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An adaptive physics-informed deep learning method for pore pressure prediction using seismic data

Petroleum Science 2024年第2期21卷 885-902页

作者： Xin Zhang Yun-Hu Lu Yan Jin Mian Chen Bo Zhou State Key Laboratory of Petroleum Resources and Prospecting China University of Petroleum(Beijing)Beijing102249China College of Petroleum Engineering China University of Petroleum(Beijing)Beijing102249China College of Artificial Intelligence China University of Petroleum(Beijing)Beijing102249China PetroChina Tarim Oilfield Company KorlaXinjiang841000China

Accurate prediction of formation pore pressure is essential to predict fluid flow and manage hydrocarbon production in petroleum *** deep learning technique has been receiving more interest due to the great potential to deal with pore pressure ***,most of the traditional deep learning models are less efficient to address generalization *** fill this technical gap,in this work,we developed a new adaptive physics-informed deep learning model with high generalization capability to predict pore pressure values directly from seismic ***,the new model,named CGP-NN,consists of a novel parametric features extraction approach(1DCPP),a stacked multilayer gated recurrent model(multilayer GRU),and an adaptive physics-informed loss *** machine training,the developed model can automatically select the optimal physical model to constrain the results for each pore pressure *** CGP-NN model has the best generalization when the physicsrelated metricλ=0.5.A hybrid approach combining Eaton and Bowers methods is also proposed to build machine-learnable labels for solving the problem of few *** validate the developed model and methodology,a case study on a complex reservoir in Tarim Basin was further performed to demonstrate the high accuracy on the pore pressure prediction of new wells along with the strong generalization *** adaptive physics-informed deep learning approach presented here has potential application in the prediction of pore pressures coupled with multiple genesis mechanisms using seismic data.

关键词： Pore pressure prediction seismic data 1D convolution pyramid pooling Adaptive physics-informed loss function High generalization capability

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Tectonics of the Solomon Sea Basin from Vertical Gravity Gradient and seismic data

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Acta Geologica Sinica(English Edition) 2023年第2期97卷 610-622页

作者： GONG Wei XING Junhui MENG Qingwei XING Lei XU Chong ZHANG Hao Key Laboratory of Submarine Geosciences and Prospecting Techniques Ministry of Educationand College of Marine GeosciencesOcean University of ChinaQingdaoShandong 266100China Laboratory for Marine Mineral Resources Qingdao National Laboratory for Marine Science and TechnologyQingdaoShandong 266237China Chinese Academy of Geological Sciences Beijing 100037China

The Solomon Sea Basin is a Cenozoic back-arc spreading basin within the convergence system of the Pacific and Indo-Australian *** the background of subduction polarity reversal,the current Solomon Sea Basin gradually formed a rhombic morphology with the subduction of the basin along the New Britain Trench and the Trobriand *** analyzing the vertical gravity gradient,natural earthquake and seismic reflection data,this study determines the structural characteristics of the Solomon Sea *** was found that the tectonics of the basin are characterized by the original expansion structure within the central part in addition to the structure induced by the latest subduction along the basin *** original spreading structure of the basin presented an east–west linear graben and horst controlled by normal faults during the basin expansion *** a result of the subduction and slab-pull of the Solomon Sea Basin,extensional structure belts parallel to the New Britain Trench formed along the basin margin.

关键词： vertical gravity gradient seismic data tectonics New Britain Trench Solomon Sea Basin

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Time-domain identification of dynamic properties of layered soil by using extended Kalman filter and recorded seismic data

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Earthquake Engineering and Engineering Vibration 2004年第2期3卷 237-247页

作者：郑亦斌王满生刘荷姚英周锡元 University of Virginia CharlottesvilleVA 22904-4743USA Assistant Professor Institute of Geophysics China Earthquake AdministrationBeijing 100036China Graduate Student University of Alaska Anchorage.USA Associate Professor University of Virginia CharlottesvilleVA 22904-4743USA Researcher Beijing University of Technology Beijing 100083 China Professor

A novel time-domain identification technique is developed for the seismic response analysis of soil-structure interaction.A two-degree-of-freedom (2DOF) model with eight lumped parameters is adopted to model the frequency- dependent behavior of *** layered soil,the equivalent eight parameters of the 2DOF model are identified by the extended Kalman filter (EKF) method using recorded seismic *** polynomial approximations for derivation of state estimators are applied in the EKF procedure.A realistic identification example is given for the layered-soil of a building site in Anchorage,Alaska in the United *** of the example demonstrate the feasibility and practicality of the proposed identification *** 2DOF soil model and the identification technique can be used for nonlinear response analysis of soil-structure interaction in the time-domain for layered or complex soil *** identified parameters can be stored in a database tor use in other similar soil conditions,lfa universal database that covers information related to most soil conditions is developed in the thture,engineers could conveniently perform time history analyses of soil-structural interaction.

关键词： soil-structure interaction identification extended Kalman filter 2DOF model equivalent lumped parameters polynomial approximation seismic data

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Stratal Carbonate Content Inversion Using seismic data and Its Applications to the Northern South China Sea

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Journal of China University of Geosciences 2006年第4期17卷 320-325,354页

作者：熊艳钟广法李前裕吴能友李学杰马在田 State Key Laboratory of Marine Geology Tongji University Shanghai 200092 China Geophysical Exploration Company of Sichuan Petroleum Administration Bureau Chengdu 610212 China Guangzhou Marine Geological Survey Guangzhou 510760 China

On the basis of the relationship between the carbonate content and the stratal velocity and density, an exercise has been attempted using an artificial neural network on high-resolution seismic data for inversion of carbonate content with limited well measarements as a control. The method was applied to the slope area of the northern South China Sea near ODP Sites 1146 and 1148, and the results are satisfaetory. Before inversion calculation, a stepwise regression method was applied to obtain six properties related most closely to the carbonate content variations among the various properties on the seismic profiles across or near the wells. These include the average frequency, the integrated absolute amplitude, the dominant frequency, the reflection time, the derivative instantaneous amplitude, and the instantaneous frequency. The results, with carbonate content errors of mostly ±5 % relative to those measured from sediment samples, show a relatively accurate picture of carbonate distribution along the slope profile. This method pioneers a new quantitative model to acquire carbonate content variations directly from high-resolution seismic data. It will provide a new approach toward obtaining substitutive high-resolution sediment data for earth system studies related to basin evolution, especially in discussing the coupling between regional sedimentation and climate change.

关键词： carbonate content inversion seismic data artificial neural network ODP Leg 184 northern South China Sea.

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The　application　of　seismic　data　with　different　precision　in　the　determination　of　seismicity　parameters

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Acta Seismologica Sinica(English Edition) 1994年第3期7卷 361-368页

作者：金学申戴英华赵军靳艳萍 Seismological Bureau of Hebei Province Shijiazhuang China

Due to the limitation of the data,the β value of seismic zones have been determined by the historical seismic data at the present seismic hazard analysis. Because of lacking of historical documents,many moderate historical events were not recorded and the determined seismicity parameters have shown the uncertainty. It is difficult to describe the temporal inhomogeneous of the seismicity by the instrumental observation data with short *** paper used the maximum likelihood method to joint two data with different precision and duration, which brings each superiority into play and overcomes each ***, it is possible for results to have more actual *** method for the estimation of the uncertainty and the sensitive analysis of these pa rameters have been shown. It might provide other way for estimation of the parameters in the seismic hazard analysis.

关键词： seismic data precision seismicity

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Method for Morphological Filtering in seismic data Processing

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Petroleum Science 2005年第4期2卷 20-29页

作者： Li Qing Wang Runqiu Huang Wenfeng Zheng Guijuan Key Laboratory of Geophysical Exploration under CNPC Faculty of Resources and Information Technology China University of Petroleum Beijing 102249 China

A new method is introduced to suppress the noise in seismic data processing. Based on the subtle difference in shape between the noise and the actual signal, we introduce morphologic filtering into seismic data processing. From the shape and the S/N we can see that the effect of morphologic filtering is superior to other methods like id-value filtering, neighbor average filtering, etc. The SNR of the signal after morphological filtering is comparatively great. In addition, the precision of the seismic data after morphological filtering is high. The characteristics of the actual signal, such as frequency and amplitude, are preserved. We give an example of the real seismic data processing using morphological filtering, in which the actual signal is retained, while the random high intensity noise was removed.

关键词： Mathematical morphology seismic data erosion dilation opening closing structuring element

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The study of seismic data gridding methods

The study of seismic data gridding methods

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The 2nd International Conference on Environmental and Engineering Geophysics

作者： Hongjie Cheng Xiangyun Hu Mima Tian China University of Geoscience Wuhan China

＜正＞The gridding of discrete data is the kernel technique of data processing methods in scientific and engineering research. seismic data is the outcome of seismic prospecting, compared with the large geographical scale, the seismic data we gathered is finite. So data gridding is a necessary part in the processing of seismic data, with the gridded data, we can describe the subsurface layers of the whole area clearly. The article discusses four kinds of gridding methods: Trend surface fitting, Interpolation, Remnant error method, Kriging method. Here we put emphasis on Kriging method and its application on seismic data processing. The result from the application shows that Kriging is an effective method.

关键词： seismic data gndding Kriging

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A hybrid of fuzzy-link clustering and classification for seismic data

A hybrid of fuzzy-link clustering and classification for sei...

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第六届（2011）中国管理学年会——商务智能分会场

作者： Zhongbin Ouyang1,2,Yong Shi1,2,3,Le Yang1,2 (1 Research Center on Fictitious Economy and data Science,CAS,Beijing 100190,China) (2 Graduate University of Chinese Academy of Sciences,Beijing 100190,China) (3 College of Information Science and Technology,University of Nebraska at Omaha,Omaha,NE 68118,USA)

Interpreting seismic data is an arduous and time-consuming *** cluster analysis can be helpful to analyze seismic data,most traditional clustering algorithms can hardly obtain satisfactory results since they do not take account of spatially dependencies of seismic data,which make clustering seismic data different from other clustering ***,seismic data are by nature fuzzy and noisy,which limit many popular clustering *** this paper,we present a hybrid of fuzzy-link clustering technique and classification for seismic data incorporating spatial and non-spatial information into the *** results on real seismic data show that our algorithm is robust to noise and can discover clusters with arbitrary shape.

关键词： seismic data cluster analysis classification spatial attribute non-spatial

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Performance of Continuous Wavelet Transform over Fourier Transform in Features Resolutions

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International Journal of Geosciences 2024年第2期15卷 87-105页

作者： Michael K. Appiah Sylvester K. Danuor Alfred K. Bienibuor Department of Physics Kwame Nkrumah University of Science and Technology (KNUST) Kumasi Ghana Department of Chemical Sciences University of Energy and Natural Resources Sunyani Ghana

This study presents a comparative analysis of two image enhancement techniques, Continuous Wavelet Transform (CWT) and Fast Fourier Transform (FFT), in the context of improving the clarity of high-quality 3D seismic data obtained from the Tano Basin in West Africa, Ghana. The research focuses on a comparative analysis of image clarity in seismic attribute analysis to facilitate the identification of reservoir features within the subsurface structures. The findings of the study indicate that CWT has a significant advantage over FFT in terms of image quality and identifying subsurface structures. The results demonstrate the superior performance of CWT in providing a better representation, making it more effective for seismic attribute analysis. The study highlights the importance of choosing the appropriate image enhancement technique based on the specific application needs and the broader context of the study. While CWT provides high-quality images and superior performance in identifying subsurface structures, the selection between these methods should be made judiciously, taking into account the objectives of the study and the characteristics of the signals being analyzed. The research provides valuable insights into the decision-making process for selecting image enhancement techniques in seismic data analysis, helping researchers and practitioners make informed choices that cater to the unique requirements of their studies. Ultimately, this study contributes to the advancement of the field of subsurface imaging and geological feature identification.

关键词： Continuous Wavelet Transform (CWT) Fast Fourier Transform (FFT) Reservoir Characterization Tano Basin seismic data Spectral Decomposition

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Turbidite Dynamics and Hydrocarbon Reservoir Formation in the Tano Basin: A Coastal West African Perspective

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International Journal of Geosciences 2024年第2期15卷 137-161页

作者： Michael K. Appiah Sylvester K. Danuor Striggner Bedu-Addo Alfred K. Bienibuor Department of Physics Kwame Nkrumah University of Science and Technology (KNUST) Kumasi Ghana Department of Chemical Sciences University of Energy and Natural Resources Sunyani Ghana

This study examines the turbidite dynamics and hydrocarbon reservoir formation in Ghana’s Tano Basin, which is located in coastal West Africa. Through an exploration of geological processes spanning millions of years, we uncover key factors shaping hydrocarbon accumulation, including source rock richness, temperature, pressure, and geological structures. The research offers valuable insights applicable to exploration, management, and sustainable resource exploitation in coastal West Africa. It facilitates the identification of exploration targets with higher hydrocarbon potential, enables the anticipation of reservoir potential within the Tano Basin, and assists in tailoring exploration and management strategies to specific geological conditions of the Tano Basin. Analysis of fluvial channels sheds light on their impact on landscape formation and hydrocarbon exploration. The investigation into turbidite systems unveils intricate interactions involving tectonics, sea-level fluctuations, and sedimentation patterns, influencing the development of reservoirs. An understanding of sediment transport and depositional settings is essential for efficient reservoir management. Geomorphological features, such as channels, submarine canyons, and distinct channel types, are essential in this situation. A detailed examination of turbidite channel structures, encompassing canyons, channel complexes, convex channels, and U-shaped channels, provides valuable insights and aids in identifying exploration targets like basal lag, channel levees, and lobes. These findings underscore the enduring significance of turbidite systems as conduits for sediment transport, contributing to enhanced reservoir management and efficient hydrocarbon production. The study also highlights how important it is to examine the configuration of sedimentary layers, stacking patterns, and angular laminated facies to identify turbidites, understand reservoir distribution, and improve well design. The dynamic nat

关键词： Reservoir Characterization Tano Basin seismic data Hydrocarbon Potential Channels Turbidites

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