Assessment of Water Saturation Using Dielectric Permittivity Measurements in Formations with Complex Pore Structure: Application to the Core- and Log- Scale Domains

2021 ◽  
Author(s):  
Zulkuf Azizoglu ◽  
Zoya Heidari ◽  
Leonardo Goncalves ◽  
Lucas Abreu Blanes De Oliveira ◽  
Moacyr Silva Do Nascimento Neto
Keyword(s):  
Dielectric Permittivity ◽  
Pore Structure ◽  
Water Saturation ◽  
Rock Type ◽  
Dielectric Dispersion ◽  
Well Logs ◽  
Well Log ◽  
Dielectric Measurements ◽  
The Core ◽  
Permittivity Measurements

Abstract Broadband dielectric dispersion measurements are attractive options for assessment of water-filled pore volume, especially when quantifying salt concentration is challenging. However, conventional models for interpretation of dielectric measurements such as Complex Refractive Index Model (CRIM) and Maxwell Garnett (MG) model require oversimplifying assumptions about pore structure and distribution of constituting fluids/minerals. Therefore, dielectric-based estimates of water saturation are often not reliable in the presence of complex pore structure, rock composition, and rock fabric (i.e., spatial distribution of solid/fluid components). The objectives of this paper are (a) to propose a simple workflow for interpretation of dielectric permittivity measurements in log-scale domain, which takes the impacts of complex pore geometry and distribution of minerals into account, (b) to experimentally verify the reliability of the introduced workflow in the core-scale domain, and (c) to apply the introduced workflow for well-log-based assessment of water saturation. The dielectric permittivity model includes tortuosity-dependent parameters to honor the complexity of the pore structure and rock fabric for interpretation of broadband dielectric dispersion measurements. We estimate tortuosity-dependent parameters for each rock type from dielectric permittivity measurements conducted on core samples. To verify the reliability of dielectric-based water saturation model, we conduct experimental measurements on core plugs taken from a carbonate formation with complex pore structures. We also introduce a workflow for applying the introduced model to dielectric dispersion well logs for depth-by-depth assessment of water saturation. The tortuosity-dependent parameters in log-scale domain can be estimated either via experimental core-scale calibration, well logs in fully water-saturated zones, or pore-scale evaluation in each rock type. The first approach is adopted in this paper. We successfully applied the introduced model on core samples and well logs from a pre-salt formation in Santos Basin. In the core-scale domain, the estimated water saturation using the introduced model resulted in an average relative error of less than 11% (compared to gravimetric measurements). The introduced workflow improved water saturation estimates by 91% compared to CRIM. Results confirmed the reliability of the new dielectric model. In application to well logs, we observed significant improvements in water saturation estimates compared to cases where a conventional effective medium model (i.e., CRIM) was used. The documented results from both core-scale and well-log-scale applications of the introduced method emphasize on the importance of honoring pore structure in the interpretation of dielectric measurements.

INTERPRETATION OF MULTI-FREQUENCY DIELECTRIC PERMITTIVITY MEASUREMENTS FOR ASSESSMENT OF WATER SATURATION IN CARBONATE FORMATIONS WITH COMPLEX PORE STRUCTURE

2021 ◽  
Author(s):  
Zulkuf Azizoglu ◽  
◽  
Zoya Heidari ◽  
Keyword(s):  
Spatial Distribution ◽  
Dielectric Permittivity ◽  
Pore Structure ◽  
Carbonate Rock ◽  
Water Saturation ◽  
Dielectric Dispersion ◽  
Pore Scale ◽  
Rock Samples ◽  
Wide Range ◽  
Permittivity Measurements

Broadband relative dielectric dispersion measurements are considered interesting options for assessment of water-filled pore volume. Conventional models such as Complex Refractive Index Model (CRIM) and Maxwell Garnett (MG), often overlook or oversimplify the complexity of pore structure, geometrical distribution of the constituting fluids, and spatial distribution of minerals. This yields to significant errors in assessment of water saturation especially in rocks with complex pore structure. Therefore, it becomes important to quantify the impacts of pore structure and spatial distribution of minerals on broadband relative dielectric dispersion measurements to be able to make decisions about reliability of water saturation estimates from these measurements in a given formation. The objectives of this paper are (a) to quantify the impacts of pore structure and spatial distribution of minerals on relative dielectric permittivity measurements in a wide range of frequencies, (b) to propose a new simple and physically meaningful workflow, which honors pore geometry and spatial distribution of minerals to enhance fluid saturation assessment using relative dielectric permittivity measurements, (c) to verify the reliability of the introduced model in the pore-scale domain. First, we perform numerical simulations of relative dielectric dispersion measurements in the frequency range of 20 MHz to 1 GHz in the pore-scale domain. The input to the numerical simulator includes pore-scale images of actual complex carbonate rock samples. We use a physically meaningful model which honors spatial distribution of the rock constituents for the multi-frequency interpretation of relative dielectric response. To verify the reliability of the model in multiple frequencies, we apply the model to the results of relative dielectric simulations in the pore-scale domain on 3D computed tomography scan (CT-scan) images of carbonate rock samples, which are synthetically saturated to obtain a wide range of water saturation. We successfully verified the reliability of the introduced model in the pore-scale domain using carbonate rock samples with multi-modal pore-size distribution. Estimated water saturations from the results of simulations at 1 GHz resulted in an average relative error of less than 4%. We observed measurable improvements in fluid saturation estimates compared to the cases which CRIM or MG models are used. Results demonstrated that application of conventional models to estimate water saturation from relative dielectric response is not reliable in frequencies below 1 GHz.

scholarly journals Depositional facies model and reservoir characterization of USANI field 1, Niger delta basin, Nigeria

2017 ◽  
Vol 5 (2) ◽  
pp. 57 ◽  
Author(s):  
Godwin Aigbadon ◽  
A.U Okoro ◽  
Chuku Una ◽  
Ocheli Azuka
Keyword(s):  
Tidal Flat ◽  
Water Saturation ◽  
Well Logs ◽  
Physical Analysis ◽  
Well Log ◽  
Delta Front ◽  
Depositional Facies ◽  
Facies Model ◽  
Core Data ◽  
The Core

The 3-D depositional environment was built using seismic data. The depositional facies was used to locate channels with highly theif zones and distribution of various sedimentary facies. The integration core data and the gamma ray log trend from the wells within the studied interval with right boxcar/right bow-shape indicate muddy tidal flat to mixed tidal flat environments. The bell–shaped from the well logs with the core data indicate delta front with mouth bar, the blocky box- car trend from the well logs with the core data indicate tidal point bar with tidal channel fill. The integration of seismic to well log tie display a good tie in the wells across the field. The attribute map from velocity analysis revealed the presence of hydrocarbons in the identified sands (A, B, C, D1, D2, D4, D5). The major faults F1, F2, F3 and F4 with good sealing capacity are responsible for hydrocarbon accumulation in the field. Detailed petro physical analysis of well log data showed that the studied interval are characterized by sand-shale inter-beds. Eight reservoirs were mapped at depth intervals of 2886m to 3533m with their thicknesses ranging from 12m to 407m. Also the Analysis of the petrophysical results showed that porosity of the reservoirs range from 14% to 28 %; permeability range from 245.70 md to 454.7md; water saturation values from 21.65% to 54.50% and hydrocarbon saturation values from 45.50% to 78.50 %. The by-passed hydrocarbons were identified and estimated in low resistivity pay sands D1, D2 at depth of 2884m – 2940m, sand D5 at depth of 3114m – 3126m respectively. The model serve as a basis for establishing facies model in the field.

Numerical Modeling of Multi-Frequency Complex Dielectric Permittivity Dispersion of Sedimentary Rocks

Geophysics ◽  
2021 ◽  
pp. 1-69
Author(s):  
Artur Posenato Garcia ◽  
Zoya Heidari
Keyword(s):  
Numerical Simulation ◽  
Dielectric Permittivity ◽  
Numerical Simulations ◽  
Dielectric Response ◽  
Water Saturation ◽  
Pore Scale ◽  
Simulation Results ◽  
Wet Rocks ◽  
Permittivity Measurements ◽  
The Impact

The dielectric response of rocks results from electric double layer (EDL), Maxwell-Wagner (MW), and dipolar polarizations. The EDL polarization is a function of solid-fluid interfaces, pore water, and pore geometry. MW and dipolar polarizations are functions of charge accumulation at the interface between materials with contrasting impedances and the volumetric concentration of its constituents, respectively. However, conventional interpretation of dielectric measurements only accounts for volumetric concentrations of rock components and their permittivities, not interfacial properties such as wettability. Numerical simulations of dielectric response of rocks provides an ideal framework to quantify the impact of wettability and water saturation ( Sw) on electric polarization mechanisms. Therefore, in this paper we introduce a numerical simulation method to compute pore-scale dielectric dispersion effects in the interval from 100 Hz to 1 GHz including impacts of pore structure, Sw, and wettability on permittivity measurements. We solve the quasi-electrostatic Maxwell's equations in three-dimensional (3D) pore-scale rock images in the frequency domain using the finite volume method. Then, we verify simulation results for a spherical material by comparing with the corresponding analytical solution. Additionally, we introduce a technique to incorporate α-polarization to the simulation and we verify it by comparing pore-scale simulation results to experimental measurements on a Berea sandstone sample. Finally, we quantify the impact of Sw and wettability on broadband dielectric permittivity measurements through pore-scale numerical simulations. The numerical simulation results show that mixed-wet rocks are more sensitive than water-wet rocks to changes in Sw at sub-MHz frequencies. Furthermore, permittivity and conductivity of mixed-wet rocks have weaker and stronger dispersive behaviors, respectively, when compared to water-wet rocks. Finally, numerical simulations indicate that conductivity of mixed-wet rocks can vary by three orders of magnitude from 100 Hz to 1 GHz. Therefore, Archie’s equation calibrated at the wrong frequency could lead to water saturation errors of 73%.

Petrophysical Type Curves for Identifying the Electrical Character of Petroleum Reservoirs

2007 ◽  
Vol 10 (06) ◽  
pp. 711-729 ◽  
Author(s):  
Paul Francis Worthington
Keyword(s):  
Water Saturation ◽  
Early Stage ◽  
Well Logs ◽  
Log Analysis ◽  
Well Log ◽  
Formation Water ◽  
Water Conductivity ◽  
Core Data ◽  
Water Saturated ◽  
Petrophysical Evaluation

Summary A user-friendly type chart has been constructed as an aid to the evaluation of water saturation from well logs. It provides a basis for the inter-reservoir comparison of electrical character in terms of adherence to, or departures from, Archie conditions in the presence of significant shaliness and/or low formation-water salinity. Therefore, it constitutes an analog facility. The deliverables include reservoir classification to guide well-log analysis, a protocol for optimizing the acquisition of special core data in support of log analysis, and reservoir characterization in terms of an (analog) porosity exponent and saturation exponent. The type chart describes a continuum of electrical behavior for both water and hydrocarbon zones. This is important because some reservoir rocks can conform to Archie conditions in the fully water-saturated state, but show pronounced departures from Archie conditions in the partially water-saturated state. In this respect, the chart is an extension of earlier approaches that were restricted to the water zone. This extension is achieved by adopting a generalized geometric factor—the ratio of water conductivity to formation conductivity—regardless of the degree of hydrocarbon saturation. The type chart relates a normalized form of this geometric factor to formation-water conductivity, a "shale" conductivity term, and (irreducible) water saturation. The chart has been validated using core data from comprehensively studied reservoirs. A workflow details the application of the type chart to core and/or log data. The analog role of the chart is illustrated for reservoir units that show different levels of non-Archie effects. The application of the method should take rock types, scale effects, the degree of core sampling, and net reservoir criteria into account. The principal benefit is a reduced uncertainty in the choice of a procedure for the petrophysical evaluation of water saturation, especially at an early stage in the appraisal/development process, when adequate characterizing data may not be available. Introduction One of the ever-present problems in petrophysics is how to carry out a meaningful evaluation of well logs in situations where characterizing information from quality-assured core analysis is either unavailable or is insufficient to satisfactorily support the log interpretation. This problem is especially pertinent at an early stage in the life of a field, when reservoir data are relatively sparse. Data shortfalls could be mitigated if there was a means of identifying petrophysical analogs of reservoir character, so that the broader experience of the hydrocarbon industry could be utilized in constructing reservoir models and thence be brought to bear on current appraisal and development decisions. Here, a principal requirement calls for type charts of petrophysical character, on which data from different reservoirs can be plotted and compared, as a basis for aligning approaches to future data acquisition and interpretation. This need manifests itself strongly in the petrophysical evaluation of water saturation, a process that traditionally uses the electrical properties of a reservoir rock to deliver key building blocks for an integrated reservoir model. The solution to this problem calls for an analog facility through which the electrical character of a subject reservoir can be compared with others that have been more comprehensively studied. In this way, the degree of confidence in log-derived water saturation might be reinforced. At the limit, the log analyst needs a reference basis for recourse to capillary pressure data in cases where the well-log evaluation of water saturation turns out to be prohibitively uncertain.

Pore-Scale Joint Evaluation of Dielectric Permittivity and Electrical Resistivity for Assessment of Hydrocarbon Saturation Using Numerical Simulations

SPE Journal ◽  
2016 ◽  
Vol 21 (06) ◽  
pp. 1930-1942 ◽  
Author(s):  
Huangye Chen ◽  
Zoya Heidari
Keyword(s):  
Electrical Resistivity ◽  
Spatial Distribution ◽  
Dielectric Permittivity ◽  
Pore Structure ◽  
Maximum Error ◽  
New Method ◽  
Pore Scale ◽  
Resistivity Measurements ◽  
Hydrocarbon Saturation ◽  
Permittivity Measurements

Summary Complex pore geometry and composition, as well as anisotropic behavior and heterogeneity, can affect physical properties of rocks such as electrical resistivity and dielectric permittivity. The aforementioned physical properties are used to estimate in-situ petrophysical properties of the formation such as hydrocarbon saturation. In the application of conventional methods for interpretation of electrical-resistivity (e.g., Archie's equation and the dual-water model) and dielectric-permittivity measurements [e.g., complex refractive index model (CRIM)], the impacts of complex pore structure (e.g., kerogen porosity and intergranular pores), pyrite, and conductive mature kerogen have not been taken into account. These limitations cause significant uncertainty in estimates of water saturation. In this paper, we introduce a new method that combines interpretation of dielectric-permittivity and electrical-resistivity measurements to improve assessment of hydrocarbon saturation. The combined interpretation of dielectric-permittivity and electrical-resistivity measurements enables assimilating spatial distribution of rock components (e.g., pore, kerogen, and pyrite networks) in conventional models. We start with pore-scale numerical simulations of electrical resistivity and dielectric permittivity of fluid-bearing porous media to investigate the structure of pore and matrix constituents in these measurements. The inputs to these simulators are 3D pore-scale images. We then introduce an analytical model that combines resistivity and permittivity measurements to assess water-filled porosity and hydrocarbon saturation. We apply the new method to actual digital sandstones and synthetic digital organic-rich mudrock samples. The relative errors (compared with actual values estimated from image processing) in the estimate of water-filled porosity through our new method are all within the 10% range. In the case of digital sandstone samples, CRIM provided reasonable estimates of water-filled porosity, with only four out of twenty-one estimates beyond 10% relative error, with the maximum error of 30%. However, in the case of synthetic digital organic-rich mudrocks, six out of ten estimates for water-filled porosity were beyond 10% with CRIM, with the maximum error of 40%. Therefore, the improvement was more significant in the case of organic-rich mudrocks with complex pore structure. In the case of synthetic digital organic-rich mudrock samples, our simulation results confirm that not only the pore structure but also spatial distribution and tortuosity of water, kerogen, and pyrite networks affect the measurements of dielectric permittivity and electrical resistivity. Taking into account these parameters through the joint interpretation of dielectric-permittivity and electrical-resistivity measurements significantly improves assessment of hydrocarbon saturation.

scholarly journals Petrophysical Properties Estimation of Euphrates Reservoir in Qayyarah Oil Field Using Core and Well Log Data

2021 ◽  
Vol 54 (2E) ◽  
pp. 186-197
Author(s):  
Maan Al-Majid
Keyword(s):  
Water Saturation ◽  
Oil Field ◽  
Oil Reservoirs ◽  
Coefficient Of Determination ◽  
Well Log ◽  
Secondary Porosity ◽  
Log Data ◽  
The Core ◽  
Core Samples ◽  
True Resistivity

The Early Miocene Euphrates Formation is characterized by its oil importance in the Qayyarah oil field and its neighboring fields. This study relied on the core and log data analyses of two wells in the Qayyarah oil field. According to the cross-plot’s information, the Euphrates Formation is mainly composed of dolomite with varying proportions of limestone and shale. Various measurements to calculate the porosity, permeability, and water saturation on the core samples were made at different depths in the two studied wells Qy-54 and Qy-55. A relationship between water saturation and capillary pressure has been plotted for some core samples to predict sites of normal compaction in the formation. The line regression for this relationship was considered as a function of the ratio of large voids to the total volume of voids in the sample. The coefficient of determination parameter was used in estimating the amount of homogeneity in the sizes of the voids, as it was observed to increase significantly at the sites of shale. After dividing the formation into several zones, the well log data were analyzed to predict the locations of oil presence in both wells. The significance of the negative secondary porosity in detecting the hydrocarbon sites in the Euphrates Formation was deduced by its correspondence with the large increase in the true resistivity values in both wells. More than 90% of the formation parts represent reservoir rocks in both wells, but only about 75% of them are oil reservoirs in the well Qy-54 and nearly 50% of them are oil reservoirs in the well Qy-55.

Rock Type Classification Models Interpretability Using Shapley Values

2021 ◽  
Author(s):  
Anton Georgievich Voskresenskiy ◽  
Nikita Vladimirovich Bukhanov ◽  
Maria Alexandrovna Kuntsevich ◽  
Oksana Anatolievna Popova ◽  
Alexey Sergeevich Goncharov
Keyword(s):  
Machine Learning ◽  
Feature Selection ◽  
Causal Inference ◽  
Rock Type ◽  
Well Logs ◽  
Well Log ◽  
Classification Models ◽  
Rock Types ◽  
Shapley Values ◽  
Type Classification

Abstract We propose a methodology to improve rock type classification using machine learning (ML) techniques and to reveal causal inferences between reservoir quality and well log measurements. Rock type classification is an essential step in accurate reservoir modeling and forecasting. Machine learning approaches allow to automate rock type classification based on different well logs and core data. In order to choose the best model which does not progradate uncertainty further into the workflow it is important to interpret machine learning results. Feature importance and feature selection methods are usually employed for that. We propose an extension to existing approaches - model agnostic sensitivity algorithm based on Shapley values. The paper describes a full workflow to rock type prediction using well log data: from data preparation, model building, feature selection to causal inference analysis. We made ML models that classify rock types using well logs (sonic, gamma, density, photoelectric and resistivity) from 21 wells as predictors and conduct a causal inference analysis between reservoir quality and well logs responses using Shapley values (a concept from a game theory). As a result of feature selection, we obtained predictors which are statistically significant and at the same time relevant in causal relation context. Macro F1-score of the best obtained models for both cases is 0.79 and 0.85 respectively. It was found that the ML models can infer domain knowledge, which allows us to confirm the adequacy of the built ML model for rock types prediction. Our insight was to recognize the need to properly account for the underlying causal structure between the features and rock types in order to derive meaningful and relevant predictors that carry a significant amount of information contributing to the final outcome. Also, we demonstrate the robustness of revealed patterns by applying the Shapley values methodology to a number of ML models and show consistency in order of the most important predictors. Our analysis shows that machine learning classifiers gaining high accuracy tend to mimic physical principles behind different logging tools, in particular: the longer the travel time of an acoustic wave the higher probability that media is represented by reservoir rock and vice versa. On the contrary lower values of natural radioactivity and density of rock highlight the presence of a reservoir. The article presents causal inference analysis of ML classification models using Shapley values on 2 real-world reservoirs. The rock class labels from core data are used to train a supervised machine learning algorithm to predict classes from well log response. The aim of supervised learning is to label a small portion of a dataset and allow the algorithm to automate the rest. Such data-driven analysis may optimize well logging, coring, and core analysis programs. This algorithm can be extended to any other reservoir to improve rock type prediction. The novelty of the paper is that such analysis reveals the nature of decisions made by the ML model and allows to apply truly robust and reliable petrophysics-consistent ML models for rock type classification.

A New Multiphysics Method for Simultaneous Assessment of Permeability and Saturation-Dependent Capillary Pressure in Hydrocarbon-Bearing Rocks

SPE Journal ◽  
2020 ◽  
pp. 1-17
Author(s):  
Artur Posenato Garcia ◽  
Zoya Heidari
Keyword(s):  
Pore Structure ◽  
Capillary Pressure ◽  
Size Distribution ◽  
Water Saturation ◽  
Rock Physics ◽  
Rock Fabric ◽  
The Core ◽  
Directional Permeability ◽  
Water Saturated ◽  
Pore Body

Summary Cost-effective exploitation of heterogeneous/anisotropic reservoirs (e.g., carbonate formations) relies on accurate description of pore structure, dynamic petrophysical properties (e.g., directional permeability, saturation-dependent capillary pressure), and fluid distribution. However, techniques for reliable quantification of permeability still rely on model calibration using core measurements. Furthermore, the assessment of saturation-dependent capillary pressure has been limited to experimental measurements, such as mercury injection capillary pressure (MICP). The objectives of this paper include developing a new multiphysics workflow to quantify rock-fabric features (e.g., porosity, tortuosity, and effective throat size) from integrated interpretation of nuclear magnetic resonance (NMR) and electric measurements; introducing rock-physics models that incorporate the quantified rock fabric and partial water/hydrocarbon saturation for assessment of directional permeability and saturation-dependent capillary pressure; and validating the reliability of the new workflow in the core-scale domain. To achieve these objectives, we introduce a new multiphysics workflow integrating NMR and electric measurements, honoring rock fabric, and minimizing calibration efforts. We estimate water saturation from the interpretation of dielectric measurements. Next, we develop a fluid-substitution algorithm to estimate the T2 distribution corresponding to fully water-saturated rocks from the interpretation of NMR measurements. We use the estimated T2 distribution for assessment of porosity, pore-body-size distribution, and effective pore-body size. Then, we develop a new physically meaningful resistivity model and apply it to obtain the constriction factor and, consequently, throat-size distribution from the interpretation of resistivity measurements. We estimate tortuosity from the interpretation of dielectric-permittivity measurements at 960 MHz by applying the concept of capacitive formation factor. Finally, throat-size distribution, porosity, and tortuosity are used to calculate directional permeability and saturation-dependent capillary pressure. We test the reliability of the new multiphysics workflow in the core-scale domain on rock samples at different water-saturation levels. The introduced multiphysics workflow provides accurate description of the pore structure in partially water-saturated formations with complex pore structure. Moreover, this new method enables real-time well-log-based assessment of saturation-dependent capillary pressure and directional permeability (in presence of directional electrical measurements) in reservoir conditions, which was not possible before. Quantification of capillary pressure has been limited to measurements in laboratory conditions, where the differences in stress field reduce the accuracy of the estimates. We verified that the estimates of permeability, saturation-dependent capillary pressure, and throat-size distribution obtained from the application of the new workflow agreed with those experimentally determined from core samples. We selected core samples from four different rock types, namely Edwards Yellow Limestone, Lueders Limestone, Berea Sandstone, and Texas Cream Limestone. Finally, because the new workflow relies on fundamental rock-physics principles, permeability and saturation-dependent capillary pressure can be estimated from well logs with minimum calibration efforts, which is another unique contribution of this work.

Inversion-based method for estimating total organic carbon and porosity and for diagnosing mineral constituents from multiple well logs in shale-gas formations

2013 ◽  
Vol 1 (1) ◽  
pp. T113-T123 ◽  
Author(s):  
Zoya Heidari ◽  
Carlos Torres-Verdín
Keyword(s):  
Shale Gas ◽  
Evaluation Method ◽  
Water Saturation ◽  
Total Porosity ◽  
Well Logs ◽  
Well Log ◽  
X Ray Diffraction ◽  
X Ray ◽  
Compositional Properties ◽  
Organic Shale

Reliable estimates of petrophysical and compositional properties of organic shale are critical for detecting perforation zones or candidates for hydro-fracturing jobs. Current methods for in situ formation evaluation of organic shale largely rely on qualitative responses and empirical formulas. Even core measurements can be inconsistent and inaccurate when evaluating clay minerals and other grain constituents. We implement a recently introduced inversion-based method for organic-shale evaluation from conventional well logs. The objective is to estimate total porosity, total organic carbon (TOC), and volumetric/weight concentrations of mineral/fluid constituents. After detecting bed boundaries, the first step of the method is to perform separate inversion of individual well logs to estimate bed physical properties such as density, neutron migration length, electrical conductivity, photoelectric factor (PEF), and thorium, uranium , and potassium volumetric/weight concentrations. Next, a multilayer petrophysical model specific to organic shale is constructed with an initial guess obtained from conventional well-log interpretation or X-ray diffraction data; bed physical properties are calculated with the initial layer-by-layer values. Final estimates of organic shale petrophysical and compositional properties are obtained by progressively minimizing the difference between calculated and measured bed properties. A unique advantage of this method is the correction of shoulder-bed effects on well logs, which are prevalent in shale-gas plays. Another advantage is the explicit calculation of accurate well-log responses for specific petrophysical, mineral, fluid, and kerogen properties based on chemical formulas and volumetric concentrations of minerals/kerogen and fluid constituents. Examples are described of the successful application of the new organic-shale evaluation method in the Haynesville shale-gas formation. This formation includes complex solid compositions and thin beds where rapid depth variations of mineral/fluid constituents are commonplace. Comparison of estimates for total porosity, total water saturation, and TOC obtained with (a) commercial software for multimineral analysis, (b) our organic-shale evaluation method, and (c) core/X-ray diffraction measurements indicates a significant improvement in estimates of total porosity and water saturation yielded by our interpretation method. The estimated TOC is also in agreement with core laboratory measurements.

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