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Sedimentary Characteristics and reservoir prediction of Paleogene in the East Part of Kuqa Foreland Basin

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Journal of China University of Geosciences 2006年第2期17卷 138-145,157页

作者：严德天王华王家豪王清晨 Laboratoryof Lithosphere Tectonic Evolution Institute of Geology and Geophysics Chinese Academy of Sciences Faculty of Earth Resources China University of Geosciences Laboratory of Lithosphere Tectonic Evolution Institute of Geology and Geophysics Chinese Academy of Sciences

Most of the Mesozoic and Cenozoic large-scale hydrocarbon-bearing basins in western China were formed in a similar foreland setting. Hydrocarbon exploration of the Kuqa foreland basin requires research into the sedimentary characteristics and filling evolution of the depositional sequences and their response to the basin process. Based on an analysis of outcrops, well logs and high resolution seismic data, the sedimentary system types and distribution characteristics of the Paleogene in the east part of Kuqa foreland basin were systematically studied. The results show that：（ 1 ） Three types of sedimentary systems are developed in the area： an oxidative salty wide shallow lacustrine system, a fan delta system and an evaporitic bordersea system. （2） The configuration and evolution of the depositional systems of the Paleogene in the Kuqa foreland basin were predominantly determined by foreland tectonism. Vertically, the Paleogene sedimentary sequence can be divided into three parts： the lower, middle and upper depositional system tracts. The lower and upper tracts commonly consist of progradational or aggradational sequences, while the middle part is usually comprised of a set of aggradational to transgressive third-order sequences. Laterally, the sedimentary systems in the east part of the Kuqa foreland basin spread from east to west as a whole, and the sedimentary facies obviously vary from south to north. The sand bodies of the delta front facies are excellent gas reservoirs, characterized by rather thick, extensive and continuous distribution, high porosity and permeability, and just a few barrier beds.

关键词： sedimentary characteristics reservoir prediction Paleogene east area of Kuqa foreland basin.

Machine learning seismic reservoir prediction method based on virtual sample generation

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Petroleum Science 2021年第6期18卷 1662-1674页

作者： Kai-Heng Sang Xing-Yao Yin Fan-Chang Zhang School of Geosciences China University of Petroleum(East China)QingdaoShandong 266580China

Seismic reservoir prediction plays an important role in oil exploration and development.With the progress of artificial intelligence,many achievements have been made in machine learning seismic reservoir prediction.However,due to the factors such as economic cost,exploration maturity,and technical limitations,it is often difficult to obtain a large number of training samples for machine learning.In this case,the prediction accuracy cannot meet the requirements.To overcome this shortcoming,we develop a new machine learning reservoir prediction method based on virtual sample generation.In this method,the virtual samples,which are generated in a high-dimensional hypersphere space,are more consistent with the original data characteristics.Furthermore,at the stage of model building after virtual sample generation,virtual samples screening and model iterative optimization are used to eliminate noise samples and ensure the rationality of virtual samples.The proposed method has been applied to standard function data and real seismic data.The results show that this method can improve the prediction accuracy of machine learning significantly.

关键词： Virtual sample Machine learning reservoir prediction Hypersphere characteristic equation

Petrophysical parameters inversion for heavy oil reservoir based on a laboratory-calibrated frequency-variant rock-physics model

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Petroleum Science 2023年第6期20卷 3400-3410页

作者： Xu Han Shang-Xu Wang Zheng-Yu-Cheng Zhang Hao-Jie Liu Guo-Hua Wei Gen-Yang Tang CNPC Key Laboratory of Geophysical Prospecting China University of Petroleum(Beijing)Beijing102249China Engineering Research Center of the Ministry of Education for Exploration and Development of Complex Oil and Gas reservoirs China University of Petroleum(Beijing)Beijing102249China Shengli Oilfield Geophysical Exploration Research Institute SinopecDongying257000ShandongChina

Heavy oil has high density and viscosity, and exhibits viscoelasticity. Gassmann's theory is not suitable for materials saturated with viscoelastic fluids. Directly applying such model leads to unreliable results for seismic inversion of heavy oil reservoir. To describe the viscoelastic behavior of heavy oil, we modeled the elastic properties of heavy oil with varying viscosity and frequency using the Cole-Cole-Maxwell (CCM) model. Then, we used a CCoherent Potential Approximation (CPA) instead of the Gassmann equations to account for the fluid effect, by extending the single-phase fluid condition to two-phase fluid (heavy oil and water) condition, so that partial saturation of heavy oil can be considered. This rock physics model establishes the relationship between the elastic modulus of reservoir rock and viscosity, frequency and saturation. The viscosity of the heavy oil and the elastic moduli and porosity of typical reservoir rock samples were measured in laboratory, which were used for calibration of the rock physics model. The well-calibrated frequency-variant CPA model was applied to the prediction of the P- and S-wave velocities in the seismic frequency range (1–100 Hz) and the inversion of petrophysical parameters for a heavy oil reservoir. The pre-stack inversion results of elastic parameters are improved compared with those results using the CPA model in the sonic logging frequency (∼10 kHz), or conventional rock physics model such as the Xu-Payne model. In addition, the inversion of the porosity of the reservoir was conducted with the simulated annealing method, and the result fits reasonably well with the logging curve and depicts the location of the heavy oil reservoir on the time slice. The application of the laboratory-calibrated CPA model provides better results with the velocity dispersion correction, suggesting the important role of accurate frequency dependent rock physics models in the seismic prediction of heavy oil reservoirs.

关键词： Heavy oil Rock physics Velocity dispersion Pre-stack inversion reservoir prediction

Dissolution mechanism of a deep-buried sandstone reservoir in a deep water area:A case study from Baiyun Sag,Zhujiang River(Pearl River)Mouth Basin

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Acta Oceanologica Sinica 2023年第3期42卷 151-166页

作者： Jihua Liao Keqiang Wu Lianqiao Xiong Jingzhou Zhao Xin Li Chunyu Zhang China National Offshore Oil Corporation(CNOOC)Research Institute Co. Ltd.Beijing 100028China Hainan Branch of China National Offshore Oil Corporation(CNOOC)Co. Ltd.Haikou 570311China School of Earth Sciences and Engineering Xi’an Shiyou University Xi’an Petroleum UniversityXi’an 710065China

Dissolution mechanism and favorable reservoir distribution prediction are the key problems restricting oil and gas exploration in deep-buried layers.In this paper,the Enping Formation and Zhuhai Formation in Baiyun Sag of South China Sea was taken as a target.Based on the thin section,scanning electron microscopy,X-ray diffraction,porosity/permeability measurement,and mercury injection,influencing factors of dissolution were examined,and a dissolution model was established.Further,high-quality reservoirs were predicted temporally and spatially.The results show that dissolved pores constituted the main space of the Paleogene sandstone reservoir.Dissolution primarily occurred in the coarse-and medium-grained sandstones in the subaerial and subaqueous distributary channels,while dissolution was limited in fine-grained sandstones and inequigranular sandstones.The main dissolved minerals were feldspar,tuffaceous matrix,and diagenetic cement.Kaolinization of feldspar and illitization of kaolinite are the main dissolution pathways,but they occur at various depths and temperatures with different geothermal gradients.Dissolution is controlled by four factors,in terms of depositional facies,source rock evolution,overpressure,and fault activities,which co-acted at the period of 23.8–13.8 Ma,and resulted into strong dissolution.Additionally,based on these factors,high-quality reservoirs of the Enping and Zhuhai formations are predicted in the northern slope,southwestern step zone,and Liuhua uplift in the Baiyun Sag.

关键词： dissolution mechanism deep-buried reservoir diagenesis evolution reservoir prediction deep water region Baiyun Sag

The applicability and underlying factors of frequency-dependent amplitude-versus-offset(AVO)inversion

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Petroleum Science 2023年第4期20卷 2075-2091页

作者： Fang Ouyang Xin-Ze Liu BinWang Zi-Duo Hu Jian-Guo Zhao Xiu-Yi Yan Yu Zhang Yi-He Qing State Key Laboratory of Petroleum Resource and Prospecting China University of Petroleum(Beijing)Beijing102249China Institute of Earthquake Forecasting China Earthquake AdministrationBeijing100036China Yumen Oil Field Branch of CNPC Exploration and Development Research Institute JiuquanGansu735000China Northwest Branch of PetroChina Research Institute of Petroleum Exploration and Development LanzhouGansu730020China Unconventional Petroleum Research Institute China University of Petroleum(Beijing)Beijing102249China College of Chemical Engineering and Environment China University of Petroleum(Beijing)Beijing102249China

Recently,the great potential of seismic dispersion attributes in oil and gas exploration has attracted extensive attention.The frequency-dependent amplitude versus offset(FAVO)technology,with dispersion gradient as a hydrocarbon indicator,has developed rapidly.Based on the classical AVO theory,the technology works on the assumption that elastic parameters are frequency-dependent,and implements FAVO inversion using spectral decomposition methods,so that it can take dispersive effects into account and effectively overcome the limitations of the classical AVO.However,the factors that affect FAVO are complicated.To this end,we construct a unified equation for FAVO inversion by combining several Zoeppritz approximations.We study and compare two strategies respectively with(strategy 1)and without(strategy 2)velocity as inversion input data.Using theoretical models,we investigate the influence of various factors,such as the Zoeppritz approximation used,P-and S-wave velocity dispersion,inversion input data,the strong reflection caused by non-reservoir interfaces,and the noise level of the seismic data.Our results show that FAVO inversion based on different Zoeppritz approximations gives similar results.In addition,the inversion results of strategy 2 are generally equivalent to that of strategy 1,which means that strategy 2 can be used to obtain dispersion attributes even if the velocity is not available.We also found that the existence of non-reservoir strong reflection interface may cause significant false dispersion.Therefore,logging,geological,and other relevant data should be fully used to prevent this undesirable consequence.Both the P-and S-wave related dispersion obtained from FAVO can be used as good indicators of a hydrocarbon reservoir,but the P-wave dispersion is more reliable.In fact,due to the mutual coupling of P-and S-wave dispersion terms,the P-wave dispersion gradient inverted from PP reflection seismic data has a stronger hydrocarbon detection ability than the S-wave dispersion gradient.Moreover,there i

关键词： Zoeppritz approximation Dispersion gradient Frequency-dependent AVO inversion reservoir prediction Fluid identification

The Seismic-Geological Comprehensive prediction Method of the Low Permeability Calcareous Sandstone reservoir

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Open Journal of Geology 2016年第8期6卷 757-762页

作者： Hongyan Jiao Zhiying Ding College of Petroleum Engineering China University of Petroleum Qingdao China

Currently in Niu-zhuang sub-sag, the seismic reflection amplitude of the newly discovered turbidite sandstone is stronger in the third Segment. The main reason is that Calcareous components accounts for a large part and physical properties is relatively poor, which results in no corresponding relation between reservoir and seismic attributes, and effective reservoir is difficult to predict and describe. Therefore, using the method of geological statistics, we firstly study the distribution of calcareous matters, secondly study the contribution to seismic reflection amplitude made by Calcareous high impedance component;thirdly analyze its influence on actual seismic reflection amplitude and determine the lithology thickness of Calcareous via replacement forward modeling. At last, we characterize the reservoir using the amplitude of calcareous matters. It proves that the method of seismic-geological comprehensive prediction is reliable. It has good guidance for exploration and development of the calcareous sand lithologic reservoir in similar areas.

关键词： Calcareous Sand-Stone Geostatistical Reflection Amplitude Calcareous Forward Modeling reservoir prediction

prediction of Tight Sand reservoir with Multi-Wavelet Decomposition and Reconstructing Method

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International Journal of Geosciences 2016年第4期7卷 529-538页

作者： Lifang Cheng Yanchun Wang Zhiguo Li Fuxiu Gong School of Geophysics and Information Technology China University of Geosciences Beijing China

Special reservoir or fluid has an abnormal response to some certain frequencies, so that seismic decomposition and reconstruction are used to highlight the seismic reflection at certain frequencies useful to identify special geological bodies. Because seismic wavelets are time-varying and spatial-variable in the propagation, synthetic traces based on single wavelet make some weak but useful information lost, and make artifacts form. However, Morlet wavelet aggregation with mathematical analytical expression is able to fully and correctly reflect the variations of wavelet in the propagation of underground medium. The matching pursuit algorithm on the basis of Morlet wavelet improves the calculating efficiency in decomposition and reconstruction greatly. This method is applied to the actual study area to do conjoint analysis of single well and well-tie multi-wavelet decomposition. It is found that frequencies sensitive to interest reservoirs range from 8 to 34 Hz. Reconstructing the wavelets at those special frequencies and analyzing the reconstructed seismic data, it is pointed out that interest reservoirs have abnormal characteristics with respectively strong RMS amplitude in the reconstructed data. Crossplot of gamma value at wells and reconstructed RMS amplitude suggests that anomalies caused by interest reservoirs are well separated from the background anomalies when the reconstructed RMS amplitude is greater than 3650. Quantitative prediction results of interest reservoirs distribution in the study area reveal that interest reservoirs of western and northern study area are distributed annularly and bandedly, while most contiguous sandstone in eastern regions appears sporadically.

关键词： Morlet Wavelet Matching Pursuit Decomposition and Reconstruction Tight Sandstone reservoir prediction

Method and practice of deep favorable shale reservoirs prediction based on machine learning

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Petroleum Exploration and Development 2022年第5期49卷 1056-1068页

作者： CHENG Bingjie XU Tianji LUO Shiyi CHEN Tianjie LI Yongsheng TANG Jianming State Key Laboratory of Oil and Gas reservoir Geology and Exploitation Chengdu University of TechnologyChengdu 610059China Key Laboratory of Earth Exploitation and Information Technology of Ministry of Education Chengdu University of TechnologyChengduSichuan 610059China School of Resources and Environment University of Electronic Science and Technology of ChinaChengdu 611731China Yangtze Delta Region Institute of University of Electronic Science and Technology of China Huzhou 313000China Southwest Oil and Gas Branch Company SINOPECChengdu 610041China

A set of methods for predicting the favorable reservoir of deep shale gas based on machine learning is proposed through research of parameter correlation feature analysis principle, intelligent prediction method based on convolution neural network(CNN), and integrated fusion characterization method based on kernel principal component analysis(KPCA) nonlinear dimension reduction principle.(1) High-dimensional correlation characteristics of core and logging data are analyzed based on the Pearson correlation coefficient.(2) The nonlinear dimension reduction method of KPCA is used to characterize complex high-dimensional data to efficiently and accurately understand the core and logging response laws to favorable reservoirs.(3) CNN and logging data are used to train and verify the model similar to the underground reservoir.(4) CNN and seismic data are used to intelligently predict favorable reservoir parameters such as organic carbon content, gas content, brittleness and in-situ stress to effectively solve the problem of nonlinear and complex feature extraction in reservoir prediction.(5) KPCA is used to eliminate complex redundant information, mine big data characteristics of favorable reservoirs, and integrate and characterize various parameters to comprehensively evaluate reservoirs. This method has been used to predict the spatial distribution of favorable shale reservoirs in the Ordovician Wufeng Formation to the Silurian Longmaxi Formation of the Weirong shale gas field in the Sichuan Basin, SW China. The predicted results are highly consistent with the actual core, logging and productivity data, proving that this method can provide effective support for the exploration and development of deep shale gas.

关键词： Sichuan Basin Ordovician-Silurian shale gas reservoir prediction machine learning convolution neural network kernel principal component analysis

Theoretical and technical progress in exploration practice of the deep-water large oil fields, Santos Basin, Brazil

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Petroleum Exploration and Development 2023年第2期50卷 255-267页

作者： HE Wenyuan SHI Buqing FAN Guozhang WANG Wangquan WANG Hongping WANG Jingchun ZUO Guoping WANG Chaofeng YANG Liu China National Oil and Gas Exploration and Development Corporation Beijing 100034China PetroChina Hangzhou Research Institute of Geology Hangzhou 310023China

The history and results of petroleum exploration in the Santos Basin, Brazil are reviewed. The regularity of hydrocarbon enrichment and the key exploration technologies are summarized and analyzed using the seismic, gravity, magnetic and drilling data. It is proposed that the Santos Basin had a structural pattern of two uplifts and three depressions and the Aram-Uirapuru uplift belt controlled the hydrocarbon accumulation. It is believed that the main hydrocarbon source kitchen in the rift period controlled the hydrocarbon-enriched zones, paleo-structures controlled the scale and quality of lacustrine carbonate reservoirs, and continuous thick salt rocks controlled the hydrocarbon formation and preservation. The process and mechanism of reservoirs being transformed by CO_(2)charging were revealed. Five key exploration technologies were developed,including the variable-velocity mapping for layer-controlled facies-controlled pre-salt structures, the prediction of lacustrine carbonate reservoirs, the prediction of intrusive/effusive rock distribution, the detection of hydrocarbons in lacustrine carbonates, and the logging identification of supercritical CO_(2)fluid. These theoretical recognitions and exploration technologies have contributed to the discovery of deep-water super-large reservoirs under CNODC projects in Brazil, and will guide the further exploration of deep-water large reservoirs in the Santos Basin and other similar regions.

关键词： lacustrine carbonates salt rock deep-water oilfield igneous rock identification reservoir prediction hydrocar-bon detection supercritical CO_(2) Santos Basin Brazil