Logging Methods Research Articles

Features of geophysical monitoring of current oil and gas saturation of productive formations

The process of developing oil and gas fields requires continuous monitoring of the current oil and gas saturation of productive reservoirs. Monitoring the current oil and gas saturation allows for effective hydrocarbon recovery. Solving this problem under the conditions of a cased hole significantly limits the suite of geophysical methods, which are the main source of information about the conditional characteristics of reservoirs. The most effective geophysical methods for determining the current oil and gas saturation of a productive reservoir in a producing well is deemed to be the methods of pulse neutron logging. In this paper, the authors analyzed the features of this method, the geological and technological conditions for its effective application, and identified factors that significantly affect the reliability of log interpretation. The indications of pulse neutron-neutron logging are influenced not only by the geological characteristics of the studied reservoir. During the operation and production of an oil and gas well, technological factors also appear, which often significantly change the methods’ indications. Scientists have identified most of these factors and proposed ways to account for their influence. In their work, the authors focused on two factors that are often neglected when performing logging using pulsed neutron methods, accordingly, and not taking them into account during interpretation often led to misinterpretation of pulsed neutron-neutron logging readings when determining the current oil and gas saturation. There are cases of reservoir contamination during drilling and cementing of the casing, when an unusually large colmatage zone is formed. Or the near-wellbore zone of the reservoir formation is damaged during well operation. Given the limited radial resolution of pulsed neutron methods, an enlargement in the colmatage zone or damaging of the downhole zone of the reservoir during well operation has a significant impact on the method readings. The authors proposed a comprehensive approach that allows avoiding such errors

EVALUATION OF THE EFFICIENCY OF ELECTRIC LOGGING METHODS WHEN STUDYING TIGHTNESS OF CASING STRINGS IN WELLS OF URANIUM DEPOSITS

Link for citation: Sharapatov A., Assirbek N., Samanbetov N. Evaluation of the efficiency of electric logging methods when studying tightness of casing strings in wells of uranium deposits. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 10, рр. 7-15. In Rus. The relevance. When exploiting uranium deposits using the method of in-situ leaching, many problematic issues arise. Among them, it is possible to distinguish a violation of the integrity and tightness of the polymer casing, which leads to leakage of solutions due to defects and threaded connections, colmatation, etc. With the help of geophysical wells surveys, namely current logging and resistivity logging, there is a technological possibility of obtaining actual data on the leakage of solutions into the near-wellbore space (their location, size). The distribution of solutions in the annulus lead to technological and environmental violations during the development of deposits. The main aim: comparative evaluation of the effectiveness of current logging and resistivity logging in solving technological problems – assessment of the integrity of polymer pipes and tightness of threaded connections in the casing of uranium wells and determination of the parameters of liquidation of wells with damaged columns based on the data of current logging or resistivity logging in the casing. Objects: artificial defects in the casing for experimental work: holes in pipes with different diameters and locations, leaky connections of casing pipes. Methods. The work was carried out at one of the sites of the Shu-Sarysu province uranium deposit and includes the following activities: preparation of polymer casing strings for the experiment; physical and technical justification of using geophysical wells surveys methods to study the problem; performing measurement work by current logging and resistivity logging methods; performing computational work using current logging, resistivity logging readings and obtaining values of a probabilistic parameter for evaluation of the state of the casing strings and the decision on the operation of wells; comparative analysis and drawing conclusions on the informativeness of borehole geophysical (electrical) methods. Results. Research results showed that to solve the problem of monitoring the technical condition of casing strings, the use of the resistivity logging method is optimal. The conclusions of the research are based on the analysis of the nature of changes in the diagrams of the electrical methods of current logging and resistivity logging, the sensitivity of the measured values of the electric field to defects in the casing. The quantitative values of the parameter % ANO – the amount of current leakage (anomalies) obtained by calculation according to current logging and resistivity logging data are probabilistic in nature. They made it possible to develop recommendations for making technological and/or managerial decisions on the condition of casing strings and the further use of production wells with various defects in them.

3D-MODELING TECHNOLOGY OF INITIAL OIL SATURATION IN TRANSITIONAL OIL-WATER ZONE BY COMPLEX OF CAPILLARIMETRY AND ELECTRIC LOGGING METHODS

Link for citation: Potekhin D.V., Shiryaev E.O., Galkin S.V. 3D-modeling technology of initial oil saturation in transitional oil-water zone by complex of capillarimetry and electric logging methods. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 10, рр. 98-107. In Rus. The relevance. The 3D distribution of the initial oil saturation in the reservoir volume is one of the key elements of geological and technological modeling, largely determining the quality of subsequent development design solutions. The publication presents an analysis of the current state of the problem of studying the oil-water transition zone and the distribution of oil saturation. For terrigenous hydrophilic reservoirs, electric lateral logging quite reliably controls the fluid saturation of the void space of the oil part of the deposit, which suggests the possibility of its integration with widely used capillarimetry methods. Aim: to evaluate the possibility of reliably determining the oil saturation of terrigenous hydrophilic reservoirs by combining the data of electrical lateral logging, filtration-capacitance properties of reservoirs and capillarimetric core studies, to build a 3D model of the distribution of the initial oil saturation of reservoirs in oil deposits, taking into account the allocation of the oil-water transition zone. Object: oil-saturated reservoirs of the Visean oil deposits of the Perm region. Method: methods of multidimensional mathematical modeling in the development of a methodology for determining the initial oil saturation of reservoirs based on a complex of well logging and capillarimetric studies of the core, construction of 3D distribution of the initial oil saturation of the reservoir, taking into account the parameters of the oil-water transition zone. Results. The authors, based on the developed methodology for the deposit of the reservoir Bb of the Aspinskoe field, built a 3D model of the distribution of the initial oil saturation. For the studied reservoir, they carried out the analysis of distribution of zones of free saturation, undersaturation, transition zone and limiting oil saturation. The resulting 3D model can be used in geological and technological modeling of the development of an oil deposit.

Fluid Identification Method of Nuclear Magnetic Resonance and Array Acoustic Logging for Complex Oil and Water Layers in Tight Sandstone Reservoir

In order to improve the logging interpretation accuracy for complex oil and water layers developed in tight sandstone reservoirs, this study takes the Chang 8 member of the Yanchang Formation in the Huanxian area as the research object, and two new fluid identification methods were constructed based on nuclear magnetic resonance (NMR) logging and array acoustic logging. Firstly, the reservoir characteristics of physical properties and conductivity were studied in the research area, and the limitations of conventional logging methods in identifying complex oil and water layers were clarified. Then, the sensitive parameters for identifying different pore fluids were established by analyzing the relationship between NMR logging and array acoustic logging with different pore fluids. On this basis, the fluid identification plate, composed of movable fluid apparent diffusion coefficient and effective porosity difference (Da-Δφe) by NMR logging data of D9TWE3 observation mode, and the other fluid identification plate, composed of apparent bulk modulus of pore fluid and elastic parameter sensitive factor (Kf-Fac), were constructed, respectively. Finally, these two fluid identification methods were used for reservoir interpretation of actual logging data. This study shows that the two new fluid identification methods constructed by NMR logging and array acoustic logging can effectively eliminate the interference of rock skeleton on logging interpretation, which make them more effective in identifying complex oil and water layers than the conventional logging method. Additionally, the two methods have their own advantages and disadvantages when used separately for interpreting complex oil and water layers, and the comprehensive interpretation of the two methods provides a technical development direction for further improving the accuracy of logging the interpretation of complex oil and water layers.

SigML++: Supervised Log Anomaly with Probabilistic Polynomial Approximation

Security log collection and storage are essential for organizations worldwide. Log analysis can help recognize probable security breaches and is often required by law. However, many organizations commission log management to Cloud Service Providers (CSPs), where the logs are collected, processed, and stored. Existing methods for log anomaly detection rely on unencrypted (plaintext) data, which can be a security risk. Logs often contain sensitive information about an organization or its customers. A more secure approach is always to keep logs encrypted (ciphertext). This paper presents “SigML++”, an extension of “SigML” for supervised log anomaly detection on encrypted data. SigML++ uses Fully Homomorphic Encryption (FHE) according to the Cheon–Kim–Kim–Song (CKKS) scheme to encrypt the logs and then uses an Artificial Neural Network (ANN) to approximate the sigmoid (σ(x)) activation function probabilistically for the intervals [−10,10] and [−50,50]. This allows SigML++ to perform log anomaly detection without decrypting the logs. Experiments show that SigML++ can achieve better low-order polynomial approximations for Logistic Regression (LR) and Support Vector Machine (SVM) than existing methods. This makes SigML++ a promising new approach for secure log anomaly detection.

Missing well-log reconstruction using a sequence self-attention deep-learning framework

Well logging is a critical tool for reservoir evaluation and fluid identification. However, due to borehole conditions, instrument failure, economic constraints, etc., some types of well logs are occasionally missing or unreliable. Existing logging curve reconstruction methods based on empirical formulas and fully connected deep neural networks (FCDNN) can only consider point-to-point mapping relationships. Recurrently structured neural networks can consider a multipoint correlation, but it is difficult to compute in parallel. To take into account the correlation between log sequences and achieve computational parallelism, we develop a novel deep-learning framework for missing well-log reconstruction based on state-of-the-art transformer architecture. The missing well-log transformer (MWLT) uses a self-attention mechanism instead of a circular recursive structure to model the global dependencies of the inputs and outputs. To use different usage requirements, we design the MWLT in three scales: small, base, and large, by adjusting the parameters in the network. A total of 8609 samples from 209 wells in the Sichuan Basin, China, are used for training and validation, and two additional blind wells are used for testing. The data augmentation strategy with random starting points is implemented to increase the robustness of the model. The results show that our proposed MWLT achieves a significant improvement in accuracy over the conventional Gardner’s equation and data-driven approaches such as FCDNN and bidirectional long short-term memory, on the validation data set and blind test wells. The MWLT-large and MWLT-base have lower prediction errors than MWLT-small but require more training time. Two wells in the Songliao Basin, China, are used to evaluate the cross-regional generalized performance of our method. The generalizability test results demonstrate that density logs reconstructed by MWLT remain the best match to the observed data compared with other methods. The parallelizable MWLT automatically learns the global dependence of the parameters of the subsurface reservoir, enabling an efficient missing well-log reconstruction performance.

Potential native timber production in tropical forest restoration plantations

Restoring tropical forests still relies on expensive tree planting. Timber production from native trees offers a promising opportunity to make restoration financially viable, but species growth data are lacking. We assessed the potential of tropical forest restoration plantations for producing native timber in the Atlantic Forest. For that we inventoried a chronosequence of unmanaged restoration plantation sites with ten commercial native tree species. Then we developed growth models and used the Growth-Oriented Logging (GOL) method to inform targeted management decisions, including an optimized timber-focused scenario, based on growth and bole quality assessment. Usually, growth-rate classes for saw wood production would be defined according to the time necessary for achieving 35 cm in DBH. Harvesting age was markedly reduced using GOL for species of fast-growth (from <50 to <25 years), intermediate-growth (from 50 to 70 to 25–50 years), slow-growth (from >70 to 50–75 years). Following GOL, basal area was 42 ± 30% larger at harvest (taking 35 ± 23% more time) or 60 ± 16.5% smaller (taking 66 ± 16% less time). The optimized scenario speeded tree-size achievement and anticipated harvesting in an average of 58 years. Species selection, individualization, and silvicultural management are critical for producing timber in forest restoration programs.

Study on the Evaluation Method of the Water Saturation Logging of a Low-Resistance Oil Reservoir in the Guantao Formation, Bohai Basin

As an unconventional and hidden special oil reservoir, a low-resistance oil reservoir has huge exploration potential. The formation of low-resistance oil reservoirs in the study area is affected by multiple factors, and the electrical characteristics of low-resistance oil reservoirs are not obvious, which makes it difficult to accurately evaluate the oil- and gas-bearing nature of low-resistance reservoirs by traditional saturation evaluation methods. The water saturation evaluation has become the focus and difficulty of the logging interpretation of low-resistance oil reservoirs in the target blocks. Low-resistance oil reservoirs have various reservoir characteristics and genesis mechanisms. Based on this, this paper firstly analyzes the genesis mechanisms of low-resistance oil reservoirs by combining geological, core NMR, X-diffraction, and well logging data. Secondly, on the basis of clarifying the genesis mechanism and the main controlling factors of the low-resistance oil formation, the additional conductivity correction of clay is carried out by combining it with the petroelectricity experiment, and the petroelectricity parameters are determined. Finally, the saturation of the low-resistance oil formation in the study area is quantitatively evaluated using the Simandoux model. The results show that the high immobile water saturation caused by the complex pore structure and the additional electrical conductivity of clay are the main controlling causes of the low-resistance reservoirs in the study area. Compared with the saturation evaluation effect of the W-S model, the evaluation accuracy of the Simandoux model corrected for the additional electrical conductivity of clay is better than that of the W-S model, which is 0.88, the relative error of its computation is 7.2%, and the model constructed can provide quantitative bases for the dredging of the low-resistance reservoirs in the Bohai Basin.

IMPROVED ERROR LOGGING WHEN WORKING WITH THE SELENIUM MODULE IN PYTHON

The article discusses the method of logging (saving) errors resulting from the operation of the selenium module, in case of an unexpected or, conversely, an assumed error, save all data about it for future solutions to this error.&#x0D; Purpose: development of a method for saving unexpected and expected errors that occur during the operation of the selenium module.&#x0D; Method or methodology of work: the article is developing a module capable of saving the error text, where in the code it occurred, its time and the image of the browser page at the time of the error.&#x0D; Result: the selenium error planning module has been developed.

Interpreting coal component content in logging data by combining gray relational analysis and hybrid neural network

The coal component content is an important parameter during the coal resources exploration and exploitation. Previous logging curve regression and single neural network methods have the disadvantages of low accuracy and weak generalization ability in calculating coal component content. In this study, a gray relational analysis-hybrid neural network (GRA-HNN) method is developed by combining GRA and HNN to predict coal component content in logging data. First, the correlation degree between different conventional logging data and coal components is calculated using the GRA method, and logging curves with a correlation degree of ≥0.7 are selected as the input training data set. Then, a back propagation neural network, support vector machine neural network, and radial basis function neural network of different coal components are constructed based on the selected optimal input logging data, and the weighted average strategy is used to form an HNN prediction model. Finally, the GRA-HNN method is used to predict the coal component content of coalbed methane production wells in the Panji mining area. The application results indicate that the coal component content predicted by the GRA-HNN method has the highest accuracy compared with the logging curve regression method and its single neural network model, with a maximum average relative error of 13.4%. In addition, the accuracy of coal component content predicted by some single intelligent models is not always higher than the logging curve regression method, indicating that the neural network model is not necessarily suitable for all coal component content predictions. Our GRA-HNN method not only optimizes the prediction performance of a single neural network model by selecting effective input parameters but also comprehensively considers the prediction effect of several neural network models, which strengthens the generalization ability of neural network model and increases the log interpretation accuracy of coal component content.

Modelling extreme water levels using intertidal topography and bathymetry derived from multispectral satellite images

Abstract. Topographic and bathymetric data are essential for accurate predictions of flooding in estuaries because water depth and elevation data are fundamental components of the shallow-water hydrodynamic equations used in models for storm surges and tides. Where lidar or in situ acoustic surveys are unavailable, recent efforts have centred on using satellite-derived bathymetry (SDB) and satellite-derived topography (SDT). This work is aimed at (1) determining the accuracy of SDT and (2) assessing the suitability of the SDT and SDB for extreme water level modelling of estuaries. The SDT was created by extracting the waterline as it tracks over the topography with changing tides. The method was applied to four different estuaries in Aotearoa / New Zealand: Whitianga, Maketū, Ōhiwa and Tauranga harbours. Results show that the waterline method provides similar topography to the lidar with a root-mean-square error equal to 0.2 m, and it is slightly improved when two correction methods are applied to the topography derivations: the removal of statistical bias (0.02 m improvement) and hydrodynamic modelling correction of waterline elevation (0.01 m improvement). The use of SDT in numerical simulations of surge levels was assessed for Tauranga Harbour in eight different simulation scenarios. Each scenario explored different ways of incorporating the SDT to replace the topographic data collected using non-satellite survey methods. In addition, one of these scenarios combined SDT (for intertidal zones) and SDB (for subtidal bathymetry), so only satellite information is used in surge modelling. The latter SDB is derived using the well-known ratio–log method. For Tauranga Harbour, using SDT and SDB in hydrodynamic models does not result in significant differences in predicting high water levels when compared with the scenario modelled using surveyed bathymetry.

Logging Identification and Distribution of Bauxite in the Southwest Ordos Basin

In recent years, with the discovery of oil and gas in the Carboniferous bauxite reservoir in the Ordos basin, the formation and distribution of bauxite and bauxite reservoirs have attracted the attention of oil and gas explorers. Based on the slightly equidistant core testing of minerals and the porosity on the formation and calibration on the logging curves, we established a logging identification method for bauxite in the study area and fitted the formula for calculating the diaspore content and porosity using logging data. By applying this formula and a large amount of logging data, thickness and porosity maps of the Taiyuan formation of bauxite in the southeastern part of the basin were produced. Then, according to the thickness of the earliest deposited Taiyuan formation on the unconformity surface, we analyzed the paleogeomorphology of the bauxite deposition. Finally, a sedimentary facies map of the Taiyuan formation was developed based on the content of sandstone, coal seams, and carbonate rocks contained there. The results show that the diaspore content of bauxite is positively correlated with the natural gamma logging (GR) values. According to the diaspore contents and the GR values, the aluminiferous rocks in the Taiyuan formation can be divided into three categories: ① Bauxite for GR values &gt; 450 API and diaspore content &gt;70%; ② Argillaceous bauxite for GR values = 300–450 API and diaspore content = 25%–70%; and ③ Bauxitic mudstone for GR values = 220–300 API and diaspore content = 0%–25%. Bauxite mainly occurred in the middle and deep lagoon environments in the lower part of the Taiyuan formation. The lagoon is distributed along the paleokarst groove in the NW strike, with a width of approximately 30–40 km and a length of approximately 150–200 km, among which the thickness of pure bauxite is 9 m, argillaceous bauxite 26 m and alumina mudstone 6 m. Bauxite with a high porosity mainly existed in pure bauxite. The lagoon bauxite in the lower part of the Taiyuan formation gradually changes upward into a tidal flat swamp and carbonate platform environment.

Geophysical prediction of organic matter abundance in source rocks based on geochemical analysis: A case study of southwestern Bozhong Sag, Bohai Sea, China

The Bozhong Sag is the largest petroliferous sag in the Bohai Bay Basin, and the source rocks of Paleogene Dongying and Shahejie Formations were buried deeply. Most of the drillings were located at the structural high, and there were few wells that met good quality source rocks, so it is difficult to evaluate the source rocks in the study area precisely by geochemical analysis only. Based on the Rock-Eval pyrolysis, total organic carbon (TOC) testing, the organic matter (OM) abundance of Paleogene source rocks in the southwestern Bozhong Sag were evaluated, including the lower of second member of Dongying Formation (E3d2L), the third member of Dongying Formation (E3d3), the first and second members of Shahejie Formation (E2s1+2), the third member of Shahejie Formation (E2s3). The results indicate that the E2s1+2 and E2s3 have better hydrocarbon generative potentials with the highest OM abundance, the E3d3 are of the second good quality, and the E3d2L have poor to fair hydrocarbon generative potential. Furthermore, the well logs were applied to predict TOC and residual hydrocarbon generation potential (S2) based on the sedimentary facies classification, using ΔlogR, generalized ΔlogR, logging multiple linear regression and BP neural network methods. The various methods were compared, and the BP neural network method have relatively better prediction accuracy. Based on the pre-stack simultaneous inversion (P-wave impedance, P-wave velocity and density inversion results) and the post-stack seismic attributes, the three-dimensional (3D) seismic prediction of TOC and S2 was carried out. The results show that the seismic near well prediction results of TOC and S2 based on seismic multi-attributes analysis correspond well with the results of well logging methods, and the plane prediction results are identical with the sedimentary facies map in the study area. The TOC and S2 values of E2s1+2 and E2s3 are higher than those in E3d3 and E3d2L, basically consistent with the geochemical analysis results. This method makes up the deficiency of geochemical methods, establishing the connection between geophysical information and geochemical data, and it is helpful to the 3D quantitative prediction and the evaluation of high-quality source rocks in the areas where the drillings are limited.

DecLog: Decentralized Logging in Non-Volatile Memory for Time Series Database Systems

Growing demands for the efficient processing of extreme-scale time series workloads call for more capable time series database management systems (TSDBMS). Specifically, to maintain consistency and durability of transaction processing, systems employ write-ahead logging (WAL) whereby transactions are committed only after the related log entries are flushed to disk. However, when faced with massive I/O, this becomes a throughput bottleneck. Recent advances in byte-addressable Non-Volatile Memory (NVM) provide opportunities to improve logging performance by persisting logs to NVM instead. Existing studies typically track complex transaction dependencies and use barrier instructions of NVM to ensure log ordering. In contrast, few studies consider the heavy-tailed characteristics of time series workloads, where most transactions are independent of each other. We propose DecLog, a decentralized NVM-based logging system that enables concurrent logging of TSDBMS transactions. Specifically, we propose data-driven log sequence numbering and relaxed ordering strategies to track transaction dependencies and resolve serialization issues. We also propose a parallel logging method to persist logs to NVM after being compressed and aligned. An experimental study on the YCSB-TS benchmark offers insight into the performance properties of DecLog, showing that it improves throughput by up to 4.6× while offering lower recovery time in comparison to the open source TSDBMS Beringei.

Interpretasi Data Geophysical Logging untuk Penentuan Sebaran Seam Batubara dalam Bentuk Model 3D

In coal exploration activities, geophysical methods are usually used. One of the most accurate and effective geophysical methods that is still used in coal exploration today is the well logging method. The purpose of this research is to determine the distribution of coal seams in 3D based on well logging data. The data used in this study is secondary data which includes Gamma Ray Log data, Density Log data, and coordinate point data. Gamma Ray Log and Density Log data are interpreted to determine the types of lithology that make up the drill holes, especially coal. Based on the interpretation of the 3D model of the distribution of coal seams in each data it is known that in Seam A it tends to thin to the Southeast and thicken to the North-East, in Seam B it tends to thin out to the Southeast and Northeast, and in Seam C it tends to split to the North-West. and Northeast with a strike ranging from N 53ºE to N 116ºE with a dip ranging from 5º to 12º.

An innovative approach: Combining OTV logging and manual core logging for geotechnical site investigation - A case study from Lesser Himalaya of eastern Nepal

Geotechnical exploration in the youngest Himalayan range requires a thorough understanding of subsurface geological conditions, including lithological, structural, and mechanical properties. Accurate data obtained from test boring, in-situ borehole tests, and logging are essential for this purpose. Down-hole optical imaging, such as the optical televiewer (OTV), can provide a cost-effective and efficient approach to capturing structural geotechnical data by providing high-resolution, oriented images of borehole walls. This study aims to test the effectiveness of a hybrid logging method that combines OTV imaging with manual core logging for geotechnical investigations in the eastern part of the Lesser Himalaya, Nepal. The hybrid method addresses inherent problems such as actual depth matching, errors in the reorientation of acquired cores, and ambiguity in the placement of weak zones like intensely fractured zones, fault gouges, and sheared zones. This approach is critical for identifying weak zones and ensuring safe and stable construction.

Sedimentary Characteristics and Model of Lacustrine Deep Water Gravity Flow in the Third Member of Paleogene Shahejie Formation in Niuzhuang Sag, Bohai Bay Basin, China

This article studies the sedimentary characteristics and models of the delta and gravity flow system of the third member of the Shahejie Formation in the Niuzhuang Sag area. Through seismic, logging, and core observation methods, a thorough investigation is conducted to examine the lithologic characteristics, grain size characteristics, sedimentary structure characteristics, and sedimentary facies distribution characteristics of this region. The results show that the third middle member of the Shahejie Formation in the Niuzhuang Sag can be classified into four sedimentary types: sliding, collapse, clastic flow, and turbidity flow. This article aimed to establish the distribution characteristics and depositional models of the deltaic and gravity flow depositional systems within the study area. The findings reveal that slip deposition primarily occurs near the delta front, while collapse and clastic flow depositions are concentrated near the far slope. Moreover, turbidity flow deposition is found near the far slope. This study significantly contributes to our understanding of the sedimentary characteristics and models associated with deltas and gravity flow systems in faulted lacustrine basins. Furthermore, it enriches existing theories related to gravity flow and provides a valuable reference for the investigation of deep-water sedimentation in continental faulted lacustrine basins.

Sedimentary Facies Types and Their Control of Reservoirs in the Lower Jurassic Lacustrine Facies Shale of the Lianggaoshan Formation, Northeastern Sichuan Basin, China

In recent years, new breakthroughs have been made in the field of shale oil and gas exploration in the Lower Jurassic Lianggaoshan Formation in Sichuan Basin. At present, there is a lack of systematic studies on reservoir properties and sedimentary facies of the Lianggaoshan Formation shale. Therefore, in this study, taking the Lianggaoshan Formation in Sichuan Basin as an example, the sedimentary facies types of shale reservoirs and their control over shale oil and gas are systematically studied, based on a large number of outcrops, experimental testing, logging, and seismic interpretation methods. The results show that five sedimentary microfacies are developed in the Lianggaoshan Formation in the study area, namely, semi-deep lake mud, shallow lake mud, wave-influenced shallow lake mud, delta-influenced shallow lake mud, and underwater interbranch bay microfacies. The stratum thickness of the Lianggaoshan Formation is in the range of 26–315 m, and mainly distributed in the eastern region, but rapidly thinned in the northwestern region. The sedimentary sequence framework of the Lianggaoshan Formation has been constructed. Moreover, the lithology of the Lianggaoshan Formation shale has been divided into three types, including shale, massive mudstone and silty mudstone. The brittleness index and total organic carbon (TOC) value of three types of shale show a negative correlation. Silty mudstone has the highest brittleness, while that of black shale is the lowest. For porosity and permeability, massive mudstone is better than silty mudstone, and silty mudstone is better than black shale. There are many kinds of matrix pores in the Lianggaoshan Formation shale, and the development degree of inorganic pores is higher than that of organic pores. Finally, based on the analysis of oil-bearing, pore types, physical properties and productivity, it is considered that black shale facies is the most favorable lithofacies type. The deep–semi-deep lacustrine facies belt obviously controls the shale oil enrichment of the Lianggaoshan Formation.

An integrated density correction method of four-detector density logging in cased holes

Density logging is critical to shale oil and gas exploration. In density logging of cased holes, the inelastic gamma count and hydrogen index are closely related to the correction of formation density. Aimed at the problems of obtaining the pure inelastic gamma count and correcting the hydrogen index in density logging, the relevant research is implemented in the four detector logging tool. Firstly, a technique to separate the pure inelastic gamma count for density logging is provided. It is based on the pure count coefficient. Then on the basis of determining the density through the pure inelastic count ratio, the hydrogen index is corrected by the epithermal neutron and thermal neutron count ratio. Finally, the integrated density correction equation is proposed. The accuracy of this method is checked using a Monte Carlo model, which provides a strong experimental foundation. By examining the influencing factors, the results show that while the density after Halliburton correction is significantly impacted by borehole size, lithology, salinity, and borehole fluid, the density after integrated correction is least affected by these variables. Besides, the integrated density correction method is more favorable for large borehole size, low salinity and sandstone formation. Through logging examples, it is discovered that the overall uncertainty of the density log after the integrated density correction is lower than the Halliburton density correction log, with a maximum of only 0.013 g/cm3, indicating that the density results are more reliable. The study's findings offer a correction technique for precisely estimating the density of cased holes.

Estimation of multistage hydraulic fracturing parameters using 4D simulation

At the present stage, most oil and gas condensate fields in the southern part of the East Siberian oil and gas province are characterized by an increasing proportion of difficult oil reserves in tight reservoirs. Multistage hydraulic fracturing (MHF) is proposed for the offshore Challenger Sea field (Southeast Dome). The implementation of this technique at a shelf will be a source of additional risks. For example, the properties of the RR-2 overlying seal have not been unambiguously assessed, and there are a number of geological uncertainties, such as the tectonic regime. However, there are a number of arguments in favor of MHF: heterogeneity of the reservoir; low permeability; low water cut of the field; sufficient thickness of the pay zone; and the overlying seal. One more positive factor is that sand ingress is not observed in the process of oil production. The selection of a principal well completion scheme on the eastern side of the RR-7 formation is aimed at effectively recovering the remaining reserves. The objectives of the study performed are: to create a geological and hydrodynamic model of the Challenger Sea (Southeast Dome); develop 1D and 3D geomechanical models; evaluate oil production forecasts based on fundamentally different well completion schemes; and determine the optimum parameters for multistage hydraulic fracturing. The research methods included: petrophysical methods; logging methods; core studies; drilling reports and formation testing data; and 3D, 4D geomechanical simulation. Other geophysical methods included acoustic logging, density logging, and gamma-ray logging. After building a geomechanical model of the reservoir at the beginning of drilling, a hydrodynamic calculation was performed. This established the reservoir pressures and saturations at certain points in time. The results made it possible for the principal stress directions, the values of effective and principal stresses, and the values of elastic strains to be determined. In order to assess MGF process efficiency, production forecasts were made using a hydrodynamic model for an exploration well with conventional completion (perforated liner) and with five-stage MGF. In the first case, the accumulated production was 144 kt over 15 years, and in the second case, 125 kt over 17 years. The difference in cumulative production is due to different initial well flow rates, as well as the rate of oil withdrawal during the first few years of development. Thereafter, the production and daily flow rate curves showed similar behavior. In order to select the most effective option, an economic analysis of the efficiency was performed.