of individual rocks lithotypes occurring in definite geological conditions and serving as the basis for the development of petrophysical classification of reservoir rocks in the oil geology. The principle of unification provides for creation of the models structure for different reservoir lithotypes both in the geological section and in the area. We have studied petrophysical properties of reservoir rocks of Carboniferous deposits in the central part of the Dnieper-Donets depression. Petrophysical properties of rocks in conditions close to the formational ones and relations between them were studied on a number of samples formed by the core samples of different age. Main geological factors that have an influence on reservoir properties of rocks were taken into consideration. While constructing and analysing of petrophysical models we have used a probable-statistic approach with the use of the correlative-regressive analysis. Result of the work is contained in typical petrophysical models for individual areas and in unified models obtained on consolidated samples for Lower Carboniferous deposits of this region. Characteristic features in variations of petrophysical properties of reservoir rocks of Carboniferous deposits and their models have been ascertained. A conclusion has been made that multidimensional models, in which the depth of occurrence of deposits is one of the parameters that are necessary to consider while constructing petrophysical models, are the most informative for determination of petrophysical properties of the studied deposits, and the models obtained by us are known to be a petrophysical basis for quantitative interpretation of data from geophysical studies in the boreholes of the given region.
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Kleinberg, Robert L. "NMR measurement of petrophysical properties." Concepts in Magnetic Resonance 13, no. 6 (2001): 404–6. http://dx.doi.org/10.1002/cmr.1027.
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Magoba, Moses, and Mimonitu Opuwari. "Petrophysical interpretation and fluid substitution modelling of the upper shallow marine sandstone reservoirs in the Bredasdorp Basin, offshore South Africa." Journal of Petroleum Exploration and Production Technology 10, no. 2 (November 7, 2019): 783–803. http://dx.doi.org/10.1007/s13202-019-00796-1.
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Abstract The fluid substitution method is used for predicting elastic properties of reservoir rocks and their dependence on pore fluid and porosity. This method makes it possible to predict changes in elastic response of a rock saturation with different fluids. This study focused on the Upper Shallow Marine sandstone reservoirs of five selected wells (MM1, MM2, MM3, MM4, and MM5) in the Bredasdorp Basin, offshore South Africa. The integration of petrophysics and rock physics (Gassmann fluid substitution) was applied to the upper shallow marine sandstone reservoirs for reservoir characterisation. The objective of the study was to calculate the volume of clay, porosity, water saturation, permeability, and hydrocarbon saturation, and the application of the Gassmann fluid substitution modelling to determine the effect of different pore fluids (brine, oil, and gas) on acoustic properties (compressional velocity, shear velocity, and density) using rock frame properties. The results showed average effective porosity ranging from 8.7% to 16.6%, indicating a fair to good reservoir quality. The average volume of clay, water saturation, and permeability values ranged from 8.6% to 22.3%, 18.9% to 41.6%, and 0.096–151.8 mD, respectively. The distribution of the petrophysical properties across the field was clearly defined with MM2 and MM3 revealing good porosity and MM1, MM4, and MM5 revealing fair porosity. Well MM4 revealed poor permeability, while MM3 revealed good permeability. The fluid substitution affected rock property significantly. The primary velocity, Vp, slightly decreased when brine was substituted with gas in wells MM1, MM2, MM3, and MM4. The shear velocity, Vs, remained unaffected in all the wells. This study demonstrated how integration of petrophysics and fluid substitution can help to understand the behaviour of rock properties in response to fluid saturation changes in the Bredasdorp Basin. The integration of these two disciplines increases the obtained results’ quality and reliability.
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Börner, Jana H., Volker Herdegen, Jens-Uwe Repke, and Klaus Spitzer. "Retrieving electrical and structural carbonate formation properties from measurements on crushed rock using a multidata inversion approach." Geophysical Journal International 230, no. 2 (March 3, 2022): 849–69. http://dx.doi.org/10.1093/gji/ggac090.
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SUMMARY Quantification understanding, and prediction of physical rock properties rely so far predominantly on laboratory analyses of cores and plugs. Based on such data, petrophysical models are found that relate both microstructural properties and environmental conditions to geophysically accessible quantities. When considering reactive rock–fluid–gas systems, for example in geothermal energy, enhanced oil recovery or carbon dioxide sequestration, especially with carbonatic rock matrix, this approach is costly and time-consuming at best, or impossible to implement at worst. This is based on the two following reasons: First, porosity, permeability and accessible internal surface area in solid rock plugs are often so low that experimental time duration of many months or even years would be required to achieve chemical equilibrium. Secondly, plugs are single specimens of their — generally heterogeneous — original rock formation, which strongly questions the representativeness of single-plug data. To overcome these shortcomings, we present a new methodology based on the combination of systematic crushing, multimethod laboratory measurements and model-based computational evaluation with solving an inverse problem. As a first step, a large amount of undisturbed rock is intentionally crushed and divided in several particle size classes. Then, petrophysical laboratory measurements are carried out on all particle size classes. The resulting data set is finally inverted for the intended properties of the undisturbed rock. This inverse problem entails a three-level forward model, which parametrizes the undisturbed rock properties, particle characteristics and particle packings, but can also be freely adapted to other tasks by any suitable model representation. The three-level model is designed to enforce the petrophysical correlation of all properties at all levels while using a minimal set of model parameters, thus keeping the inverse problem overdetermined. For the inversion, we have developed a publicly available software tool (AnyPetro) based on a Gauss–Newton inversion scheme to minimize a damped least-squares objective function. To demonstrate and validate the proposed methodology, we present a study using five rock types — four carbonates and one sandstone as a reference. Laboratory measurements of complex electrical conductivity (from spectral induced polarization), specific surface (from nitrogen adsorption) and intraparticle porosity (from mercury intrusion) have been carried out on eight particle size classes and on plugs of each rock for comparison. Supportive and complementary analyses include, for example particle geometry, nuclear magnetic resonance, scanning electron microscopy, computer tomography, uniaxial compression strength and mineralogical composition. We show that our new methodology is highly capable of robustly recovering the complex electrical conductivity, specific surface and porosity of the undisturbed rocks from the measured data. The resulting sets of model parameters are petrophysically reasonable and verifiable. The presented methodology can further be applied to the use of drill cuttings as sample material, which is often the only available rock material from deep wells. Our findings also represent a methodological advance for laboratory experiments on reactive systems and both the interpretation and prediction of petrophysical rock properties in such systems.
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Maksimova, E. N., E. G. Viktorov, E. O. Belyakov, and B. V. Belozerov. "SOCIETY OF PETROPHYSICISTS. ONLINE-PLATFORM FOR KNOWLEDGE MANAGEMENT AND SHARING." Энергия: экономика, техника, экология, no. 4 (2020): 87–92. http://dx.doi.org/10.7868/s2587739920040138.
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The geology of oilfields is becoming more complex, which leads to uncertain distribution of petrophysical properties. Quality of reservoir properties prediction depends on petrophysical models and log interpretation algorithms. It is also connected with the level of expertise of each petrophysicist as well as knowledge sharing among experts and young specialists. The aim of this paper is to present Gazprom Neft Science and Technical Centre approach to development of petrophysical competences with communities of practice.
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Lang, Xiaozheng, and Dario Grana. "Bayesian linearized petrophysical AVO inversion." GEOPHYSICS 83, no. 3 (May 1, 2018): M1—M13. http://dx.doi.org/10.1190/geo2017-0364.1.
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Seismic reservoir characterization aims to provide a 3D model of rock and fluid properties based on measured seismic data. Petrophysical properties, such as porosity, mineral volumes, and water saturation, are related to elastic properties, such as velocity and impedance, through a rock-physics model. Elastic attributes can be obtained from seismic data through seismic modeling. Estimation of the properties of interest is an inverse problem; however, if the forward model is nonlinear, computationally demanding inversion algorithms should be adopted. We have developed a linearized forward model, based on a convolutional model and a new amplitude variation with offset approximation that combined Gray’s linearization of the reflectivity coefficients with Gassmann’s equation and Nur’s critical porosity model. Physical relations between the saturated elastic moduli and the matrix elastic moduli, fluid bulk modulus, and porosity are almost linear, and the model linearization can be obtained by computing the first-order Taylor series approximation. The inversion method for the estimation of the reservoir properties of interest is then developed in the Bayesian framework. If we assume that the distributions of the prior model and error term are Gaussian, then the explicit analytical solution of the posterior distribution of rock and fluid properties can be analytically derived. Our method has first been validated on synthetic seismic data and then applied to a 2D seismic section extracted from a real data set acquired in the Norwegian Sea.
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Dewhurst, David, Tony Siggins, Utpalendu Kuila, Ben Clennell, Mark Raven, and Hege Nordgård Bolås. "Elastic and Petrophysical Properties of Shales." ASEG Extended Abstracts 2007, no. 1 (December 1, 2007): 1–5. http://dx.doi.org/10.1071/aseg2007ab033.
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Rojo, A., F. J. Alonso, and R. M. Esbert. "Propiedades hídricas de algunos granitos ornamentales de la península ibérica con distintos acabados superficiales: interpretación petrofísica." Materiales de Construcción 53, no. 269 (March 30, 2003): 61–72. http://dx.doi.org/10.3989/mc.2003.v53.i269.268.
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Naeini, Ehsan Zabihi, Sam Green, Iestyn Russell-Hughes, and Marianne Rauch-Davies. "An integrated deep learning solution for petrophysics, pore pressure, and geomechanics property prediction." Leading Edge 38, no. 1 (January 2019): 53–59. http://dx.doi.org/10.1190/tle38010053.1.
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In unconventional plays, wells are drilled at an unprecedented rate. This, together with technical challenges in terms of complex stratigraphy, multiple play types, variable rock properties, and various elements of pore pressure, geomechanics, fracturing, and diagenesis, calls for more sophisticated, faster, consistent, and wider ranging analytical tools. Given the scale of the work — i.e., the number of wells — performing classical workflows for petrophysics, pore pressure, and geomechanics prediction can be impractical (if not impossible) due to turnaround considerations. Also such workflows might not use any preexisting regional studies efficiently. In principle, a machine learning approach can mitigate these shortcomings. We show that a supervised deep neural network approach can be an alternative innovative tool for petrophysical, pore pressure, and geomechanics analysis enabling the use of all the previously interpreted data to devise solutions that simultaneously integrate wide-ranging wellbore and wireline logs. Beyond that, a similar approach is taken to predict a certain number of attributes solely from seismically derived properties, which allows one to compute volumetric models. The application of such an algorithm is shown on a Permian case study in which the automatic neural-network-based algorithms achieve reasonable accuracy in a fraction of the time.
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Jameel, Layth A., Fadhil S. Kadhim, and Hussein Ilaibi Al-Sudani. "Geological Model for Khasib Formation of East Baghdad Field Southern Area." Journal of Petroleum Research and Studies 10, no. 3 (November 15, 2020): 21–35. http://dx.doi.org/10.52716/jprs.v10i3.327.
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Geological model construction is an important phase of reservoir study as the production capacity of a reservoir depends on its structural and petrophysical characteristics. The economic benefit of the reservoir is evaluated by estimating the formation petrophysical properties and calculating the oil reserves. East Baghdad southern area field is a newly developing oil field in the middle region of Iraq, where Khasib formation is its main reservoir. The aim of this study is to estimate the petrophysical properties and determine the pay units of the formation under study and the initial oil in place. Sequential Gaussian Simulation was used here to distribute the petrophysical properties as the statistical method and volumetric method was used to calculate the oil in place. The results show that the main reservoir units of the formation are K2 and K3 units, and the estimated oil reserves equal to 2179 mmSTB (346.43 million cubic meters).
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Majeed, Yousif N. Abdul, Dr Ahmad A. Ramadhan, and Dr Ahmed J. Mahmood. "Constructing 3D Geological Model for Tertiary Reservoir in Khabaz Oil Field by using Petrel software." Journal of Petroleum Research and Studies 10, no. 2 (November 12, 2020): 54–75. http://dx.doi.org/10.52716/jprs.v10i2.350.
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3D Geological model for tertiary reservoir in khabaz oil field had been constructed byusing petrel software. Seven wells have been selected in this study in order to designPetrophysical properties (porosity, water saturation, and permeability). Structural modelcan be clarified tertiary reservoir in term of geological structures is a symmetrical smallanticline fold with four faults. Tertiary reservoir consist of six units are (Jeribe, UnitA,UnitA', UnitB, UnitBE, and UnitE). According to Petrophysical properties, layering hadbeen constructed for each tertiary units. Petrophysical model has been designed using thesequential Gaussian simulation algorithm as a geostatistical method. The results illustratesthat Unit B and Unit BE have the best petrophysical properties and the big amount of oil.
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Alafnan, Saad. "The Impact of Pore Structure on Kerogen Geomechanics." Geofluids 2021 (September 15, 2021): 1–12. http://dx.doi.org/10.1155/2021/4093895.
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Production stimulation techniques such as the combination of hydraulic fracturing and lateral drilling have made exploiting unconventional formations economically feasible. Advancements in production aspects are not always in lockstep with our ability to predict and model the extent of a fracturing job. Shale is a clastic sedimentary rock composed of a complex mineralogy of clay, quartz, calcite, and fragments of an organic material known as kerogen. The latter, which consists of large chains of aromatic and aliphatic carbons, is highly elastic, a characteristic that impacts the geomechanics of a shale matrix. Following a molecular simulation approach, the objective of this work is to investigate kerogen’s petrophysics on a molecular level and link it to kerogen’s mechanical properties, considering some range of kerogen structures. Nanoporous kerogen structures across a range of densities were formed from single macromolecule units. Eight units were initially placed in a low-density cell. Then, a molecular dynamic protocol was followed to form a final structure with a density of 1.1 g/cc; the range of density values was consistent with what has been reported in the literature. The structures were subjected to petrophysical assessments including a helium porosity analysis and pore size distribution characterization. Mechanical properties such as Young’s modulus, bulk modulus, and Poisson ratio were calculated. The results revealed strong correlations among kerogen’s mechanical properties and petrophysics. The kerogen with the lowest porosity showed the highest degree of elasticity, followed by other structures that exhibited larger pores. The effect temperature and the fluid occupying the pore volume were also investigated. The results signify the impact of kerogen’s microscale intricacies on its mechanical properties and hence on the shale matrix. This work provides a novel methodology for constructing kerogen structures with different microscale properties that will be useful for delineating fundamental characteristics such as mechanical properties. The findings of this work can be used in a larger scale model for a better description of shale’s geomechanics.
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Alyafei, Nayef, Rashid Al Musleh, Jerahmeel Bautista, Mohamed Idris, and Thomas Seers. "Enhanced Learning of Fundamental Petrophysical Concepts Through Image Processing and 3D Printing." Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description 62, no. 5 (October 1, 2021): 463–76. http://dx.doi.org/10.30632/pjv62n5-2020a2.
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We designed a multidimensional visual learning project with the primary goal of helping undergraduate students better understand fundamental concepts in petrophysics through a set of exercises centered around an analysis of flooding experiment images. More specifically, we focused on concepts related to the trapped fluid within a rock’s pores in this project. To do this, eight different pore networks with unique internal structures were used and then 3D printed. The models were printed using a transparent resin to showcase the movement of fluids inside the rock model. The fluid’s displacement within the 3D-printed rock model was recorded using a high-definition camera, and still images were taken. Undergraduate petroleum engineering students were then assigned a set of exercises to guide them through an analysis of the pore network model images. Students conducted the analysis through an open-source image analysis software (Fiji) to help explore and better understand fundamental petrophysical properties: porosity, fluid saturation, wettability, grain-size distribution, and displacement efficiency. A survey was given to the students to gauge the effectiveness of the exercise in improving their understanding of these concepts. Survey results illustrated that the project-based learning exercises were effective in helping students to better understand difficult-to-grasp petrophysical concepts as they could be more easily visualized through the captured flooding experiment images and the accompanying analysis. An additional benefit to this unique visual learning experience is the ease at which it can be delivered remotely to adhere to safety measures as a result of the global COVID-19 pandemic.
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Grana, Dario, Marco Pirrone, and Tapan Mukerji. "Quantitative log interpretation and uncertainty propagation of petrophysical properties and facies classification from rock-physics modeling and formation evaluation analysis." GEOPHYSICS 77, no. 3 (May 1, 2012): WA45—WA63. http://dx.doi.org/10.1190/geo2011-0272.1.
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Formation evaluation analysis, rock-physics models, and log-facies classification are powerful tools to link the physical properties measured at wells with petrophysical, elastic, and seismic properties. However, this link can be affected by several sources of uncertainty. We proposed a complete statistical workflow for obtaining petrophysical properties at the well location and the corresponding log-facies classification. This methodology is based on traditional formation evaluation models and cluster analysis techniques, but it introduces a full Monte Carlo approach to account for uncertainty evaluation. The workflow includes rock-physics models in log-facies classification to preserve the link between petrophysical properties, elastic properties, and facies. The use of rock-physics model predictions guarantees obtaining a consistent set of well-log data that can be used both to calibrate the usual physical models used in seismic reservoir characterization and to condition reservoir models. The final output is the set of petrophysical curves with the associated uncertainty, the profile of the facies probabilities, and the entropy, or degree of confusion, related to the most probable facies profile. The full statistical approach allows us to propagate the uncertainty from data measured at the well location to the estimated petrophysical curves and facies profiles. We applied the proposed methodology to two different well-log studies to determine its applicability, the advantages of the new integrated approach, and the value of uncertainty analysis.
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Al-Aani, Zuhoor J. Younis. "Geological model Construction for Yamama Formation at Faihaa Oil Field- South of Iraq." BASRA JOURNAL OF SCIENCE 38, no. 3 (August 1, 2020): 521–43. http://dx.doi.org/10.29072/basjs.2020310.
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A construction of a 3D geological model of Yamama Formation to explain the distribution of petrophysical properties (shale volume, effective porosity and hydrocarbon saturation) by using Petrel software. Five wells were selected in order to build structural and petrophysical models based on interpretation of well logs and petrophysical properties. Yamama reservoir is divided into four main units (YA, YB, YC, and YD), YA is divided into five secondary reservoir units (YA1, YA2, YA3, YA4, and YA5), YB is divided into two secondary reservoir units (YB1 and YB2), YC is divided into two secondary reservoir units (YC1 and YC2) and YD is divided into three secondary reservoir units (YD1, YD2, and YD3). Structural model showed Faihaa oil field represented by anticlinal fold with double plunging. Petrophysical models (shale volume, effective porosity and hydrocarbon saturation) constructed for each subunit of Yamama reservoir using sequential Gaussian simulation executed with Petrel software. According to data analyzes and the results from modeling, the subunits for both YB and YB are good reservoir units regarding its good petrophysical properties (high effective porosity and high hydrocarbon saturation) and considered as the most important productive units in Yamama Formation
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Zhang, Bo, Tao Zhao, Xiaochun Jin, and Kurt J. Marfurt. "Brittleness evaluation of resource plays by integrating petrophysical and seismic data analysis." Interpretation 3, no. 2 (May 1, 2015): T81—T92. http://dx.doi.org/10.1190/int-2014-0144.1.
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The main considerations for well planning and hydraulic fracturing in unconventional resources plays include the amount of total organic carbon and how much hydrocarbon can be extracted. Brittleness is the direct measurement of a formation about the ability to create avenues for hydrocarbons when applying hydraulic fracturing. Brittleness can be directly estimated from laboratory stress-strain measurements, rock-elastic properties, and mineral content analysis using petrophysical analysis on well logs. However, the estimated brittleness using these methods only provides “cylinder” estimates near the borehole. We proposed a workflow to estimate brittleness of resource plays in 3D by integrating the petrophysics and seismic data analysis. The workflow began by brittleness evaluation using mineral well logs at the borehole location. Then, we used a proximal support vector machine algorithm to construct a classification pattern between rock-elastic properties and brittleness for the selected benchmark well. The pattern was validated using well-log data that were not used for constructing the classification. Next, we prestack inverted the fidelity preserved seismic gathers to generate a suite of rock-elastic properties volumes. Finally, we obtained a satisfactory brittleness index of target formations by applying the trained classification pattern to the inverted rock-elastic-property volumes.
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Das, Vishal, and Tapan Mukerji. "Petrophysical properties prediction from prestack seismic data using convolutional neural networks." GEOPHYSICS 85, no. 5 (August 17, 2020): N41—N55. http://dx.doi.org/10.1190/geo2019-0650.1.
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We have built convolutional neural networks (CNNs) to obtain petrophysical properties in the depth domain from prestack seismic data in the time domain. We compare two workflows — end-to-end and cascaded CNNs. An end-to-end CNN, referred to as PetroNet, directly predicts petrophysical properties from prestack seismic data. Cascaded CNNs consist of two CNN architectures. The first network, referred to as ElasticNet, predicts elastic properties from prestack seismic data followed by a second network, referred to as ElasticPetroNet, that predicts petrophysical properties from elastic properties. Cascaded CNNs with more than twice the number of trainable parameters as compared to end-to-end CNN demonstrate similar prediction performance for a synthetic data set. The average correlation coefficient for test data between the true and predicted clay volume (approximately 0.7) is higher than the average correlation coefficient between the true and predicted porosity (approximately 0.6) for both networks. The cascaded workflow depends on the availability of elastic properties and is three times more computationally expensive than the end-to-end workflow for training. Coherence plots between the true and predicted values for both cases show that maximum coherence occurs for values of the inverse wavenumber greater than 15 m, which is approximately equal to 1/4 the source wavelength or λ/4. The network predictions have some coherence with the true values even at a resolution of 10 m, which is half of the variogram range used in simulating the spatial correlation of the petrophysical properties. The Monte Carlo dropout technique is used for approximate quantification of the uncertainty of the network predictions. An application of the end-to-end network for prediction of petrophysical properties is made with the Stybarrow field located in offshore Western Australia. The network makes good predictions of petrophysical properties at the well locations. The network is particularly successful in identifying the reservoir facies of interest with high porosity and low clay volume.
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Lei, Xing, Liu Xueqin, Liu Huaishan, Qin Zhiliang, and Ma Benjun. "Research on the Construction of a Petrophysical Model of a Heterogeneous Reservoir in the Hydrate Test Area in the Shenhu Area of the South China Sea (SCS)." Geofluids 2021 (October 31, 2021): 1–19. http://dx.doi.org/10.1155/2021/5586118.
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The occurrence characteristics of hydrates in the Shenhu area reflect a typical inhomogeneity in terms of spatial distribution. It is difficult to accurately describe the petrophysical properties of a reservoir using a petrophysical model considering a single cementation factor parameter. According to the analysis of a mathematical model and the estimation results of V p and V s , the unique structure of foraminiferal sediment particles provides opportunities for forming a diversified hydrate occurrence in the foraminiferal area. In areas where hydrates are thin and interbedded, hydrate reservoirs are generally three-phase media, with obvious thermoelastic properties. Therefore, the parameters of the three characteristic models of the pore-filling model, particle cementation model, and thermodynamic elastic model are all included in the correction model. The weights of the influence factors are then changed to realize an accurate description of the petrophysical characteristics of the correction model in different drilling areas and at different formation depths, reducing the limitations of using a single petrophysical model to describe the petrophysical characteristics of heterogeneous regions under the influence of multiple factors.
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Bosch, Miguel, Luis Cara, Juan Rodrigues, Alonso Navarro, and Manuel Díaz. "A Monte Carlo approach to the joint estimation of reservoir and elastic parameters from seismic amplitudes." GEOPHYSICS 72, no. 6 (November 2007): O29—O39. http://dx.doi.org/10.1190/1.2783766.
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Inversion of seismic data and quantification of reservoir properties, such as porosity, lithology, or fluid saturation, are commonly executed in two consecutive steps: a geophysical inversion to estimate the elastic parameters and a petrophysical inversion to estimate the reservoir properties. We combine within an integrated formulation the geophysical and petrophysical components of the problem to estimate the elastic and reservoir properties jointly. We solve the inverse problem following a Monte Carlo sampling approach, which allows us to quantify the uncertainties of the reservoir estimates accounting for the combination of geophysical data uncertainties, the deviations of the elastic properties from the calibrated petrophysical transform, and the nonlinearity of the geophysical and petrophysical relations. We implement this method for the inference of the total porosity and the acoustic impedance in a reservoir area, combining petrophysical and seismic information. In our formulation, the porosity and impedance are related with a statistical model based on the Wyllie transform calibrated to well-log data. We simulate the seismic data using a convolutional model and evaluate the geophysical likelihood of the joint porosity-impedance models. Applying the Monte Carlo sampling method, we generate a large number of realizations that jointly explain the seismic observations and honor the petrophysical information. This approach allows the calculation of marginal probabilities of the model parameters, including medium porosity, impedance, and seismic source wavelet. We show a synthetic validation of the technique and apply the method to data from an eastern Venezuelan hydrocarbon reservoir, satisfactorily predicting the medium stratification and adequate correlation between the seismic inversion and well-log estimates for total porosity and acoustic impedance.
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Abdelrahman, Moataz Mohamed Gomaa, Norbert Péter Szabó, and Mihály Dobróka. "Meta-algorithm assisted interval inversion for petrophysical properties prediction." Multidiszciplináris tudományok 12, no. 4 (2022): 242–60. http://dx.doi.org/10.35925/j.multi.2022.4.26.
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Well logging inversion was carried out using Levenberg-Marquardt (LM) and Singular Value Decomposition (SVD) techniques for the determination of petrophysical parameters, respectively. In this research, synthetic data contaminated with 5% Gaussian noise, and field data were used to compare the results from the two inversion methods. MATLAB software has been developed to solve the overdetermined inverse problem. The estimated petrophysical parameters from both inversion methods had been compared to one another in terms of robustness to noise, rock interface differentiation, different fluid prediction, and the accuracy of the estimated parameters. This research returns the reason to the inner iterative loop which is considered more about the Jacobian matrix sensitivity. The inversion results showed that both methods can be used in petrophysical data estimation for a reliable well-log data interpretation.
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Suhail, Ahmed Abdulwahhab, Mohammed H. Hafiz, and Fadhil S. Kadhim. "Petrophysical Properties of Nahr Umar Formation in Nasiriya Oil Field." Iraqi Journal of Chemical and Petroleum Engineering 21, no. 3 (September 30, 2020): 9–18. http://dx.doi.org/10.31699/ijcpe.2020.3.2.
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Petrophysical characterization is the most important stage in reservoir management. The main purpose of this study is to evaluate reservoir properties and lithological identification of Nahr Umar Formation in Nasiriya oil field. The available well logs are (sonic, density, neutron, gamma-ray, SP, and resistivity logs). The petrophysical parameters such as the volume of clay, porosity, permeability, water saturation, were computed and interpreted using IP4.4 software. The lithology prediction of Nahr Umar formation was carried out by sonic -density cross plot technique. Nahr Umar Formation was divided into five units based on well logs interpretation and petrophysical Analysis: Nu-1 to Nu-5. The formation lithology is mainly composed of sandstone interlaminated with shale according to the interpretation of density, sonic, and gamma-ray logs. Interpretation of formation lithology and petrophysical parameters shows that Nu-1 is characterized by low shale content with high porosity and low water saturation whereas Nu-2 and Nu-4 consist mainly of high laminated shale with low porosity and permeability. Nu-3 is high porosity and water saturation and Nu-5 consists mainly of limestone layer that represents the water zone.
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Tawfeeq, Yahya. "DIGITAL ROCK ANALYSIS: AN ALTERNATIVE METHOD TO PREDICT PETROPHYSICAL PROPERTIES, CASE STUDY FROM MISHRIF FORMATION." Iraqi Geological Journal 53, no. 2C (September 30, 2020): 34–55. http://dx.doi.org/10.46717/igj.53.2c.4rs-2020-09-04.
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The digital core analysis of petrophysical properties replace the use of conventional core analysis by reducing the required time for investigation. Also, the ability to capture pore geometries and fluid behavior at the pore-scale improves the understanding of complex reservoir structures. In this work, 53 samples of 2D thin section petrographic images were used for analyses from the core plugs taken from the Buzurgan oil field. Each sample was impregnated with blue-dyed epoxy, thin sectioned and then was stained for discrimination of carbonate minerals. Each thin section has been described in detail and illustrated by photomicrographs. The studied samples include a variety of rock types. Packstone is the most common rock type observed followed by grainstone and packstone – wackestone. Floatstone and dolostone are noted rarely in the studied interval. However, the samples of thin section images are processed and digitized, utilizing MATLAB programming and image analysis software. The entire workflow of digital core analysis from image segmentation to petrophysical rock properties determination was performed. A focused has been made on determining effective and total porosity, absolute permeability, and irreducible water saturation. Absolute permeability is estimated with the Kozeny-Carman permeability correlation model and Timur-Coates permeability correlation model. Irreducible water saturation simply is derived from total and effective porosity. Also, some pore void characteristics, such as area and perimeter, were calculated. The results of Digital 2D image analysis have been compared to laboratory core measurements to investigate the reliability and restrictions of the digital image interpretation techniques.
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Prioul, Romain, Richard Nolen-Hoeksema, MaryEllen Loan, Michael Herron, Ridvan Akkurt, Marcelo Frydman, Laurence Reynolds, et al. "Using cuttings to extract geomechanical properties along lateral wells in unconventional reservoirs." GEOPHYSICS 83, no. 3 (May 1, 2018): MR167—MR185. http://dx.doi.org/10.1190/geo2017-0047.1.
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We have developed a method using measurements on drill cuttings as well as calibrated models to estimate anisotropic mechanical properties and stresses in unconventional reservoirs, when logs are not available in lateral wells. We measured mineralogy and organic matter on cuttings using diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS). We described the methodology and illustrated it using two vertical control wells in the Vaca Muerta Formation, Argentina, and one lateral well drilled in the low-maturity oil-bearing reservoir. The method has two steps. First, using a vertical control well containing measurements from cuttings, a comprehensive logging suite, cores, and in situ stress tests, we define and calibrate four models: petrophysical, rock physics, dynamic-static elastic, and geomechanical. The petrophysical model provides petrophysical constituent volumes (mineralogy, organic matter, and fluids) from logs or DRIFTS inputs to the rock-physics model for calculating the dynamic anisotropic elastic moduli. The dynamic-static elastic and geomechanics models provide the relationships for computing static elastic properties and the minimum stress. Second, we acquire DRIFTS data on cuttings in the target lateral well and apply the four models for calculating stresses. We find that the method is successful for two reasons. First, the sonic-log-derived elastic moduli could be reconstructed accurately from the rock-physics model using input from petrophysical volumes from logs and DRIFTS data. A striking observation is that the elastic-property heterogeneity in those wells is explainable almost solely by compositional variations. Second, petrophysical volumes can be reconstructed by the petrophysical model and DRIFTS data. In the lateral well, we observed horizontal variations of mineralogy and organic matter, which controlled variations of elastic moduli and its anisotropy, and, in turn, affected partitioning of the gravitational and tectonic components in the minimum stress. This methodology promises accurate in situ stress estimates using cutting-based measurements and assessments of unconventional-reservoir heterogeneity.
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K, Taheri. "Determination of Petrophysical Parameters of Reservoir Rock with a Special Look to Shale Effect (Case Study: One of the Gas Fields in Southern Iran)." Petroleum & Petrochemical Engineering Journal 5, no. 2 (2021): 1–10. http://dx.doi.org/10.23880/ppej-16000262.
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Determination of petrophysical parameters is necessary for modeling hydrocarbon reservoir rock. The petrophysical properties of rocks influenced mainly by the presence of clay in sedimentary environments. Accurate determination of reservoir quality and other petrophysical parameters such as porosity, type, and distribution of reservoir fluid, and lithology are based on evaluation and determination of shale volume. If the effect of shale volume in the formation not calculated and considered, it will have an apparent impact on the results of calculating the porosity and saturation of the reservoir water. This study performed due to the importance of shale in petrophysical calculations of this gas reservoir. The shale volume and its effect on determining the petrophysical properties and ignoring it studied in gas well P19. This evaluation was performed in Formations A and B at depths of 3363.77 to 3738.98 m with a thickness of 375 m using a probabilistic calculation method. The results of evaluations of this well without considering shale showed that the total porosity was 0.1 percent, the complete water saturation was 31 percent, and the active water saturation was 29 percent, which led to a 1 percent increase in effective porosity. The difference between water saturation values in Archie and Indonesia methods and 3.3 percent shale volume in the zones show that despite the low shale volume in Formations A and B, its effect on petrophysical parameters has been significant. The results showed that if the shale effect not seen in the evaluation of this gas reservoir, it can lead to significant errors in calculations and correct determination of petrophysical parameters.
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Ladygin, V. M., Ju V. Frolova, and Yu S. Genshaft. "Petrophysical properties of Quaternary lavas of Spitsbergen." Russian Journal of Earth Sciences 5, no. 4 (August 25, 2003): 291–98. http://dx.doi.org/10.2205/2003es000128.
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Assefa, Solomon, and Jeremy Sothcott. "Acoustic and Petrophysical Properties of Seafloor Bedrocks." SPE Formation Evaluation 12, no. 03 (September 1, 1997): 157–63. http://dx.doi.org/10.2118/37164-pa.
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Rutter, Ernest, Julian Mecklenburgh, and Kevin Taylor. "Geomechanical and petrophysical properties of mudrocks: introduction." Geological Society, London, Special Publications 454, no. 1 (2017): 1–13. http://dx.doi.org/10.1144/sp454.16.
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Alber, Michael, and Nils Ehringhausen. "Petrophysical Properties of Casing Cement While Curing." Procedia Engineering 191 (2017): 164–71. http://dx.doi.org/10.1016/j.proeng.2017.05.168.
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