Shale oil development in China is still at an early stage, with limited sample size and highly nonlinear relationships between production and multiple geological and engineering parameters. Under these conditions, quantifying parameter sensitivity, elucidating their mechanisms of influence on production, and integrating sensitive parameter combinations to achieve accurate sweet spot prediction have become critical issues in shale oil exploration and development. To address this, a Variance-Adaptive Random Forest (VA-RF) method is proposed, in which node-splitting strategies are dynamically adjusted based on variance. This approach balances decision tree correlation and strength in small-sample scenarios, thereby reducing generalization error and improving prediction accuracy. Experimental results show that VA-RF reduces prediction error by 13.8

By 2024, the proven natural gas reserves of the Maokou Formation in the central Sichuan Basin had exceeded 1.5×1011 m3, suggesting great potential for hydrocarbon exploration. However, this formation exhibits small reservoir thicknesses and pronounced lateral heterogeneity due to sedimentation and erosion. These characteristics lead to significantly varying single-well production, complicating the identification of major controlling factors in high production and reducing the prediction accuracy of sweet spots. To identify the key geological factors controlling the gas production in the Maokou Formation, this study investigated the geological and seismic characteristics of the dolomite reservoirs in this formation. The primary geological factors influencing single-well production were explored using a machine learning approach—an enhanced random forest (RF) prediction model based on Shapley additive explanations (SHAP) values (also referred to as the SHAP-enhanced RF model). Accordingly, an optimal combination of geological parameters for high production was determined, followed by the identification of sweet spots. The results demonstrate that the SHAP-enhanced RF model allows for the effective quantification of the relative importance of various factors. The most critical factors affecting the gas production in the Maokou Formation include burial depth, natural gamma-ray value, the spatial distance of bright spots (defined as the time thickness of bright spots relative to the base of the second member of the Maokou Formation), and paleogeomorphology. High-yielding wells typically feature a joint advantage of multiple critical factors. A strong synergistic effect is prone to occur when several optimal factors fall within their optimal ranges simultaneously. In this case, high production capacity might be achieved. Compared to an equal-weight RF model, the SHAP-enhanced RF model yielded a mean absolute error (MAE) decreasing by 18.6%, thereby enhancing prediction accuracy and reliability. The findings of this study can serve as a valuable guide for production planning and well placement optimization in the Maokou Formation.

The Jurassic Lianggaoshan Formation in eastern Sichuan Basin is a key target for shale oil exploration.It faces challenges in three-pressure prediction due to complex structural and sedimentary interactions,as well as strong reservoir anisotropy.These issues often lead to wellbore instability and gas logging anomalies during drilling.This study presents an integrated workflow that combines residual moveout correction using correlation-based dynamic time warping(CDTW),high-resolution seismic waveform indication inversion,and three-pressure prediction of jointing well-seismic data.Applied to the LT1 well block,the workflow effectively corrects anisotropic residual moveout in image gathers,leading to a signal strength increase of over 10％in frequency bands above 30 Hz and enhancing event continuity.High-resolution rock mechanical parameters are obtained through seismic waveform inversion and regional calibration,enabling the prediction of three-dimensional pore pressure,collapse pressure and fracture pressure.The results are consistent with actual drilling gas shows and core data,confirming the method's accuracy and supporting mud weight planning and wellbore stability efforts.This cost-effective and technically robust approach proves highly reliable in complex environments with significant heterogeneity and anisotropy,assisting drilling decisions and risk management in eastern Sichuan and similar challenging geological settings.

In the central Sichuan area, shallow continental clastic strata and deep marine carbonate formations are vertically developed. The mechanisms that generate abnormal pressure differ between these two types of strata, and the overall heterogeneity is strong. Conventional empirical pore-pressure prediction methods are markedly inadequate in deep carbonate rocks, exhibit poor universality, and fail to achieve accurate prediction over the entire well section. Therefore, using logging, geological and well-test data from the study area, this paper compares the Eaton, effective‑stress and Fillippone methods for pore-pressure prediction. The results indicate that both the Eaton and effective‑stress methods are based on the normal compaction trend line and yield relatively large prediction errors in deep carbonate formations, whereas the Fillippone method performs best. On this basis, the paper further modifies the Fillippone method by adjusting the velocity‑ratio relationship so that the velocity response in abnormally high‑pressure intervals changes from “attenuated feedback” to “compensatory uplift”. The research results demonstrate that the proposed method achieves higher prediction accuracy, and the predicted pressure coefficients agree well with fracture and electrical image data, making it more suitable for pore‑pressure prediction in deep carbonate formations and capable of effectively supporting rapid and efficient drilling operations.

The Changxing Formation in the central Sichuan Basin developed on a central isolated gentle-slope platform, where multiple rows of high-energy reef-shoal bodies occur. In some local areas, dolomitized reservoirs are well developed, indicating significant exploration potential. However, strong reservoir heterogeneity and the pronounced characteristic of “one reef, one reservoir” have resulted in challenges such as unclear delineation of internal reservoir boundaries and ambiguous seismic response characteristics. Therefore, further refined delineation of reef-shoal body boundaries are required. Based on geological and logging data, the petrological and seismic response characteristics of reef-shoal reservoirs in the Changxing Formation were first clarified. Combined with the results of forward modeling, a seismic identification model for reef-shoal reservoirs was then established. Subsequently, by integrating paleogeomorphic restoration, seismic attribute analysis, and related techniques, a method for delineating internal boundaries—namely, the Three-Determination Method—was proposed. Finally, through the combined application of seismic inversion, seismic facies analysis, and related techniques, the vertical and lateral distribution characteristics of reef-shoal reservoirs were defined. The results indicate that, vertically, reef-shoal reservoirs in the study area are mainly developed in the Chang 1 Member and the middle-upper part of the Chang 2 Member, with thicknesses ranging from 10 to 60 m. Laterally, they are primarily distributed along the platform margin and at local paleogeomorphic highs within the platform, and the characteristic of “one reef, one reservoir” is evident. Reef-shoal bodies in the platform-margin zone, characterized by clear seismic response patterns and relatively large individual extents, still exhibit considerable exploration potential.

With the continued expansion of oil and gas exploration, both in the eastern and western regions, the quality of seismic acquisition has become a key factor in oil and gas exploration in complex areas. However, conventional seismic acquisition methods cannot efficiently avoid challenging acquisition locations and produce high-quality seismic data. In this regard, based on the curvelet transform, this paper proposes an irregular seismic acquisition method, which utilizes the high-precision characteristics of the curvelet transform and simulated annealing algorithm to establish a method for the evaluation of the coherence of irregular sampling matrices and design of observation systems. The method was verified using forward simulation and actual acquisition data. The results suggest the superior quality of seismic data gathered in complicated areas through this method over those acquired using traditional methods, which can provide technical guidance for the design of observation systems in complex areas.

How to effectively remove blending noise is the key to the success of simultaneous source acquisition. The traditional deblending of 3D simultaneous source data is based on the energy difference between blending noise and useful signals in the sparse domain, and remove blending noise independently from each 2D partition of 3D simultaneous source data using sparse inversion algorithm. However, this 3D deblending techniques do not fully utilize a priori information derived from the locations of the spares coefficients from different partitions, especially when highly redundant curvelet domain sparsity is used. In this paper, we propose to use the priori support information to improve the deblending performance of 3D simultaneous source data by using 2D curvelet transform. Firstly, Based on the correlations between the support sets of the significant curvelet coefficients of adjacent partitions, a weighted operator is constructed in the curvelet domain using the prior support sets provided by the previous partition that has removed blending noise. Then incorporate it into the iterative shrinkage thresholding algorithm to delineate the main energy distribution range of the useful signals, and define a sequence of 2D curvelet-based deblending problems that exploit 3D correlations exhibited by seismic wavefields without using the highly redundant 3D curvelet transform. To test the performance of our proposed method, we compared deblending from synthetic and field artificially blended data. These examples demonstrated that our method is superior to the traditional iterative algorithm in terms of deblending performance, and computational memory requirements.

With the high yield of many wells represented by Well JT1 in the Maokou Formation, has catalyzed a surge in exploration activities along the platform margin facies of the Maokou Formation in central Sichuan and further showed the significant exploration potential of the Maokou Formation in the northern slope. However, the fracture cave body of the Maokou Formation exhibits a high degree of development, strong longitudinal and horizontal heterogeneity, large formation pressure differences, and drilling events such as gas kicks and lost circulation occur frequently, which seriously affects the efficient implementation of drilling. Understanding the spatial distribution of the three-pressure in the formation can help better deal with and solve the above problems. Therefore, in order to help the safe, high-quality and rapid drilling of the Maokou Formation in the study area, and enhance the efficiency of oil and gas development, this paper explores the research on the prediction method of the three-pressure of jointing well-seismic data based on the geomechanical experimental data and the actual drilling data. In the process of prediction of pore pressure, this study found that the pore pressure and formation velocity in the study area have an exponential relationship. In order to enhance the applicability of the Filippone's method in the study area and improve the prediction accuracy of pore pressure, the linear relationship between pore pressure and formation velocity in the Filippone's method is modified to an exponential relationship, and a pore pressure prediction model suitable for the work area was established. Based on the Mohr-Coulomb criterion and Huang's model, the prediction models of collapse pressure and fracture pressure applicable to the study area were established, respectively. Then, the elastic parameters were obtained through pre-stack inversion, and the three-pressure bodies were calculated based on the elastic parameter bodies. The results indicate that: (1) The three-pressure prediction method of the jointing well-seismic data in this paper can predict the formation's longitudinal and transverse pressure anomaly zones in advance. (2) The Maokou Formation in the study area is characterized by abnormally high pressure, to balance the pressure of the high-ground formation, high-density drilling fluid is necessary. (3) The prediction results of three-pressure in this paper are highly consistent with the actual drilling engineering events, which verifies the reliability of the three-pressure prediction results presented in this study. The results of the study can provide a basis for decision-making in drilling geological design, such as the determination of drilling fluid density, the evaluation of borehole stability and other engineering problems that require support from three-pressure data.

This research aims to address the ambiguity surrounding the extent of development of Changxing Formation bio-reef reservoirs in the Longhuichang-Tieshan area of the northeastern Sichuan Basin, China, and to elucidate the relationship between these reservoirs and gas distribution. Utilizing drilling and logging data, this study provides a comprehensive summary of the seismic geological characteristics of bio-reef reservoirs. Furthermore, it investigates the effects of reservoir parameters, structural location, and strike-slip faults on the development of bio-reef gas reservoirs. The research shows that bio-reef reservoirs in the area predominantly manifest vertical development in the middle and upper parts of the Changxing Formation, with horizontal expansion occurring along the platform margin and local highland areas. Notably, potential exploration areas are identified, particularly the western wing of the Longhuichang structure and the southwestern side of the Tieshannan structure. By comparing and analyzing the relationship between bio-reef gas reservoirs in the study area, the study aims to clarify the controlling effects of reservoir parameters, structural location, strike-slip faults, and other pertinent factors on the development of bio-reef gas reservoirs. It is observed that while these factors do not exhibit a clear strong linear relationship, they have a comprehensive effect on the development of gas reservoirs. The enrichment mode and failure mode of favorable gas reservoirs in the study area have been analyzed and established, providing crucial technical support to facilitate further exploration of Changxing Formation bio-reef gas reservoirs in the northeastern Sichuan Basin.

The glutenite reservoir in an exploration area in eastern China is well-developed and holds significant exploration potential as an important oil and gas alternative layer. However, due to the influence of sedimentary characteristics, the glutenite reservoir exhibits strong lateral heterogeneity, significant vertical thickness variations, and low accuracy in reservoir space characterization, which affects the reasonable and effective deployment of development wells. Seismic data contains the three-dimensional spatial characteristics of geological bodies, but how to design a suitable transfer function to extract the nonlinear relationship between seismic data and reservoirs is crucial. At present, the transfer functions are concentrated in low-dimensional or high-dimensional fixed mathematical models, which cannot accurately describe the nonlinear relationship between seismic data and complex reservoirs, resulting in low spatial description accuracy of complex reservoirs. In this regard, this paper first utilizes a fusion method based on probability kernel to fuse seismic attributes such as wave impedance, effective bandwidth, and composite envelope difference. This provide a more intuitive reflection of the distribution characteristics of glutenite reservoirs. Moreover, a hybrid nonlinear transfer function is established to transform the fused attribute cube into an opaque attribute cube. Finally, the illumination model and ray casting method are used to perform voxel imaging of the glutenite reservoirs, brighten the detailed characteristics of reservoir space, and then form a set of methods for ' brightening reservoirs and darkening non-reservoirs ', which improves the spatial engraving accuracy of glutenite reservoirs.

Traditional seismic data sampling must strictly follow the Nyquist sampling theorem,and actual field data acquisition may not be able to record the complete seismic wave field due to construction conditions or obstacles on the ground. Therefore,data reconstruction in seismic data processing is an important factor. problem. Compressed sensing theory originates from the field of signal processing. It includes sparse representation of signals and mathematical combination optimization problems. It provides a new solution for the reconstruction of seismic data. And how to choose the optimal iterative algorithm is the key issue in data reconstruction. This paper summarizes the seismic data interpolation problem into a constrained optimization problem, chooses Fourier transform,which can effectively represent the seismic wave field sparsely, and then applies the Bregman iterative method to solve the mixed norm inverse problem under the framework of compressed sensing theory. In the reconstruction process, for the disadvantage of slow convergence of traditional threshold parameters, the threshold parameters of the improved exponential decay law are summarized. In order to reduce the number of iterations and improve the accuracy of seismic data reconstruction,the hard threshold operator is selected to perform the two-dimensional seismic data. Rebuild and restore. The processing results of theoretical model and actual seismic data show that this method can quickly and effectively restore the missing data of seismic wave field.

川东北龙会场—龙门地区位于茅口组沉积高能相带及古地貌有利部位,具备形成相控和岩溶储层的条件,区内钻遇茅口组的井常见良好的油气显示,具有较大的勘探潜力.但茅口组储层非均质性强,厚度薄,展布规律不清,地震响应特征不明显,导致一直未能形成行之有效的储层地震识别模式.针对以上问题,综合利用地震和地质资料,从储层单井特征研究出发,结合正演模拟挖掘储层地震响应特征,建立茅口组储层地震预测模式.重点分析了古地貌、高角度和低角度断层对储层发育的影响,建立了川东北地区茅口组储层综合地震识别模式.研究认为,高能沉积的颗粒滩相及岩溶古地貌是茅口组储层形成的关键因素,低角度和高角度断层进一步改造储层,高角度断层是沟通志留系和奥陶系烃源岩的纽带.因此,有利相带、古地貌高部位以及高、低角度断层发育区为勘探的最有利区,满足此识别模式的广大向斜区同样具有较大的勘探潜力.

High-quality seismic data is key to determining the success or failure of oil and gas exploration in complex mountain fronts. Observation systems are important factors affecting the quality of the seismic collection. Currently, the seismic collection design of piedmont zones is mainly based on optimizing and analyzing a single collection parameter. The multiparameter optimization is not performed as a whole. Moreover, the collection parameters that significantly impact the imaging quality of piedmont zones are not deeply excavated. This paper first uses the relationship between the acquisition parameters and the signal-to-noise ratio of a previous seismic data analysis to solve this problem and then obtains the prestack offset profiles of different acquisition parameters through forward modeling and prestack offset methods, further analyzes the acquisition parameters that have a more significant impact on imaging quality, uses the degenerative treatment method to process and analyze the newly collected seismic data, and delves into the most sensitive acquisition parameters for imaging quality. The results show that the influence of the gun line distance is the largest, and the influence of the receiving line distance, the number of receiving lines, and the number of receiving channels is reduced. Therefore, the effect of each acquisition parameter on the imaging quality is different, and different acquisition parameters should be selected according to the depth of the target layer.

Abstract With the deepening of the exploration of complex hidden oil and gas reservoirs, the spatial characterization of complex reservoir bodies determines the deployment of development wells, and seismic data contains the three-dimensional spatial characteristics of geological bodies and plays an important role in the spatial characterization of reservoirs, among which designing appropriate transfer functions to express the nonlinear relationship between seismic data and reservoirs is the key to solving the problem. At present, the transfer functions are concentrated in low-dimensional functions or high-dimensional functions of fixed mathematical models, which cannot accurately depict the nonlinear mapping relationship between seismic data and complex reservoirs, resulting in low spatial description accuracy of reservoirs. In this paper, the hybrid nonlinear transfer function is established to convert the seismic volume fusion attribute into the light blockers attribute, and then the emission model and light projection method are used to render the reservoir volume, so as to achieve the purpose of illuminating the reservoir and shielding the non-reservoir, and improve the depiction accuracy of the three-dimensional spatial characteristics of the reservoir.

ST9井测试获气进一步展示了川西复杂构造带二叠系具有较大的勘探潜力,但由于龙门山推覆构造地层破碎,地震波场畸变,地震数据品质低,难以满足后续地震地质解释研究的需求,因此如何提高该区地震数据采集及成像质量尤为重要.针对这一问题,以HX1井区资料为基础,建立地质模型,从地下目的层成像角度优选采集参数,总结分析川西复杂构造带不同激发区域地震波场特征差异,利用照明能量优化采集参数和激发区域,深入分析对成像质量最为敏感的采集参数,分区域提出观测系统建议方案,研究认为炮点距(或炮线距)对成像质量的改善最为敏感,龙门山构造主体应进行局部加密炮点距(或炮线距),而盆地内激发效果好,但对改善龙门山主体构造的成像质量作用不大,可以降低炮点密度,从而通过有目标的疏密炮点设计方法,经济高效地提高研究区主体构造成像质量.

The high-yield reservoir test of the second member of the Dengying Formation in the Zhongjiang-Penglai area shows great exploration potential. Due to the dual effects of sedimentation and dissolution， the reservoir heterogeneity is strong and the gas-water relationship is complex. In addition to the development of dense zones in the horizontal direction， there are also dense area barriers in the vertical direction， forming multiple independent gas reservoirs with different gas-water interfaces. In this regard， based on the seismic geological characteristics of drilled wells， this paper intends to establish the seismic identification model of Dengying reservoir and dense area， and then deeply analyze the sedimentary evolution process of paleogeomorphology in the upper sub-member of Dengying Formation， finely characterize lithologic traps， and clarify the spatial distribution law of effective reservoirs. The study shows that the high-quality reservoir of the hilly-Shoal reservior is developed in the second member of 2 layers of the upper sub-member of Deng 2， with a thickness of 30-110 m. Laterally， it is developed in the high landform area near the platform margin， showing a continuous distribution characteristics. The dense area develops in the low part of paleogeomorphology， and has a good coupling relationship with rift of Sinian System， which has a shielding effect on gas reservoir. The practice shows that the understanding in this paper is highly consistent with the actual drilling， which can provide technical support for the exploration of Dengying Formation gas reservoir in the northern slope.

Oil and gas seismic exploration have to adopt irregular seismic acquisition due to the increasingly complex exploration conditions to adapt to complex geological conditions and environments. However, the irregular seismic acquisition is accompanied by the lack of acquisition data, which requires high-precision regularization. The sparse signal feature in the transform domain in compressed sensing theory is used in this paper to recover the missing signal, involving sparse transform base optimization and threshold modeling. First, this paper analyzes and compares the effects of six sparse transformation bases on the reconstruction accuracy and efficiency of irregular seismic data and establishes the quantitative relationship between sparse transformation and reconstruction accuracy and efficiency. Second, an adaptive threshold modeling method based on sparse coefficient is provided to improve the reconstruction accuracy. Test results show that the method has good adaptability to different seismic data and sparse transform bases. The f-x domain reconstruction method of effective frequency samples is studied to address the problem of low computational efficiency. The parallel computing strategy of curvelet transform combined with OpenMP is further proposed, which substantially improves the computational efficiency under the premise of ensuring the reconstruction accuracy. Finally, the actual acquisition data are used to verify the proposed method. The results indicate that the proposed method strategy can solve the regularization problem of irregular seismic data in production and improve the imaging quality of the target layer economically and efficiently.

近年来随着国家油气需求进一步增加,致密储层逐渐成为研究热点,川东地区凉高山组是典型的致密砂岩储层,具有层系多、河道规模大、砂体厚、生储组合好和烃源丰富等优点,具有较好的勘探前景,但也存在储层岩性致密、孔渗低、勘探程度低等难题.针对这些问题,从地震地质资料入手,详细分析凉高山组纵横向砂岩储层地震地质特征.研究发现:优势砂体发育在凉高山组中上部,中下部烃源岩发育好,水下分流河道及河口坝为主要储集体,河道宽度大,河道沙坝呈块状非连续性分布,油气保存条件较好.储层甜点区受相带控制特征明显,远离通天断层的向斜区、河道中沙坝、裂缝发育区为最有利的勘探区域.

中国东部油田普遍存在断裂复杂、砂泥岩互层严重以及河道砂体间错落重叠等地质特征.由于地震纵向分辨率的限制,因而无法可靠识别低序级小断层和砂体重叠带,这对于油田开发方案的部署与调整影响很大.针对这一难题,设计了一个包含不同断距的断层和不同叠置范围及落差的重叠河道砂体模型,正演结果表明:小于调谐厚度的砂体重叠带在地震剖面上会形成"伪断层"响应,即与小断层类似的地震同相轴的扭曲或错断.但通过地震多属性的综合分析,发现了地震振幅类属性和地震波形结构类属性对小断层与砂体重叠带有不同的响应特征,结合常规的均方根振幅属性和波形变异系数属性,建立了两条识别准则:①均方根振幅与波形变异系数同时为低值突变可以识别断层存在;②均方根振幅为低值突变而波形变异系数为高值突变则可以识别砂体重叠带.胜利探区W102断块S23储层的地震资料应用结果表明,小断层发育区和薄砂体重叠带的均方根振幅和波形变异系数属性的异常特征与这两条识别准则基本一致,可用于识别与区分薄互层砂岩储层中的小断层与砂体重叠带,为该探区开发方案的调整部署提供了参考依据.

四川盆地二叠系火山岩具有良好的勘探前景,而盆地东部地区多口钻井显示钻遇火山岩,但都没有展开相应的研究.基于测录井及地震等资料分析,对四川盆地东部龙会场-龙门地区二叠系火山岩识别模式及分布特征进行综合研究.结果表明:在地震剖面上,当龙潭组内部多形成一个波峰反射时,代表着火山岩发育;区内火山岩以溢流相玄武岩为主,少见凝灰岩;垂向上可划分为2个喷发期次,主要发育在龙潭组中下部;平面上火山岩分布受古地貌和基底断裂共同控制,在古地貌低洼处和基底断裂附近是火山岩主要堆积部位,厚度较大.