Reserve Estimation Research Articles

Dynamic Reserve Calculation Method of Fractured-Vuggy Reservoir Based on Modified Comprehensive Compression Coefficient

The low comprehensive compressibility coefficient characteristic of fracture-vuggy reservoirs often leads to imprecise dynamic reserve calculations. This study introduces a novel method for estimating dynamic reserves, which incorporates a modified comprehensive compressibility coefficient to enhance accuracy. This methodology has been applied to 23 wells in the Tahe Oilfield, resulting in error rates substantially lower than those associated with traditional techniques, thereby markedly enhancing the accuracy of dynamic reserve estimations. Specifically, for karst cave and fracture-vuggy reservoirs, the error rate in dynamic reserve calculations is reduced to under 10%, surpassing conventional methods by more than fivefold. In the case of fractured reservoirs, despite minor fluctuations in error rates due to stress sensitivity, diversion capacity, and channel variations, the proposed method still demonstrates a significant reduction in error rates compared to standard practices.

A review of the Carboniferous shale gas potential of northern England: a data-based analysis of why it won't work

Abstract The recent shale gas revolution originated in the USA in the late 1990s with the exploration of the Carboniferous Barnett Shale in Texas. Success in a number of additional basins in North America, such as the Marcellus, Eagle Ford and Bakken basins, stimulated a search for similar opportunities elsewhere around the world. Among the shales and basins targeted by industry was the Carboniferous Bowland Shale (and equivalents) in northern England. The initial premise that the Barnett Shale represented an excellent analogue for the Bowland Shale led to over-optimistic reserve estimates that have since been shown to be largely incorrect. On the basis of visual inspection of wellbore cores, the Carboniferous Barnett and Bowland shales appear to be very similar. Unfortunately, it is there that the similarity ends. Research carried out for the UK Unconventional Hydrocarbons project has highlighted important differences adversely impacting prospectivity. These can be summarized as basin type/continuity and structural complexity. The total organic carbon, maturity, mineralogy and thickness of the Bowland Shale and equivalents are broadly similar to the successful US examples. Our conclusion is that the Bowland Shale in the UK does not represent a technically significant resource, and in hindsight did not merit the considerable industry and media attention that has been associated with it. One key learning is that fundamental research based on heritage data and modern analytical and modelling techniques should have preceded drilling and fracking operations in northern England.

Impacts of solid rock components on resistivity-based reserves evaluation in organic-rich mudrocks

The effective electrical conductivity of organic-rich mudrocks can be influenced by the presence of clay, pyrite, and thermally mature organic matter. In this paper, we investigate the impacts of conductivity, volumetric concentrations, and spatial distribution/connectivity of clay, pyrite, and kerogen networks on the effective conductivity of the rock and how this affects the assessment of water/hydrocarbon saturation. This quantification enables an understanding of when such components need to be considered in interpreting resistivity measurements in organic-rich mudrocks. We perform sensitivity analysis on the impacts of (a) thermal-maturity-dependent kerogen conductivity, (b) volumetric concentration/spatial distribution of kerogen, (c) conductivity and volumetric concentration/spatial distribution of pyrite, and (d) cation exchange capacities of various clay minerals and their concentration/spatial distribution on the effective conductivity of the rock. The sensitivity analysis showed that with increasing pyrite concentration, the effective conductivity of the rock increased. This increment became significant when the concentration of pyrite was above 2%. Lastly, we observed that thermally mature kerogen increased the conductivity of the rock, with a significant increment occurring when the kerogen conductivity was above 0.01 S m −1 . Results confirmed that the incorporation of conductive rock components such as clay, pyrite, and kerogen into the electrical rock physics model improved the estimates of hydrocarbon reserves.

Improvement in the estimation of perfusable tissue fraction and myocardial flow reserve in the ischemic myocardial lesions using ECG-gated dynamic myocardial PET with 15O-water.

Perfusable tissue fraction (PTF) and myocardial flow reserve (MFR) from 15O-water dynamic positron emission tomography (PET) are parameters of myocardial viability. However, myocardial motion causes errors in these values. We aimed to develop accurate estimation of PTF and MFR in ischemic lesions using an electro-cardiogram (ECG)-gated dynamic myocardial PET with 15O-water. Twenty-seven patients with ischemic heart disease were enrolled. All patients underwent percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG). List mode 3D PET data and ECG signals were acquired using Philips Gemini TF64 instrument. For each scan, 500MBq of 15O-water was infused slowly for 2min, and the dynamic data were scanned for 6min. Both non-gated dynamic images and ECG-gated diastolic dynamic images were reconstructed. On the myocardial PET images of each patient, the entire myocardial region of interest (ROI) was set and divided into 17 segments. Myocardial blood flow in the resting state (rest MBF), hyperemic state (stress MBF), PTF, and MFR in each segment were estimated from both non-gated and ECG-gated dynamic PET images. Coronary arteriograms were obtained for all patients. In total, 128 normal segments without stenosis and 50 ischemic segments with > 90% stenosis were evaluated. In the ischemic myocardial segments, the PTF with ECG-gated PET was estimated as significantly lower than that with non-gated PET (0.63 ± 0.09 vs. 0.72 ± 0.08 [mL/mL], p < 0.001). The ECG-gated PET estimated a significantly lower PTF in the ischemic segments than in the normal segments (0.63 ± 0.09 vs. 0.67 ± 0.07 [mL/mL], p < 0.01). In the normal segments, the ECG-gated PET detected no significant difference in MFR compared with those from the non-gated PET (2.15 ± 0.76 vs. 2.24 ± 0.79, p = 0.28). However, in the ischemic myocardial segments, the MFR with ECG-gated PET was estimated as significantly lower than that with the non-gated PET (1.23 ± 0.29 vs. 1.69 ± 0.71, p < 0.001). The ECG-gated PET presented a significantly higher inter-observer reproducibility of PTF and rest MBF than the non-gated PET (p < 0.01). Neither stress MBF nor MFR yielded significant differences in inter-observer reproducibility between the ECG-gated and non-gated PET. The ECG-gated dynamic 15O-water PET suppressed the myocardial motion effect and resulted in a lower PTF and MFR in ischemic myocardial lesions than the non-gated PET. The ECG-gated PET seemed to be better than the conventional non-gated dynamic PET for the detection of ischemic myocardial lesion.

Prediction and quantification of effective gas source rocks in a lacustrine basin: Western Depression in the Liaohe Subbasin, China

Due to limited data on the geochemical properties of natural gas, estimations are needed for the effective gas source rock in evaluating gas potential. However, the pronounced heterogeneity of mudstones in lacustrine successions complicates the prediction of the presence and geochemical characteristics of gas source rocks. In this paper, the Liaohe Subbasin of Northeast China is used as an example to construct a practical methodology for locating effective gas source rocks in typical lacustrine basins. Three types of gas source rocks, microbial, oil-type, and coal-type, were distinguished according to the different genetic types of their natural gas. A practical three-dimensional geological model was developed, refined, and applied to determine the spatial distribution of the mudstones in the Western Depression of the Liaohe Subbasin and to describe the geochemical characteristics (the abundance, type, and maturation levels of the organic matter). Application of the model in the subbasin indicates that the sedimentary facies have led to heterogeneity in the mudstones, particularly with respect to organic matter types. The effective gas source rock model constructed for the Western Depression shows that the upper sequence (SQ2) of the Fourth member (Mbr 4) of the Eocene Shahejie Formation (Fm) and the lower and middle sequences (SQ3 and SQ4) of the Third member (Mbr 3) form the principal gas-generating interval. The total volume of effective gas source rocks is estimated to be 586 km3. The effective microbial, oil-type, and coal-type gas source rocks are primarily found in the shallow western slope, the central sags, and the eastern slope of the Western Depression, respectively. This study provides a practical approach for more accurately identifying the occurrence and geochemical characteristics of effective natural gas source rocks, enabling a precise quantitative estimation of natural gas reserves.

Estimation of gold-bearing mineral resources and reserves in North-Eastern Yakutia

Estimation of gold-bearing mineral resources and reserves in North-Eastern Yakutia

The Influence of Kinetic Models and Attenuation Correction on Cadmium-Zinc-Telluride Single-Photon Emission Computed Tomography (CZT SPECT)-Derived Myocardial Blood Flow and Reserve: Correlation with Invasive Angiography Data.

(1) Background: The objective of this study was to determine the optimal post-processing model for dynamic cadmium-zinc-telluride single-photon emission computed tomography (CZT-SPECT). (2) Methods: A total of 235 patients who underwent diagnostic invasive coronary angiography within three months of the SPECT and those who had coronary computed tomography angiography (CCTA) before SPECT (within 3 months) were enrolled in this study. Each SPECT study was processed to obtain global and regional stress myocardial blood flow (sMBF), rest-MBF (rMBF), myocardial flow reserve (MFR) and flow difference (FD) estimates obtained with 1-tissue-compartment (1TCM) and net retention (NR) modes, both with and without attenuation correction. (3) Results: The use of AC led to significantly higher sMBF, rMBF and DF values obtained by 1TCM compared those values derived by 1TCM with NAC; the lowest values of stress MBF and rest MBF were obtained by 1TCM_NAC. The resting flow, MFR and DF were significantly (p < 0.005) higher in the AC model than in NAC. All quantitative variables were significantly (p < 0.05) higher in NR_NAC than in the 1TC_NAC model. Finally, sMBF, rMBF and FD showed significantly (p < 0.05) higher values by using 1TMC_AC compared to NR_AC. (4) Conclusions: We suggested that 1-compartment and net retention models correctly reflect coronary microcirculation and can be used for clinical practice for evaluating quantitative myocardial perfusion by dynamic SPECT. Attenuation correction is an important step in post-processing dynamic SPECT data, which increases the consistency and diagnostic accuracy of models.

Physicochemical Characteristics of Feldspar Deposits in Zango Daji, Kogi State Using Geological Methods

Six rock samples were randomly collected and photographs, locational coordinates and elevation points were taken with appropriate tools and devices. Portions of samples were prepared into thin sections and observed under hand lenses, microscope, tested for hardness and other diagnostic properties. Specific density was also determined. The remaining samples were subjected to geochemical and mineralogical analysis. An average percentage composition of 17.1958 mass % of K2O was obtained which is far greater than its Calcium and Sodium contents, indicating it is a K-feldspar. Geochemical result showed averages of Si2O, Al2O3, K2O, Na2O, CaO, and Fe2O3, contents of 59.54 mass %, 17.83 mass %, 17.19 mass %, 2.33 mass %, 0.08 mass % and 1.60 mass % respectively while mineralogical results revealed it is orthoclase in view of its high alumina content of 17.83 percent. The results showed that the sample specification meets the British International Standard specification. Furthermore, electrical resistivity tomography survey was conducted by setting up Schlumberger Electrode Array to determine the significant resistivity contrast between the feldspar and the compact bedrock in the profile. The resistivity data of eight points were processed into Resists curves after conversion and subjecting the data by inversion with WinResist software to obtain 1 - D and 2 – D maps. Together with results of chemical analyses and vertical electrical sounding, the location map of mineralogical composition of the Oxides were determined. Field and petrographic evidence showed a potential source of gemstones and niobium. The study also revealed the occurrence of feldspar deposit are hosted by granitic and pegmatitic intrusive. The quantum and reserve estimates of both overburden layer and target mineral thickness were determined to be 44.3 ± 2.18 million metric tons and 741,933 ± 132,205 m³ respectively.

Well-Log-Based Reservoir Property Estimation With Machine Learning: A Contest Summary

Well logs are processed and interpreted to estimate in-situ reservoir properties, which are essential for reservoir modeling, reserve estimation, and production forecasting. While the traditional methods are mostly based on multimineral physics or empirical formulae, machine learning provides an alternative data-driven approach that requires much less a-priori geological or petrophysical information. From October 2021 to March 2022, the Petrophysical Data-Driven Analytics Special Interest Group (PDDA SIG) of the Society of Petrophysicists and Well Log Analysts (SPWLA) hosted a machine-learning contest aiming to develop data-driven models for estimating reservoir properties, including shale volume, porosity, and fluid saturation, based on a common set of well logs, including gamma ray, bulk density, neutron porosity, resistivity, and sonic. Log data from nine wells from the same field, together with the interpreted reservoir properties by petrophysicists, were provided as training data, and five additional wells were provided as blind test data. During the contest, various data-driven models were developed by the contestants to predict the three reservoir properties with the provided training data set. The top five performing models from the contest, on average, beat the performance of the benchmarked Random Forest model by 45% in the root-mean-square error (RMSE) score. In the paper, we will review these top-performing solutions, including their preprocessing techniques, feature engineering, and machine-learning models, and summarize their advantages and conditions.

Reserve estimation using paid and incurred claims information

Reserve estimation using paid and incurred claims information

Application of NSR-AISC Method in Reserve Estimation and Technical Economic Evaluation of Low-Grade Polymetallic Deposits: Taking a Low-Grade Copper-Molybdenum Mine in Guangdong Province as an Example

Application of NSR-AISC Method in Reserve Estimation and Technical Economic Evaluation of Low-Grade Polymetallic Deposits: Taking a Low-Grade Copper-Molybdenum Mine in Guangdong Province as an Example

Spectrum of Nanopores, Micropores, and Associated Pore Networks and their Origins in Carbonate Strata

Nano- and micropores (defined as pores less than 10 μm in diameter) are common in carbonate reservoirs as either the sole pore type or in combination (dual pore networks) with matrix macropores and fracture pores. These very fine-scale pores form in limestones and dolostones and in associated organic matter (e.g., solid bitumen). Limestone nano- and micropores occur between crystals that are commonly less than 1 to 9 μm in size in limestone, but in dolostone the crystal size can be much larger. Limestone nano- and micropores commonly originate in three ways, although some inherited original nano- and micropores between mud components are preserved. First, in original lime-mud mixtures of aragonite, Mg–calcite, and calcite, the origin is both depositional and diagenetic as aragonite dissolves and reprecipitates because microrhombic calcite, Mg–calcite transforms to microrhombic calcite, and original calcite grains are generally unaffected. Second, in chalks, nano-and micropores are related to the original depositional fabric as interparticle pores between coccoliths and other pelagic allochems. Third, in sediment originally composed of Mg–calcite-rich allochems, nano-and micropores form by transformation of unstable Mg–calcite allochems to microrhombic calcite. In dolostones, nano-and micropores are associated with extensive dolomitization and the nearly complete occlusion of pores (overdolomitization), whereas another diagenetic origin in dolostones is differential dolomitization at the grain scale. Also, in some dolostones, nano- to micropores pores are inherited from precursor microporous limestone. A late process of nano- and micropore formation is subaerial weathering of both limestones and dolostones resulting in pulverulite. This form of micropores is commonly developed at unconformities as enhanced porosity zones. Organic-matter nano- and micropores in solid bitumen, common in thermally mature organic-rich argillaceous limestone, can also be present in coarser-grained carbonates in which solid-bitumen occurs within macropores. Only in organic-rich limestones do organic-matter pores have potential to form an effective pore system. Because nano- and micropores have multiple origins, their lateral and vertical distribution reflects or depends on their origin; therefore, one must not only describe nano- and micropores, but also define their origin. Recognition of nano- and micropores is important because they form tight carbonate reservoirs and have significant effects on permeability, porosity perseveration with burial, hydrocarbon saturation, hydrocarbon recovery, sweep efficiency, storage, and reserve estimations. Not recognizing nano- and micropore networks can lead to errors relative to the aforementioned measurements and as a result, economic evaluations may be invalid.

Combining Deterministic and Probabilistic Approaches in an Improved Volumetric Model With the Aim to Reduce Geological Uncertainties for Accurate Hydrocarbon Reserve Estimation: Case Study in the Rio Del Rey Basin, Cameroon

The aim of this study is to improve hydrocarbon reservoir estimation by combining the deterministic and probabilistic approaches in an improved volumetric model with the objective of reducing geological uncertainties and achieving better reserve estimations. The case study was made in the Rio Del Rey basin of Cameroon. To achieve this goal, a mathematical model was built using the volumetric expression of the stock tank original oil in place (STOIIP), the Raymer–Hunt expression of porosity and transit time, and the Simandoux model modified by the Schlumberger expression of water saturation. The application and validation of the proposed model were made through Interactive Petrophysics, Petrel software, and Monte Carlo simulation on Minitab Workspace. The results obtained by a deterministic approach on the investigated area of 2000 m2 give a total estimated quantity of oil in place of 11897.67 MMbbl, a total estimated quantity of gas in place of 27.79 Bcf, a total estimated quantity of recoverable oil of 3606.28 MMbbl, and a total estimated quantity of recoverable gas of 19.52 Bcf. The probabilistic approach permitted to obtain an estimated quantity of oil in place of 150194141.45 MMbbl. In this study, it appears that the net value added is $288,898,222. This therefore confirms the accuracy of the model and the profitability of the project.

Constraint-Aware Learning for Fractional Flow Reserve Pullback Curve Estimation from Invasive Coronary Imaging.

Estimation of the fractional flow reserve (FFR) pullback curve from invasive coronary imaging is important for the intraoperative guidance of coronary intervention. Machine/deep learning has been proven effective in FFR pullback curve estimation. However, the existing methods suffer from inadequate incorporation of intrinsic geometry associations and physics knowledge. In this paper, we propose a constraint-aware learning framework to improve the estimation of the FFR pullback curve from invasive coronary imaging. It incorporates both geometrical and physical constraints to approximate the relationships between the geometric structure and FFR values along the coronary artery centerline. Our method also leverages the power of synthetic data in model training to reduce the collection costs of clinical data. Moreover, to bridge the domain gap between synthetic and real data distributions when testing on real-world imaging data, we also employ a diffusion-driven test-time data adaptation method that preserves the knowledge learned in synthetic data. Specifically, this method learns a diffusion model of the synthetic data distribution and then projects real data to the synthetic data distribution at test time. Extensive experimental studies on a synthetic dataset and a real-world dataset of 382 patients covering three imaging modalities have shown the better performance of our method for FFR estimation of stenotic coronary arteries, compared with other machine/deep learning-based FFR estimation models and computational fluid dynamics-based model. The results also provide high agreement and correlation between the FFR predictions of our method and the invasively measured FFR values. The plausibility of FFR predictions along the coronary artery centerline is also validated.

Measurement Claim Reserving Insurance Contract in Accordance with IFRS 17 using Stochastic State Space Model

International Financial Reporting Standard 17 (IFRS 17) is a global accounting standard developed by the International Accounting Standards Board (IASB). It guides the accounting treatment of insurance contracts in financial statements. In IFRS 17, claim reserving is vital for measuring insurance contracts and determining the Contractual Service Margin (CSM). The claim reserving process involves estimating expected claim payouts over the contract’s duration. These estimates are crucial for calculating the liability for incurred claims and determining the CSM, representing unearned profit. Claim data is treated as ordered data by sorting the run-off triangle row-wise, resulting univariate time series with missing values. The state space model provides a framework for modeling time series, assuming system development over time. By taking the log of claim data so that the data is normally distributed, the lognormal state space model, along with Kalman recursion algorithms, can be applied for Incurred but Not Reported (IBNR) projections. The lognormal state space model’s IBNR reserve estimate is more precise and sufficient to compensate loss than the chain ladder method. Furthermore, the performance of the lognormal state space model outperforms the chain ladder method by means of model validation using RMSE, MAE, RSE, and R2.

Why and when do reserves estimates in mining change and innovations take place?

This commentary is a practice expert essay based on review of scientific papers on phosphorus scarcity that provides a resumé of arguments relating to adequacy of phosphate rock (PR) resources to supply future requirements and an explanation as to why, although we cannot know how much will be available in future, we can say that the static lifetime is much more likely to be of the order of hundreds or even thousands of years rather than decades. Once the knowable facts are established, a case can be made for moving towards increased phosphate recycling and loss-reduction, based on the current inefficient use and the consequential harm done to the environment. Whilst these concerns are understandable, given that phosphate resources are finite and unsubstitutable, it is important to derive a true perspective in order that the most efficient use of financial and human resources can be deployed by governments. An assertion in 2010 that phosphorus mining would begin to be resource-constrained within decades proved false, but continues to be referred to by those advocating resource governance. Such assertions, when proved not to be accurate, run the risk of validating a ‘cornucopian’ view of mineral resource adequacy and diminish the tenets of ecological economics which, among other things, prescribe a move towards a circular economy, by cutting losses in the supply chain and increasing recycling. The phosphate supply industry has generally been less concerned about potential resource constrains than the academic community. It is true that, apart from a few larger state-owned producers, this lack of concern partly results from the industry's shorter-term economically-driven perspective which tends towards the cornucopian view. This short-term perspective of the commercial industry is at odds with the long-term mitigation of the impacts of mining that is a feature of ecological economics. In the phosphate industry mining and chemical processing has certainly led to major negative environmental legacies and impacts being deferred to future generations.

Geological and geostatistical analysis for equivalent uranium and thorium mineralization, Gattar-V Eastern Desert, Egypt

Purpose. This paper aims to assess the distribution of uranium and thorium ore grade distribution to produce a uranium potential map and estimate of the uranium ore reserves in the Gattar-V area, Eastern Desert, Egypt. Methods. Multidisciplinary approach is applied to determine the equivalent uranium mineralization in the Gattar-V area. It includes geological (petrographical, mineralogical and geochemical) and geostatistical (kriging analysis and variogram models) methods. Findings. Geological studies show that the U-mineralization located along or near the contact between younger granites and Hammamat sediments exhibits episyenitization and bleaching alteration, respectively. Geochemical studies indicate a strong relationship between U-mineralization and Chemical Alteration Index (CIA), alteration features, and associated hydrothermal solution mineralization. The geostatistical method is used to study the behavior and distribution of U and Th in both younger granites and Hammamat sediments. The Total Gamma, eU, and eTh values are used in kriging analysis and variogram models to determine their spatial dependence and perform a spatial interpolation of sparse measurements and deposition level map. Originality. The use of a multidisciplinary method combining petrographical, mineralogical and geochemical investigations with geostatistical analysis allowed for a quantitative evaluation of the spatial location of geological objects such as uranium mineralization in the area. Practical implications. Variogram models and kriging analysis can also be used to assess the lithological composition of rocks and mineralogical phases, and they also provide a clear vision of the elements distributed in the ore, which is very useful during the planning and production stages.

Log-exponential transformation function for interpreting NMR relaxation measurements of hydrocarbon in organic porous media for enhancing absolute adsorption estimation

Assessing unconventional petroleum resources, particularly shale gas reserve estimation, is challenging due to the adsorption phenomenon. This study presents a new method combining experimental and mathematical procedures to determine the absolute adsorption amount in shale samples. In the experimental section of this study, a new behavior was observed in the NMR decay time series of hydrocarbons in organic porous media. The fast section has a linear relationship with time rather than an exponential one. As a result, a Log-Exponential fit to these decay curves was proposed. Then the logarithmic portion was then used to estimate the absolute adsorbed amount. The method was validated against literature data and conventional methods.Based on this newly developed method, absolute adsorption isotherms were obtained for a Duvernay shale sample and activated carbon packs at pressures ranging from 0.77 MPa to 7 MPa. The model proved to be applicable and consistent with pressure variations. Methane in Duvernay shale exhibited adsorbed isotherm type V, with a methane adsorption capacity of 0.08 g per gram of Total Organic Content (TOC) at 6.24 MPa.In addition to absolute adsorption, the competitive adsorption of methane and CO2 was explored, which is critical for evaluating CO2-enhanced shale gas recovery and storage techniques. The injected CO2 resulted in the displacement of methane from smaller shale pores to larger ones.Adsorption and desorption experiments were conducted to investigate hysteresis. The new method was able to better describe the physical behavior of gaseous hydrocarbons in organic porous media. It was able to capture phase transition and critical pressure specific to organic porous media, which differ from non-organic porous media. This innovative approach enables the accurate characterization of shale reservoirs.

Stochastic Chain-Ladder Reserving with Modeled General Inflation

We consider two possible approaches to the problem of incorporating explicit general (i.e., economic) inflation in the non-life claims reserve estimates and the corresponding reserve SCR, defined—as in Solvency II—under the one-year view. What we call the actuarial approach provides a simplified solution to the problem, obtained under the assumption of deterministic interest rates and absence of inflation risk premia. The market approach seeks to eliminate these shortcomings by combining a stochastic claims reserving model with a stochastic market model for nominal and real interest rates. The problem is studied in details referring to the stochastic chain-ladder provided by the Over-dispersed Poisson model. The application of the two approaches is illustrated by a worked example based on market data.

Integration of a Low Gas-Saturated Zone in Creating a 3D Model of the Medvezhye Field

3D geological modeling is an integral part of reserves estimation and project documentation for the development of gas and oil fields. The developed 3D geological model of the Cenomanian productive complex including the low gas-saturated zone of the Medvezhye field represents a combination of data from the drilling of 350 wells, the structural features of the reservoir, permeability properties determined on cores, seismic surveys, and the results of geophysical well surveys. Based on examining the available well logs recorded in the Medvezhye field wells, the low gas-saturated zone is integrated into the construction of the 3D geological model of the Medvezhye field of the Cenomanian productive complex. A total of three models are constructed, and a 400*400*0.4 m grid is recommended for further hydrodynamic modeling. A comparison of the three grids suggests that a more detailed model delivers more thorough results, however, heavy models cannot be applied to hydrodynamic modeling. Resource estimations do not differ across the three grids significantly.