Gamma-ray Logs Research Articles

Integration of Seismic and Well Log Data for Reservoir Characterization in Offshore Niger Delta, Nigeria

The demand for fossil fuels is continually increasing due to the growing global population and industrialization. It is thus necessary to find hydrocarbon prospects in new fields and those that have previously been classified as marginal fields in order to maximize production. An integrated approach is required to effectively characterize hydrocarbon reservoirs and assess their ability to store and produce hydrocarbons. 3D seismic reflection data and well log data were combined to quantitatively estimate hydrocarbon reserves in a field, offshore Niger delta, Nigeria. The reservoirs were delineated on the gamma ray and resistivity logs which penetrate four wells selected from the field. The petrophysical analysis provided information about the net-to-gross thickness ratio, porosity, shale volume and water saturation of the reservoirs, deduced from well log suites comprising gamma, resistivity, density and neutron-porosity logs through four wells. The seismic interpretation involved mapping of horizons and faults across the wells on the seismic section. Check shot data were used to tie the seismic data to the well log data to generate the synthetic seismogram. The time structural and depth structural maps were generated. The volumetric analysis entailed derivation of the Gross rock volume from the depth structural map, and estimation of the Stock Tank Oil Initially In Place (STOIIP). Four reservoirs were delineated in each of the four wells. The average thickness of the reservoirs ranges from 56.6 m to 232.7 m while the water saturation varies from 0.29% to 0.57%. The average porosities of the reservoirs ranges from 0.18% to 0.22%. The structural interpretation of the eight faults mapped reveals synthetic and antithetic faults, and rollover anticlines. The time- and depth structural maps generated from the mapped horizons show that the reservoirs are penetrated by the different faults. The Stock Tank Oil Initially In Place (STOIIP) of the reservoirs range from 25 MMstb to 468 MMstb. The study shows that the integration of 3D reflection data and well log data can be used effectively to estimate hydrocarbon reserves. The results of the study are expected to contribute to the development of new exploration and production strategies in the Niger delta basin and similar sedimentary environments.

Petrophysical analysis to determine the hydrocarbon prospectivity of sands in AA field, Niger Delta

Petrophysical analysis is a crucial process in the oil and gas industry. It entails the analysis and interpretation of well logs, fluid samples or core smaples to understand the behaviour of the embedded reservoirs in the subsurface. Three well logs from AA field were provided for this study, but two well data were finally loaded to the workstation due to absence of key well logs (such as gamma ray and density logs) from the third well. The quality control check of the data was done prior to the uploading of data. Delineation of lithologies and identification of hydrocarbon reservoirs were done; the identified reservoirs were correlated across the two wells; and the petrophysical evaluation (such as estimations of shale volume, porosity, permeability and water/hydrocarbon saturation) of the three pay zones (that is, Sand A, B and C) in AA field were done. The porosity of Sands A, B and C varied from 0.27 to 0.28, 0.24 to 0.30 and 0.27. The permeability of Sands A, B and C varied from 1012 to 1314 md, 884 to 1013 md and 692 to 892 md. Meanwhile, the hydrocarbon saturation for Sands A, B and C varied from 1 to 89%, 45 to 80% and 79 to 80%, respectively. It can be concluded that the order of hydrocarbon prospectivity of the reservoir sands correlated across Well AA-1 and Well AA-2 is Sand C > Sand B > Sand A.

Integrating Rock Typing and Petrophysical Evaluations to Enhance Reservoir Characterization for Mishrif Formation in Garraf Oil Field

Accurate reservoir characterization is essential for successful hydrocarbon extraction, especially in complex fields such as the Garraf Oil Field. This study aims to enhance reservoir characterization by integrating different petrophysical assessments and rock typing methodologies. Density, neutron, and sonic porosity evaluations were used to assess porosity, while gamma-ray logs and resistivity measurements were used to determine shale volume. The Archie equation was employed to estimate water saturation and sensitivity analysis was used to determine the cutoff values. The study also utilized rock typing techniques, including hydraulic flow unit assessment and Rock fabric number cross-plots, to categorize reservoir rocks into flow units and identify unique rock types. The combination of these approaches led to the precise identification of reservoir heterogeneities and optimal oil production zones. The results showed that the Gamma-ray log is the best method for determining shale volume, and the closest method for porosity determination is the density log. The water resistivity value was estimated at 0.016, while the Archie parameters (a,m,n) were 1.1, 2.1, and 3.7, respectively, with cutoff values of 0.22 for shale volume, 0.11 for porosity, and 0.56 for water saturation. The study identified five rock types ranging from packstone, pack to wackstone, wackstone, wack to mudstone, and mudstone. Overall, the integration of petrophysical evaluations and rock typing techniques facilitates the accurate delineation of oil-rich zones with enhanced reservoir connectivity.

Lithocodium mound identification using logging-while-drilling image log and quantified cutting analysis — Validation with analogues

Lithocodium mounds are early Cretaceous sedimentary structures described in the literature from outcrops, however, never described in the subsurface. The objective of this work is to identify and characterize Lithocodium mounds in the subsurface along a 25,000 ft horizontal well. Drill cuttings sampled at a 100 ft interval are observed in thin sections to define and quantify key sedimentary indicators (bioclasts, facies, and texture). Logging-while-drilling (LWD) gamma ray (GR), density, neutron, and resistivity logs are acquired along with the LWD high-resolution borehole image (BHI) log. Bedding dips from BHI data, interpreted along the horizontal well, enabled the reconstruction of the reservoir paleotopography. In particular, the alternation of dip azimuth combined with the facies interpretation from the thin sections supported the interpretation of eight distinct mound structures. An assessment of their overall geometry confirmed the mound shape to be subcircular, consistent with the subcircular geometries observed in Oman at the outcrop. The inferred dimensions of the mounds are comparable with the Aptian Lithocodium mounds in Oman (30–40 m), and their intermound organization resembles that of the Albian mounds in Texas. This work demonstrates the value of analyzing cuttings to complement image log interpretation and the value of outcrop analogues for interpreting sedimentary structures. For the first time, the subsurface identification and characterization of Lithocodium mounds and intermounds are achieved.

Reservoir Characterization of KD Field Located Onshore of Akwa-Ibom State, Niger Delta, Nigeria Using Well Logs Property Comparison to Seismic Amplitude Analysis

Characterization of reservoirs defines how well they can generate and store hydrocarbon, reservoir parameters are used to determine the behavior of reservoir fluids under various conditions and to identify the best production practices that can optimize hydrocarbon production, the objective is to identify and map reservoir sand zones using basic logs, provide information about the reservoir depth and thickness using well log data, interpret faults and sealing system using the seismic data and generate amplitude maps and model basic reservoir facies, the method applied was sectioned into three distinct parts that encompasses qualitative well log analysis, seismic interpretation and cross plotting of basic well logs versus amplitude for reservoir characterization, the well data analyzed shows well number 5, 6 and 8 have incomplete GR logs resulting in missing lithology while well 10 have some missing logs, such as, density (DEN) log, neutron porosity (NEU) log and porosity (POR) log, five logs needed for this study were available in the remaining complete wells. These logs include gamma ray (GR) log, resistivity (RES) log, density (DEN) log, neutron porosity (NEU) log, and porosity (POR) log. This study looks at a possible change in log signal due to an increase or decrease in seismic amplitude in characterizing a reservoir sand and how logs are influence with Amplitude peaks and trough.

In-situ radiogenic heat production in the Cenozoic sediments of the North sea

Radioactive decay is a significant heat source in sedimentary basins. Spectral gamma ray logs from the North Sea well 1/2-2 were used to obtain the uranium, thorium and potassium concentrations in the Cenozoic sediments beneath the well. On average, the sediments contain 1.86 ± 0.37% potassium, 10.12 ± 2.55 ppm thorium and 2.74 ± 1.54 ppm uranium. Abnormally high, up to 8 ppm, uranium concentrations were measured in the transition zones between the Nordland and the Hordaland Group and in the Sele Formation of the Rogaland Group.The estimated heat production rate, of all in-situ radioactive isotopes, is, on average, 1.281 ± 0.35 μW/m3. About 12% (0.143 ± 0.31 μW/m3) can be contributed to potassium, 46% (0.570 ± 0.14 μW/m3) to thorium and 42% (0.567 ± 0.31 μW/m3) to uranium. The estimated radiogenic heat rates vary significantly across the main stratigraphic units. On average, radiogenic heat production is more intensive in shale-dominated material (1.33 ± 0.31 μW/m3) than in sand-rich sediments (0.84 ± 0.36 μW/m3). High heat production rates are very closely related to high uranium concentration. In the “hottest” (2.012 ± 0.27 μW/m3) unit, the Sele Formation, the uranium accounts for about 69% of the generated heat, while the thorium and the potassium contribute with 24% and less than 7%, respectively. In the ”coldest” (0.782 ± 0.35 μW/m3) unit, the Forties, the relative contribution of uranium is only about 36% and that of potassium and thorium are about 18% and 46%, respectively.The radiogenic heat rates in the Cenozoic sediments should be integrated in future evaluations of the geothermal potential in the North Sea.

The ∼170 kyr astronomical cycle in the Early Permian Lucaogou Formation of the Junggar Basin

According to Milankovitch’s theory, periodic climate change in Earth’s history is controlled by the periodic changes in the Earth’s orbit and axis of rotation. Milankovitch cycle include eccentricity, obliquity, and precession cycles. In addition to them, there are also some amplitude modulation (AM) cycles that affect the climate system through a series of “nonlinear” feedback processes, such as the 173 kyr obliquity AM cycle. Previous studies have demonstrated that the ∼170 kyr cycle modulate the paleoclimate and carbon cycle at mid-high latitude regions in the Meso-Cenozoic. However, due to the limitation of astronomical solutions and the lack of high-resolution geological records, the ∼170 kyr cycle has been less reported in the Paleozoic Era. In this study, cyclostratigraphic analysis of natural gamma ray (GR) logging data from four wells (Ji30, Ji31, Ji32, and Ji174) and total organic carbon (TOC) data from well Ji174 penetrating the Early Permian Lucaogou Formation in Jimusar Sag, Junggar Basin suggests preservation of eccentricity, obliquity, and precession cycles, and the ∼170 kyr AM cycle. Through the astronomical tuning of GR logging data obtained from four wells to eccentricity target cycles, we established the floating astronomical time scale (ATS). The results indicate an average sedimentation rate ranging from 7.4 to 9.5 cm/kyr and a duration from 2.8 to 3.2 million years (Myr) for the Lucaogou Formation. The differences in sedimentation rate and duration among these four wells may result from different well locations. Moreover, the ∼170 kyr cycle signal has been identified in the detrended GR logging and TOC data series, and its obliquity AM series. This signal might be attributed to the obliquity AM cycles originated from the interaction between s3 and s6 (s3 and s6 represent the precession of nodes of Earth and Saturn), which was recorded in the GR logging and TOC data time series due to nonlinear responses within the depositional system.

دراسة تكاملية بين المسح الاشعاعي و المسح المغناطيسي لصخور الكربوناتايت باستخدام تقنية نظم المعلومات الجغرافية جنوب شرق ليبيا

Due to the economic importance of carbonatite rocks in terms of the presence of rare elements such as uranium and thorium, there are 527 known carbonatite sites around the world including sites R33 and R34A. Both of these sites are located on the eastern edge of the Kufra Basin in the AL-Uwaynat area, south east Libya. Through the ground survey of carbonatite complex, R33 and R34A that located at the eastern edge of the Kufra basin AL- Uwaynat area. The several radioactive anomalies of uranium and thorium were detected. Where we found the highest value for the uranium in the carbonatite rock R33 120 ppm and the lowest value is 40PPM while the highest value of R34 is 240PPM and the lowest was 70PPM . By the study Gamma ray log of the well CH7 the highest value is 730 C.P.S at depth 130m.Through the magnetic survey, the relationship was found between the radioactive anomalies and the magnetic anomalies. Keywords: Radioactive survey, Magnetic survey, Carbonatite, Uranium, Gamma ray log.

Paleogene to Neogene sequence stratigraphy and deepwater depositional systems in Kribi-Campo/Rio-Muni margin (Offshore Cameroon-Equatorial Guinea Margin)

2D seismic data and Gamma Ray logs were interpreted to document the Tertiary deepwater depositional system observed in the southern part of the Kribi-Campo sub-basin and the northern part of the Rio Muni basin, both basins separated by the Campo high. The sedimentary filling of both basins occurred with cyclicity during the Tertiary. The Paleogene filling exhibits at least three Seismic Unit Packages (SUP1 to SUP3) interpreted as some Feeder Channels-Lobe Complexes (FCLC). The units with Mass Transport Complexes (MTCs) are low amplitude and chaotic to transparent seismic facies. They are interpreted as mud-rich complexes. The units related to FCLC, features high to moderate amplitude with shingled oblique progradational clinoforms. The Neogene filling is dominated by some submarine Leveed-Channels Complexes associated to Lobes (LCCL) with low to moderate amplitude and concave-up mounded configuration. The well log analysis revealed three main electrofacies namely, shale, siltstone, and sandstone that were deposited in various depositional environments. Shale lithology are underlined by irregular, bell and bow gamma ray log motifs which may be deposited in inner shelf, tidal channels and channel-levees systems that are associated with transgressive to regressive depositional sequences. Sandstone and siltstone lithology are typified by funnel and cylindrical gamma ray log motifs that are deposited in prograding marine shelf fans and slope channels. Influenced by the high slope of paleotopography around the Campo High, the submarine channel-levee are confined to a western part of Kribi-Campo sub-basin. The FCLC shows large planar distribution, while the MTC are poorly structured.

A New Workflow for Estimating Reservoir Properties With Gradient Boosting Model and Joint Inversion Using MWD Measurements

Triple-combo logs are important measurements for estimating geological, petrophysical, and geomechanical properties. Unfortunately, wireline and advanced logging-while-drilling (LWD) logs are typically dropped from the formation evaluation plan for unconventional wells due to economic constraints or borehole instability risks. Available measurements are typically measurement-while-drilling (MWD) gamma ray (GR) logs, along with surface measurements such as weight on bit (WOB), rate of penetration (ROP), torque, rotation per minute (RPM), and differential pressure. The development of a robust and rapid model for predicting reservoir properties using this limited data set would be of high value for geological evaluation. Estimating such properties is a challenging task due to the nonlinear relationship between the available log data and unknown reservoir properties. A novel workflow that combines two sequential models is presented. First is a machine-learning (ML) algorithm to predict triple-combo logs from drilling dynamics and GR logs. To train the ML algorithm, well logs obtained from multiple wells located in the Eagle Ford and Permian Basins are scrutinized to identify important features. This process includes depth shifting, outlier detection, and feature selection, which allows for strategic hyperparameter tuning. Several regression algorithms are investigated, and it is found that gradient boosting algorithms yield superior prediction performance. Unlike random forest methods, boosting algorithms train predictors sequentially, each trying to correct its predecessor. After triple-combo logs are predicted from MWD logs, a physics-based joint inversion model is applied to estimate various reservoir properties. The trained model is deployed on a blind test well, and the predicted logs show excellent agreement compared to the corresponding triple-combo measurements. The multimineral inversion using predicted triple-combo logs yields a geologic model that is validated with elemental capture spectroscopy (ECS) measurements. Additionally, reconstructed logs from the forward model closely match measured logs by minimizing the cost function. Therefore, real-time estimated geological, petrophysical, and geomechanical properties can reveal complex geologic information and be used to mitigate uncertainty related to drilling optimization, reservoir characterization, development planning, and reserve estimation. Using the MWD logs to predict triple-combo logs followed by a joint inversion is an innovative approach for geological evaluation with a limited data set. The developed workflow can successfully provide (1) geologic lithofacies identification and rock typing, (2) more confidence in real-time drilling operation, (3) reservoir properties prediction, (4) missing log imputations and pseudo-log generation with forward modeling, (5) guidance for future logging and perforation, (6) reference for seismic quantitative interpretation (QI) and well tie, and (7) potentially massive computation time saving from days to minutes.

Characterization of subaerial lava flows of the presalt strata in the Santos Basin based on basic well logs

It is hard to identify volcanic morphologies using well logs to support technical decisions during well drilling and the acquisition of geological information. Therefore, this study was carried out on the volcanic sequence present in the Presalt interval of the Santos Basin, Brazil, which is referred to as the Camboriú Formation. This section was described in a previous study using image well logs as a succession of subaerial lava flows formed mainly by compound pahoehoes, sheet pahoehoes and rubbly pahoehoes. Based on sidewall core samples and petrophysical, geochemical and mineralogical reports, we identified five electrofacies from gamma ray, resistivity, sonic, density and neutron logs, representing patterns for identifying lava flows in subaerial sequences. In addition, we applied a porosity quantification method that resulted in a method for obtaining information from the matrix and presented coherent values in facies that did not present amygdalae or breccias and inferring altered zones from variations in resistivity and density logs or from cross-plots. Patterns of well log responses were defined for each type of lava flow present in the studied well, as was the inference about the most favorable facies for reservoirs. This methodology, which uses basic well logs from basalts, is unprecedented in the Presalt sequence and can be easily used to evaluate this exploratory frontier because of its close association with subaerial volcanism.

Forward modeling of spectral gamma-ray (SGR) logging in sedimentary formations

We propose a new approach to improve spectral gamma-ray (SGR) logging forward modeling by considering the radioactive minerals present in the rock as gamma-ray sources. This is based on the radioactive attenuation theory. The assumptions are: 1) minerals with K40, U238, and Th232 content are considered radioactive sources uniformly distributed in the rock; 2) the measured radioactivity is proportional to the concentration of radioactive minerals and inversely proportional to the rock bulk density; 3) the radioactivity is only attenuated by absorption of gamma-rays. The forward modeling was tested using a synthetic case of sandstone with clay minerals and brine-saturated pores to analyze the sensitivity of SGR to changes in illite/smectite-illite/mica ratios and sandstone porosities. Finally, it was further validated with 44 core samples, of which 22 are from two shale gas and 22 from two clastic formations. The Pearson correlation coefficient applied to measure the misfit between the simulated and observed K, U, Th, and SGR data attained values of 0.82, 0.83, 0.61, and 0.57, respectively. A further improvement to 0.87, 0.85, 0.65, and 0.69 was achieved when applying joint inversion for data where illite/smectite and illite/mica ratios were not specified. The correlation between the simulated and observed data supports the viability of the proposed SGR forward modeling approach method.

Studying the Statistical and Petrophysical of the Mishrif Formation in the Nasiriya Oilfield, Southern Iraq

The Mishrif Formation was studied in seven wells that were distributed in the Nasiriya Oil-field, southern Iraq, well logs were obtained for these wells and included: Gamma ray, Neutron, Density and Resistivity log. The Nasiriya Oil field is located at the unstable platform Mesopotamian zone. The Mishrif Formation was divided into two rock units, the upper MA and lower MB, separated by insulating shale rocks based on the gamma ray log. Furthemore, the lower rock unit was also divided into two reservoir units MB1 and MB2. The petrophysical properties of the formation were studied using various logs and through realationships between the logs. The petrophysical study of the water and hydrocarbon saturations showed that the formation contains varying proportions and quantities of water and hydrocarbons that can be produced. The research also included a statistical study and calculation of reservoir heterogeneity using two methods: first using the Dykstra-Parsons Coefficient, where the results showed that is, the Lateral extension of the reservoir units of the study wells are heterogeneous, and second using the Lorenz coefficient, where the results showed that wells heterogeneous distribution, while Ns-9 and Ns-16 wells a homogeneous distribution.

Automated processing of well logging data to monitor the position of the gas-water contact in underground gas storage facilities

Natural oil and gas deposits in most fields include some fluid contacts, such as oil–water, gas–water, or gas–oil. Monitoring the position of the gas–water contact in underground gas storage (UGS) facilities is crucial for monitoring the safety of the subsurface environment. As UGS facilities are geological features of long-term operation, the condition of these features must be regularly monitored for possible gas leaks due to various reasons, whether geological or technical. Periodic surveys of production wells using geophysical methods make it possible to timely detect the reasons for abnormal technical conditions and higher-than-normal water cuts of reservoirs, and to assess shifts in gas–water contact. The suite of production logging methods for surveying and monitoring underground gas storage facilities includes nuclear logging with the use of steady radiation sources (i.e., gamma ray logging and neutron logging). Analysis and interpretation of these methods make it possible to track the shift over time of the gas–water contact in gas-saturated sandstones with an interparticle porosity of >15%. Data from nuclear logging, temperature logs, and composition-based and flow-based surveying are processed and interpreted with the use of known methods and diagnostic indicators to achieve the following goals: to determine the intervals of inter-reservoir and behind-the-casing fluid movement on the base of the well log, to assess the technical condition of the wellbore, to monitor the position of the gas–water contact in the reservoir, to assess the gas saturation of the reservoir, and to monitor the thickness and integrity of the clay caprocks of UGS facilities [1]. This paper discusses the results of automated processing and interpretation of well data recorded during the survey of an UGS facility to determine the current position of the gas–water contact in the reservoir and the gas–water interface in the well. Quantitative interpretation of the neutron logging data with the use of steady radiation sources was performed, and the current gas saturation factor was estimated. Keywords: gas–water contact (GWC); gas saturation; underground gas storage; processing algorithm; gas–water interface (GWI).

Fracture Density Prediction of Basement Metamorphic Rocks Using Gene Expression Programming

Many methods have been developed to detect and predict the fracture properties of fractured rocks. The standard data sources for fracture evaluations are image logs and core samples. However, many wells do not have these data, especially for old wells. Furthermore, operating both methods can be costly, and, sometimes, the data gathered are of bad quality. Therefore, previous research attempted to evaluate fractures indirectly using the widely available conventional well-logs. Sedimentary rocks are widespread and have been studied in the literature. However, fractured reservoirs, like igneous and metamorphic rock bodies, may also be vital since they provide fluid migration pathways and can store some hydrocarbons. Hence, two fractured metamorphic rock bodies are studied in this study to evaluate any difference in fracture responses on well-log properties. Also, a quick and reliable prediction method is studied to predict fracture density (FD) in the case of the unavailability of image logs and core samples. Gene expression programming (GEP) was chosen for this study to predict FD, and ten conventional well-log data were used as input variables. The model produced by GEP was good, with R2 values at least above 0.84 for all studied wells, and the model was then applied to wells without image logs. Both selected metamorphic rocks showed similar results in which the significant parameters to predict FD were the spectral gamma ray, resistivity, and porosity logs. This study also proposed a validation method to ensure that the FD value predictions were consistent using discriminant function analysis. In conclusion, the GEP method is reliable and could be used for FD predictions for basement metamorphic rocks.

Influence of sedimentary architecture on static connectivity and geothermal doublet performance (Mezőberény, SE Hungary)

Although the Pannonian Basin in Hungary boasts significant geothermal potential, most geothermal wells in the region suffer from reinjection issues. The aim of this study is to examine the impact of the sedimentary architecture of a paralic lacustrine succession on the static connectivity of a geothermal aquifer. This problem was examined for a case-study geothermal doublet drilled in Mezőberény, southeast Hungary, which experienced injectivity problems shortly after commencing operations in 2012, ultimately leading to shut-in of the wells. A characterization of the architecture of the deltaic aquifer has been undertaken through a novel workflow that combines sedimentological and sequence stratigraphic analysis of the well-doublet and stochastic 3D modelling techniques to assess the likely static connectivity between the production and injection wells. Planform dimension of aquifer-forming mouth-bar elements and fluvial channel bodies were estimated from geological analogues, selected based on the thickness values of such sedimentary bodies interpreted on the gamma-ray logs of the well doublet and nearby hydrocarbon wells. In total five mouth-bar and two fluvial channel input geometry groups were selected, and fifty object-based realizations were constructed to analyse the static connectivity of different geological scenarios. The internal lithology of mouth-bar and fluvial-channel elements were modelled by sequential indicator simulations (ten realizations). Results of connected volume analysis indicate that the sandstone content of the aquifer is located within vertically segmented fluvial-channel and mouth-bar elements separated by mud-prone prodelta and lower delta-front deposits. This architectural configuration, in combination with low net-sandstone content suggests limited connectivity between the wells. Across the set of stochastic realizations, the volume of sandstone connecting the injection and production wells is ∼4% of the total aquifer volume, on average. Results of this study shows that simplified reservoir models can lead to over-estimation of connectivity of geothermal doublets. The proposed workflow combines sedimentological analysis and 3D modelling supported by geological analogues to predict sandstone reservoir connectivity of deltaic geothermal reservoirs. The described workflow can be carried out in target areas using existing boreholes to assist borehole planning.

Reservoir rock typing assessment in a coal-tight sand based heterogeneous geological formation through advanced AI methods

Geoscientists now identify coal layers using conventional well logs. Coal layer identification is the main technical difficulty in coalbed methane exploration and development. This research uses advanced quantile–quantile plot, self-organizing maps (SOM), k-means clustering, t-distributed stochastic neighbor embedding (t-SNE) and qualitative log curve assessment through three wells (X4, X5, X6) in complex geological formation to distinguish coal from tight sand and shale. Also, we identify the reservoir rock typing (RRT), gas-bearing and non-gas bearing potential zones. Results showed gamma-ray and resistivity logs are not reliable tools for coal identification. Further, coal layers highlighted high acoustic (AC) and neutron porosity (CNL), low density (DEN), low photoelectric, and low porosity values as compared to tight sand and shale. While, tight sand highlighted 5–10% porosity values. The SOM and clustering assessment provided the evidence of good-quality RRT for tight sand facies, whereas other clusters related to shale and coal showed poor-quality RRT. A t-SNE algorithm accurately distinguished coal and was used to make CNL and DEN plot that showed the presence of low-rank bituminous coal rank in study area. The presented strategy through conventional logs shall provide help to comprehend coal-tight sand lithofacies units for future mining.

Yanovstan formation of Western Siberia: Lithology, structure, and correlation of deposits

Research subject. Yanovstan f ormation ( J3-K1jnv) of Kimmeridgian-Early Beriasian age. Aim. To identify structural features of the Yanovstan formation, to carry out a detailed correlation of its deposits, including the development of criteria for determining the boundaries of the suite. Materials and methods. The studies were carried out on the basis of borehole data, including core material from 5 boreholes and borehole logging data from 209 boreholes. The borehole logging complex comprised the following methods: gamma ray logging, neutron gamma ray logging, acoustic logging, caliper logging, as well as apparent resistivity and self-polarization logging. The borehole sections were correlated by tracing individual sections of the geological section, which are characterized by relatively stable geophysical parameters. Additionally, a sequence stratigraphic approach was used. Results. The boundaries between the Sigov and Yanovstan formations were identified based on the description of core material and its comparison with the borehole logging data. The Yanovstan formation was subdivided into three units proposed by the authors: lower (ЯНв), middle (ЯНб), and upper (ЯНa). A borehole correlation of the units of the formation was carried out, on the basis of which maps of the total thickness and net-to-gross ratio and the structural plan of each of the identified stratigraphic units were constructed. It was determined that the total thickness of the lower unit reaches 80 m and is characterized by maxima within the eastern part of the study area. The thickness of the upper unit reaches 240 m and is identified within the northeastern part of the area. This part is represented by a predominantly clay composition. The total thickness of the formation as a whole varies from 40 m in the west to 320 m in the northeast. The thicknesses of the middle unit are relatively consistent throughout the study area. The sandiness of the lower unit varies from 0 to 0.27 units; the upper ranges within 0–0.45 units. The middle unit is not characterized by the presence of sandstones. Conclusions. The theory about the supply of sedimentary material during the sedimentation of the suite from paleomounts within the eastern edge of the West Siberian Jurassic paleobasin was confirmed. An assumption was made that the increased thickness of the predominantly clayey suite within the northeastern part of the study area is associated with the redistribution and transfer of terrigenous material carried from the Siberian land by currents moving unidirectionally along the coast (counterclockwise). These currents thus seized the lightest (clayey) material and transported it to the northern part of the basin.

Friction Angle Prediction of Carbonate Rocks: A Case Study, Rumaila Oil Field

Friction angle (𝜑) and Cohesion (𝑐) are the most important factors to depict rock's shear strength. The friction angle (φ) expresses a unit of rock's capacity to endure shear stress. For the optimization of drilling operations, monitoring of the reservoir, and production of hydrocarbons, the prediction of friction angle is essential. From laboratory measurements or wireline logging data, this parameter can be empirically predicted. The main goal of this study is to develop a new correlation for predicting friction angle for carbonate formations from well logs using the typically accessible well log data (i.e. neutron porosity, gamma ray, bulk density, and sonic logs) and core data. A total of 5197 well log data points were collected from carbonate formation with depth interval of (1920 m to 2711 m) from Rumaila oil field. For all 5197 data points neutron porosity, and gamma ray logs were recorded as a function of depth, and the corresponding shale volume and total porosity were estimated. In addition to these well log data, 20 data core points with 9 different values of friction angle were collected. The developed correlation's estimated friction angle has been contrasted with measured ones. The results show that the new correlation is able to predict the friction angle of carbonate rocks with high accuracy (i.e. R coefficient of the new correlation was 90% and average absolute error of 1.6%).Thus, we conclude that the new correltion can be used to estimate the friction angle for carbonate formation. The new correlation helps in providing continues profile for friction angle with depth and leads to reduce the cost of estimating the rock strength.

Petrophysical Properties Evaluation Using Well Logging of Jeribe Formation in Mansuriya Gas Field Diyala Governorate, Eastern Iraq

Al-Mansuriya gas field is regarded as one of Iraq's most important gas fields because of its good economic gas reserves. The major gas reserves of the Mansuriya field are situated in the Jeribe Formation. The present study aims to determine the petrophysical properties of the Jeribe Formation in the Mansuriya gas field by using the interpretation of different well logs for the open wells MN-1, MN-2, MN-3, and MN-4. The Jeribe Formation was divided into several reservoir units depending on the final results of CPI computer processing interpretation using the Interactive Petrophysics program (Techlog). According to the results of the CPI, the Jeribe Formation in the Mansuriya gas field was divided into seven units, which are J1, J2, J3, J4, J5, J6, and J7. Matrix definition (MID) and density-neutron cross plots indicate that the lithology of the Jeribe Formation consists of a large proportion of dolomite and limestone and a little anhydrite, also in the direction of the gas evident in the Jeribe Formation. The Gamma-ray log showed that the volume of the shale is very small in the Jeribe Formation, and the formation may be clean of shale content. The reason for this small reading is the presence of some radioactive materials in the rocks of formation. Through the readings of the RHOB and NPHI logs and the results of cutoff boundaries, we can conclude that units J1 and J6 represent non-reservoir units and can be considered a cap rock for the reservoir units, and the units J2, J3, J4, and J5 are the main reservoir units for Jeribe Formation according to CPI results and the results of high porosity in these units, as they are characterized by the porosity of up to 24% and water saturation of 40 to 60%, which makes them reservoirs of high quality. The Mn-4 well showed different results from the rest of the wells, and none of its units can be considered a reservoir due to the large water saturation volume.