Logarithmic Curve Research Articles

New Method for Capacity Evaluation of Offshore Low-Permeability Reservoirs with Natural Fractures

In recent years, the development of two offshore low-permeability oil fields has revealed unexpected challenges. The actual productivity of these fields significantly deviates from the designed capacity. Some wells even outperform the expectations for low-permeability limestone fields. This discrepancy primarily stems from a lack of accurate understanding of natural fractures before and after drilling, resulting in substantial errors in capacity assessment. This paper addresses these challenges by proposing a new production capacity model and evaluation method for both vertical and horizontal wells in low-permeability limestone reservoirs. The method leverages logging curve data, incorporating vertical gradation and fractal analysis to effectively represent the fracture’s complexity and connectivity. It uniquely considers factors such as fracture fractal dimensions, threshold pressure, and stress sensitivity, significantly enhancing prediction accuracy. Furthermore, by analyzing the longitudinal gradient in logging curves, the method effectively identifies strong heterogeneity, leading to more accurate capacity evaluations in actual fields. The results demonstrate that our model reduces the average prediction error to less than 15%, markedly outperforming traditional methods. Calculation results of the newly developed capacity formula align closely with actual production data and tracer test results, showcasing its practical applicability and potential for widespread use. This study notably advances the evaluation of reasonable production capacity in similar offshore reservoirs.

Intelligent Classification of Volcanic Rocks Based on Honey Badger Optimization Algorithm Enhanced Extreme Gradient Boosting Tree Model: A Case Study of Hongche Fault Zone in Junggar Basin

Lithology identification is the fundamental work of oil and gas reservoir exploration and reservoir evaluation. The lithology of volcanic reservoirs is complex and changeable, the longitudinal lithology changes a great deal, and the log response characteristics are similar. The traditional lithology identification methods face difficulties. Therefore, it is necessary to use machine learning methods to deeply explore the corresponding relationship between the conventional log curve and lithology in order to establish a lithology identification model. In order to accurately identify the dominant lithology of volcanic rock, this paper takes the Carboniferous intermediate basic volcanic reservoir in the Hongche fault zone as the research object. Firstly, the Synthetic Minority Over-Sampling Technique–Edited Nearest Neighbours (SMOTEENN) algorithm is used to solve the problem of the uneven data-scale distribution of different dominant lithologies in the data set. Then, based on the extreme gradient boosting tree model (XGBoost), the honey badger optimization algorithm (HBA) is used to optimize the hyperparameters, and the HBA-XGBoost intelligent model is established to carry out volcanic rock lithology identification research. In order to verify the applicability and efficiency of the proposed model in volcanic reservoir lithology identification, the prediction results of six commonly used machine learning models, XGBoost, K-nearest neighbor (KNN), gradient boosting decision tree model (GBDT), adaptive boosting model (AdaBoost), support vector machine (SVM) and convolutional neural network (CNN), are compared and analyzed. The results show that the HBA-XGBoost model proposed in this paper has higher accuracy, precision, recall rate and F1-score than other models, and can be used as an effective means for the lithology identification of volcanic reservoirs.

Study on Voids and Seepage Characteristics within Rock Fracture after Shear Dislocation Viewing from CT Test and Numerical Modeling

In rock mass engineering, stress balance changes often cause the relative slip of fractures along a wall surface, impacting the seepage behavior of fluid in the fractures. Using computer tomography (CT) scanning, spatial models of fractures with dislocations ranging from 0 to 10 mm were created to explore the relationship between changes in fracture dislocation and changes in fluid flow behavior, respectively. The spatial fractal dimension of cavity distribution within the fractures was calculated using a thin-plate filling approach to characterize the complexity of the fracture cavity distribution. The fluid flow within the dislocation fractures was then simulated using COMSOL, and the effect of cavity alterations in the form of dislocation on the fluid seepage behavior was analyzed using the spatial fractal. The results show that the values of mechanical aperture after dislocation of the fracture obtained by a CT test are normally distributed, the distribution range of mechanical aperture gradually widens with an increase in the dislocation distance, and the average mechanical aperture increases on a logarithmic curve. The relative spatial fractal dimension decreases gradually with an increase in dislocation distance, and the interconnected pathways within the fracture decrease; in addition, it is observed that the change in the relative spatial fractal dimension is closely correlated with the change in the mean mechanical aperture. Numerical simulations of dislocation fracture seepage found that the permeability increases nonlinearly with increasing dislocation distance. When the dislocation distance reaches 5 mm, nonlinear behaviors such as eddy currents occur, and the influence range of eddy currents gradually expands with the increase in dislocation distance under the influence of the boundary. Moreover, the inertia coefficient B in the Forchheimer equation and the critical hydraulic gradient Jc, which can describe the nonlinear seepage characteristics, show a power function decreasing trend with increasing dislocation distance, and the fluid in the fracture is more likely to produce nonlinear flow.

Fine characterization of interbedding sand-mudstone based on waveform indication inversion

Abstract Owing to the increasing challenges associated with coal mine exploration and development, extremely precise surveys with high-resolution images are required to support production. Conventional inversion methods cannot provide sufficiently precise images of the complex lithologies in coal measure strata. Accordingly, this study performed research in Qiyuan mining area, Shanxi Province, China, and predicted the complex lithology on the basis of facies control using waveform indication inversion and waveform indication simulation. Horizontal changes in seismic waveforms were used to reflect lithologic assemblage characteristics for facies-controlled constraints, and the vertical mapping the connection between seismic waveform and logging curves was shown. Moreover, high-resolution inversions of wave impedance and natural gamma parameters were conducted. Combined with lithologic shielding and accurate time–depth conversion, the inversions enabled the precise characterization of the lithological assemblage distribution in the study area. Our results showed that waveform indication inversion could distinguish between coal seams and limestone, whereas waveform indication simulation based on natural gamma could effectively distinguish between sandstone and mudstone. Furthermore, the horizontal resolution was improved and the vertical resolution extended to a thickness of 2–3 m. In addition, the inversion results were highly consistent with drilling results, with an error <0.1 m. Therefore, waveform indication inversion and simulation could be applied to coal mines for safe and efficient production.

Carrier mobility in organic semiconductors with an exponential density of states under the framework of admittance spectroscopy

The carrier transport in amorphous organic semiconductors with an exponential density of states is systematically studied under the framework of admittance spectroscopy. Due to the exponential distribution, the slope of the double logarithmic curve of current density versus voltage is expressed as b+2, where b relates to the width of the density of states. And the mobility is proportional to nb, where n is the density of carrier. In this case, the peak frequencies of the negative differential susceptance and imaginary part of impedance turn out to be functions of parameter b. Therefore, the relation between transit time and mobility will be a linear function of parameter b. Applying our model to interpret experimental data of both small molecular and polymeric materials are illustrated. The contributions of electric field and of carrier density to mobility are discussed.

Study on Flow Line Characteristics and Well Test Interpretation Methods of Multi Branch Fractured Wells in Dual Porous Media

Fractured reservoirs have developed fractures, strong heterogeneity, and complex seepage patterns. The analysis of core and imaging logging data in Bohai BZ Oilfield shows that there are a large number of fractures developed in the formation, with some wells having up to 6-8 fractures per meter. To study the impact of fractures on seepage, a multi fracture system seepage field simulation method was established, and the characteristic curves of flow lines under different fracture shapes were drawn. The fracture flow line morphology shows that there is a significant difference in the distribution of flow lines between the presence and absence of fractures, and the location of the fractures The size and shape of the reservoir have varying degrees of influence on the distribution of the streamline. The streamline around the well is distributed radially around it. When the fluid encounters an area with developed fractures, it first flows into the fractures and then flows from the fractures towards the wellbore. At the same time, based on the characteristics of fracture development in BZ oilfield and the theory of vertical fracture well testing, a dual medium multi fracture system oil well testing model was established. The model was numerically solved using Laplace transform, and a dual logarithmic curve chart for dual pore medium multi branch fracture well testing was obtained. The effects of fracture branching number, fracture length, conductivity coefficient ratio, and fracture conductivity on the shape of the testing curve were analyzed. The established well testing interpretation model can analyze oilfield stratigraphic information, reservoir fracture development, and boundary conditions. The research results have important guiding significance for evaluating the dynamic performance of oil wells in a dual pore medium multi fracture system and designing oilfield development plans.

DDViT: Advancing lithology identification on FMI image logs through a dual modal transformer model with less information drop

Lithology is an essential topic in oil and gas reservoir studies. Lithological observation lays the foundation for assessing oil and gas prospects and guides future exploration and development. Currently, the prevailing approach in lithological observation heavily depends on the manual analysis of core samples. However, such an approach is highly subjective and time-consuming. With the development of deep learning, some automated deep learning-based methods have been proposed for lithology interpretation from logging curves. However, the Fullbore Formation MicroImager (FMI) image logging, while widely used in the oil field exploration and development process, is occasionally deployed and utilized for lithology identification. In this work, we proposed a Dual-modal Drop-less-information Vision Transformer (DDViT), an FMI image lithology identification model based on transformer architecture. DDViT uses a dual-modal architecture to identify lithology using two different image modalities, namely dynamic FMI images (FMI_DYN) and static FMI images (FMI_STAT). These modalities reflect the local and overall characteristics, respectively. Furthermore, DDViT uses a less-information dropping module to drop the blank band information inherent in the FMI images to make our model more rational and stable. DDViT achieved a 90.81% lithology identification accuracy on Fengxi Well A of the western Qaidam Basin, providing a new approach to lithology identification and demonstrating the great potential of deep learning in geological images.

Identification of carbonate sedimentary facies from well logs with machine learning

Sedimentary facies identification is critical for carbonate oil and gas reservoir development. The traditional method of sedimentary facies identification not only be affected by the engineer's experience but also takes a long time. Identifying carbonate sedimentary facies based on machine learning is the trend of future development and has the advantages of short time consuming and reliable results without engineers' subjective influence. Although many references reported the application of machine learning to identify lithofacies, but identifying sedimentary facies of carbonate reservoirs is much more challenging due to the complex sedimentary environment and tectonic movement. This paper compares the performance of the carbonate sedimentary facies identification using four different machine learning models, and the optimal machine learning with the highest prediction accuracy is recommended. First, the carbonate sedimentary facies are classified into the lagoon, shallow sea, shoal, fore-shoal, and inter-shoal five tags based on the well loggings. Then, five well log curves including spectral gamma ray (SGR), uranium-free gamma ray (CGR), photoelectric absorption cross-section index (PE), true formation resistivity (RT), shallow lateral resistivity (RS) are used as the input, and the manual identified carbonate sedimentary facies are used as the output of the machine learning model. The performance of four different machine learning algorithms, including support vector machine (SVM), deep neural network (DNN), long short-term memory (LSTM) network, and random forest (RF) are compared. The other two wells are used for model validation. The research results show that the RF method has the highest accuracy of sedimentary facies prediction, and the average prediction accuracy is 78.81%; the average accuracy of sedimentary facies prediction using SVM is 77.93%. The sedimentary facies predictions using DNN and LSTM are less satisfying compared with RF and SVM, and the average accuracy is 69.94% and 73.05%, respectively. The predicted carbonate sedimentary facies by LSTM are more continuous compared with other machine learning models. This study is helpful for identifying compelx sedimentary facies of carbonate reservoirs from well logs.

Analysis of the filling patterns and reservoir development models of the Ordovician paleokarst reservoirs in the tahe oilfield

The characteristics of Ordovician paleokarst reservoirs in the Tahe Oilfield are complex. Many prediction studies on the distribution of karst fractures and caves have been carried out, but the filling types and distribution characteristics of caves have been less studied and are thus less understood. First, the development characteristics of the early paleohydrological landforms in the early Hercynian are considered, the paleokarst landforms are restored, the characteristics of the paleohydrological network are clarified, and the lateral distribution of the surface and groundwater systems is illustrated. Additionally, based on a qualitative analysis of core thin section photographs, conventional logging curves, full-bore formation microresistivity scanning, imaging, logging and other characteristics, the existing filling types are divided into four classes: vertical flow filling, river transport filling, cave collapse and hydrothermal transformation. Moreover, reservoir facies division standards for the different filling types are established. Different filling types are constrained in the context of paleogeomorphology and paleohydrology to further study the filling effects and the corresponding controlling factors. As research progresses, five common joint control modes are proposed: joint control of sinkholes and underground rivers, joint control of ancient landforms and underground rivers, joint control of multilayer caves and ancient landforms, control due to collapse and fracture, and joint control of early collapse and late hydrothermal transformation. Based on the model, the relevant mechanisms and the concentrated areas of development are analyzed in depth. The distribution map of the plane filling type is obtained by combining the development model with the identification of the filling type. The relationships between oil and gas production and the reservoir filling degree and between oil and gas migration channels are analyzed by the classification and statistics of different filling types laterally, and the relationships between oil and gas production and the reservoir filling degree and between oil and gas migration channels are analyzed. Hydrothermal action has the strongest ability to transform reservoirs, mainly due to hydrothermal dissolution and fault zones transporting oil and gas; the yield of caves filled with sinkholes is relatively low, which is related to the good reservoir space retained by oil and gas filling and the migration channels provided by fault zones. The yield of the underground river filling type is lower than that of the water-falling cave filling type, mainly because the underground river filling type is located in the karst slope and lower part of the basin. The water energy in the karst slope is relatively strong, and the interior of the cave is filled with medium-fine sandstone. In the lower part of the karst zone, the water energy becomes weak; both of these conditions lead to further filling of the cave reservoir space and a lack of migration channels. The collapse filling type has the strongest impact on the reservoir because this discussion is mainly about late collapse, which causes the cave to collapse, and the internal filling is severe; even if a fault zone acts as a migration channel, oil and gas production is relatively low.

Pouring and Curing for Sample Preparation Technology for the Analysis of the Silicon-Aluminum Ratio of Molecular Sieves by Energy Dispersive X-Ray Fluorescence (EDXRF)

The silicon-aluminum ratio of the molecular sieves is a crucial control index for the quality of synthetic molecular sieves. Here a fast, simple and reliable sample preparation method, referred to as pouring and curing method, is described for determining the silicon-aluminum ratio of high silicon molecular sieves by energy dispersive x-ray fluorescence (EDXRF). Resin is used as the carrier with the addition of a curing agent, so that the sample powder is embedded in the resin matrix. By measuring sixteen random positions of the same cured sample, the homogeneity of the sample was evaluated to ensure the stability of the results. A double logarithmic calibration curve of the analysis line ratio and the corresponding concentration ratio of silicon and aluminum was established according to the binary ratio method. The results by EDXRF and inductively coupled plasma-optical emission spectrometer (ICP-OES) were compared with a relative standard error from 2.934 to 6.777%. The good precision shows that the pouring and curing method is a suitable for measuring the silicon-aluminum ratio of molecular sieves.

Novel closed-loop control system of dual rotary blood pumps in total artificial heart based on the circulatory equilibrium framework: a proof-of-concept in vivo study.

Total artificial heart (TAH) using dual rotary blood pumps (RBPs) is a potential treatment for end-stage heart failure. A well-noted challenge with RBPs is their low sensitivity to preload, which can lead to venous congestion and ventricular suction. To address this issue, we have developed an innovative closed-loop control system of dual RBPs in TAH. This system emulates the Frank-Starling law of the heart in controlling RBPs while monitoring stressed blood volume (V) based on the circulatory equilibrium framework. We validated the system in in-vivo experiments. In 9 anesthetized dogs, we prepared a TAH circuit using 2 centrifugal-type RBPs. We first investigated whether the flow and inlet atrial pressure in each RBP adhered to a logarithmic Frank-Starling curve. We then examined whether the RBP flows and atrial pressures were maintained stably during aortic occlusion (AO) and pulmonary cannula stenosis (PS), whether averaged flow of dual RBPs and bilateral atrial pressures were controlled to their predefined target values for a specific V, and whether this system could maintain the atrial pressures within predefined control ranges under significant changes in V. This system effectively emulated the logarithmic Frank-Starling curve. It robustly stabilized the flow and atrial pressures during AO and PS without venous congestion or ventricular suction, accurately achieved target values in averaged flow and atrial pressures, and efficaciously maintained these pressures within the control ranges. This system controls dual RBPs in TAH accurately and stably. This system may accelerate clinical application of TAH with dual RBPs.

Golden Ratio Flap Designed Using the Golden Ratio Rectangle.

Rotation flaps are arcuate repairs that redistribute tension vectors and recruit adjacent and/or distant tissue laxity. The incision curve could be a logarithmic spiral curve to reduce the length of an incision. We propose a rotation flap-the golden ratio flap-designed using a golden rectangle. The flap incision is an arc though the major square which is beside the minor square of a golden rectangle. The defect is attached to the line of another minor square and diagonal to the major square. The bottom line runs from the incision end to the tangent point of the circle or the oval, and the perpendicular height line runs from the bottom line to the cross point of the flap incision. These parameters were analyzed retrospectively for four superficial sarcomas that were treated using a rotation flap with an incision approximating the logarithmic spiral curve. The ratio of height to bottom of the golden ratio flap design was highly similar to the preoperative flap design in the four cases assessed. With the new design, the ratio of bottom to the defect diameter (minor axis in the oval defect) was 1.3, and for the height, it was 1.4. The golden ratio flap, designed using the golden rectangle, is reproducible. The parameters of height and bottom approximate the flap shape, or the length and width, respectively. For clinical applications, step-by-step guidance for drawing the new flap are also proposed.

Interactive Forward and Inversion Scheme‐Based Anisotropic Correction for Shale Gas Horizontal Well Sonic Logs and Its Application

Well logging interpretation and evaluation of reservoirs in horizontal wells plays an important role in shale gas exploration and development. The accuracy of the interpreted petrophysical parameters is directly affected by well logging curves. This study focuses on a horizontal well targeting deep shale gas layers in the Luzhou block, Southern Sichuan Basin. It employs an interactive forward and inversion scheme to precisely reconstruct the borehole trajectory using a comprehensive dataset encompassing well logs, mud logs, and seismic data. The research introduces a method for anisotropic correction of sonic log, crucial for calculating reservoir parameters, and assess payzone targeting in the horizontal well. The research results show that the interactive forward and inverse simulation method can achieve the recovery of horizontal well borehole trajectory and finely delineate the sublayers, improving the evaluation accuracy of platinum target drilling encounter ratio by over 6%. Numerically simulated acoustic wave can be used to carry out the anisotropy correction of acoustic wave in horizontal wells and calculate reservoir parameters, reducing the relative error in computed porosity to 1.72%. The comprehensive logging evaluation results from both geological and engineering aspects provide the data basis for planning the fracturing program of the shale gas horizontal well. This research has established a new method and idea for well logging evaluation in shale gas horizontal wells, marking a significant step toward integrating geological and engineering aspects in shale gas exploration.

Evaluation of integrated geological engineering reservoir reconstruction in Block X of Bozi

The geological structure of the reservoir in Bozi-Dabei area is complex, and the longitudinal difference of rock mechanical properties of the reservoir is large. Most of the current evaluation techniques after reservoir reconstruction are based on the fitting of construction pressure based on the logging curve of a single well, so as to analyze the fracture morphology and the geometric dimensions of length, width and height after pressure. It is difficult to explain the fracture morphology and geometric parameters correctly because the interpretation methods used do not comprehensively consider the influence of natural fractures, 3D geological properties and 3D geomechanical properties. In order to explain the artificial fracture morphology more accurately, the target layer ant body is generated by using 3D original seismic data, and the natural fracture model of three different reservoir types in Bozi X block is generated, which provides geological basis for the integrated demonstration. By combining dynamic and static data and multidisciplinary methods, a one-dimensional rock mechanics profile model is established, and a three-dimensional geomechanical model of three different reservoir types in Block X of Bozi is established by combining geological model and deep diagenesis theory. The matching relationship between horizontal stress, fault strike and natural tensile fracture distribution is comprehensively analyzed and evaluated, providing a geomechanical basis for the evaluation of integrated reservoir reconstruction. Integrated geological model and geomechanical model are closely combined with engineering parameters to establish an integrated true three-dimensional artificial fracture model. On this basis, the optimization research and design of the parameters of displacement, liquid volume and sand ratio are completed. The optimal flow rate of Class I reservoir 6-7 (m³·min-1), Class II reservoir 5-6 (m³·min-1), Class III reservoir 4-5 (m³·min-1), Class I reservoir 600-700 m³, Class II reservoir 600-700 m³, Class III reservoir 500-600 m³, Sand ratio of 15%-20% for Class I reservoir, 15%-20% for class II reservoir and 20%-25% for class III reservoir are the optimal construction parameters, which provide guidance for field construction.

Fluid classification through well logging is conducted using the extreme gradient boosting model based on the adaptive piecewise flatness-based fast transform feature extraction algorithm

In recent years, fluid prediction through well logging has assumed a pivotal role in the realm of oil and gas exploration. Seeking to enhance prediction accuracy, this paper introduces an adaptive piecewise flatness-based fast transform (APFFT) algorithm in conjunction with the XGBoost (extreme gradient boosting) method for logging fluid prediction. Initially, the APFFT technology is employed to extract frequency-domain features from the logging data. This algorithm dynamically determines the optimal frequency interval, transforming raw logging curves into frequency domain data. This adaptive process enhances the preservation of frequency domain information reflective of fluid characteristics, simultaneously minimizing the impact of noise and non-fluid compositions. Subsequently, the acquired frequency domain features are utilized as inputs to construct an XGBoost model for fluid prediction. To validate the efficacy of this proposed approach, real logging data were collected, and an extensive experimental evaluation was conducted. The experimental findings underscore the substantial advantages of the APFFT-XGBoost method over traditional machine learning models such as XGBoost, random forest, K-nearest neighbor algorithm, support vector machine, and backpropagation neural network in logging fluid prediction. The proposed method demonstrates the ability to accurately capture fluid features, leading to improved prediction accuracy and stability.

Study of vertical electrical resistance changes in reservoir beds of Tournaisian oil deposits

The article proposes a method for rapid assessment of the initial position of oil-water contacts, oxidized oil zones, transition zones, zones of high and decreasing resistance in the Lower Carboniferous Tournaisian oil deposits at one of the oilfields of the Republic of Tatarstan. As initial data, the values of electrical resistivity of effective interlayers from the catalog of geological and geophysical data, determined from induction logging curves, were used. Well log data for more than 200 wells drilled in elevation areas were used in analysis. The change in the electrical properties of deposits vertically is considered using the average resistivity values of effective interlayers averaged over all wells. Conclusions are based on the results of the done work: according to the resistivity values in massive carbonate deposits of the Tournaisian age, it is possible to distinguish various zones of oil saturation along the vertical; initial oil saturation does not grow exponentially, as in the Leverett function, but linearly in each zone.

Quantitative Evaluation of Paleocene Reservoir Diagenetic Facies by Logging in Lishui West Sag, East China Sea Basin

Exploration in the Lishui West Sag of the East China Sea Basin is limited by the scarcity of offshore drilling sites, and the prediction of deep, high-quality reservoirs is challenging using only geophysical methods. This study introduces a quantitative approach to diagenetic facies division in individual wells based on logging data, providing a new method and perspective for the prediction of deep, high-quality reservoirs. We employed comprehensive data from core, logging, thin-section casting, cathodoluminescence, scanning electron microscopy, and X-ray diffraction analyses from five wells to study the petrology, physical properties, diagenetic types and strength, and diagenetic minerals of the Paleocene sandstone reservoirs in the Lishui West Sag. Apparent compaction rate, apparent cementation rate, and other quantitative characterization parameters were used to calculate the comprehensive diagenetic coefficient (Cg), and the diagenetic facies were divided into compaction, cementation, and dissolution facies. A logging calculation model for the comprehensive diagenetic coefficient (Cg) and a quantitative identification method for diagenetic facies in individual well reservoirs were established through a fitting analysis between Cg and logging curve parameters. Continuous quantitative identification of vertical diagenetic facies in the five wells in the study area showed that the high-quality reservoirs in wells L1, L2, and L3 within the L1 gas field are characterized by extensive development of dissolution facies, while wells L4 and L5 are dominated by compaction and cementation facies, with poor reservoir properties and no industrial gas flow output. The results demonstrate the reliability of the model method. The establishment of this quantitative characterization method for diagenetic facies using logging data provides guidance for the prediction of favorable reservoirs.

The Formation Mechanism of Abnormal Overpressure in Depositional Basins and Its Controlling Effect on Hydrocarbon Accumulation

Abnormal overpressure is commonly encountered in depositional basins and is considered a key factor influencing the efficiency, safety, and assessment of hydrocarbon accumulation dynamics in drilling projects. Research indicates the following: (1)The genesis of abnormal overpressure in depositional basins can be broadly classified into five types, including disequilibrium compaction, fluid expansion, diagenesis, tectonic squeezing, and pressure transmission;(2) For specific geological conditions in depositional basins, the mudstone logging curve chart method is employed to assess abnormal overpressure;(3) The impact of abnormal overpressure in depositional basins on hydrocarbon accumulation is manifested in four aspects: its influence on hydrocarbon generation from source rocks, its effect on reservoir connectivity, its impact on seal integrity of cap rocks, and its influence on hydrocarbon migration. These research findings provide crucial guidance for a deeper understanding of abnormal overpressure in depositional basins and its significance in the evaluation of hydrocarbon exploration.

Comparison of measured versus modeled TOC in the Tuscaloosa marine shale of Southwestern Mississippi, U.S.A.

This study presents a comparison of measured versus modeled total organic carbon (TOC) in the Upper Cretaceous Tuscaloosa marine shale (TMS) of southwestern Mississippi as a case study to evaluate the effects of mineralogy on the TOC estimated from the ΔlogR method. The ΔlogR method is utilized to calculate TOC, which involves baselining sonic transit time and resistivity log curves in a non-source rock section of the formation. In our application, the well log curves were baselined in the upper TMS, which is described as a non-source rock section, and in the lower TMS above the high resistivity zone (HRZ), which is described as having a higher carbonate content. The ΔlogR calculated TOC values from these two baselining approaches show that the lower baseline results in improved agreement between measured TOC and calculated TOC. This improvement is likely to be due to the lower baseline accounting for the increase in resistivity caused by higher carbonate content, in addition to any presence of TOC. The upper baseline, which has a lower carbonate content, does not account for this resistivity increase. Additionally, sample type appears to affect the comparison of measured and ΔlogR calculated TOC. Most of the samples used in this study are legacy cuttings that were not preserved during storage, exposing the high surface area cuttings to increased rates of oxidation, whereas geophysical logs record the rock properties in situ. To account for this oxidation effect, the difference between the medians of the TMS HRZ TOC core and cuttings values was added to each TOC measurement in this study, resulting in a median measured TOC value that is similar to the median of the lower TMS-baselined ΔlogR calculated TOC value. Overall, this study demonstrates that carbonate content and sample type can affect how well measured and ΔlogR-modeled TOC values compare.

Fracture identification and characteristics of carbonate underground gas storage: an example from the eastern area of Sulige gas field, ordos Basin, China

The carbonate rock formations have obvious dual media characteristics, fracture development and good physical conditions, which are the main seepage channels and storage spaces for gas after the reconstruction of underground gas storage. The carbonate strata of the Ordovician system are important natural gas reservoirs in the eastern area of Sulige Gas Field in the Ordos Basin, and the identification and characterization of their fractures are of great significance for the modeling of fractures in the later stage and the improvement of the operation scheme of the gas storage. At present, there is little research on fractures, which restricts exploration and development. Therefore, taking the 39–61 gas storage reservoir in the eastern area of Sulige Gas Field in the Ordos Basin as the research object, this paper identifies and studies the characteristics of the fractures by core, microscopic, conventional logging curves, and imaging logging identification. The results show that the fracture length ranges from 5 to 15 cm and the width ranges from 0.1 to 3 mm. The fracture angles are mostly between 75° and 90° and the main direction is NW–SE. In conventional logging curves, porosity logging has a good response to fractures, while resistivity logging has a general response to fractures; In layers with more developed fractures, natural gamma values are mostly higher than 40API, rock volume density is less than 2.8 g/cm3, neutron porosity is greater than 12.5%, and acoustic time difference is greater than 160 μ s/m. This study is of great significance for improving the identification of carbonate fractures, enriching the relevant theories, and providing guidance for the construction of carbonate gas storage.