In order to detect fault exactly and quickly, cusp catastrophe theory is used to interpret 3D coal seismic data in this paper. By establishing a cusp model, seismic signal is transformed into standard form of cusp cat...In order to detect fault exactly and quickly, cusp catastrophe theory is used to interpret 3D coal seismic data in this paper. By establishing a cusp model, seismic signal is transformed into standard form of cusp catastrophe and catastrophe parameters, including time-domain catastrophe potential, time-domain catastrophe time, frequency-domain catastrophe potential and frequency- domain degree, are calculated. Catastrophe theory is used in 3D seismic structural interpretation in coal mine. The results show that the position of abnormality of the catastrophe parameter profile or curve is related to the location of fault, and the cusp catastrophe theory is effective to automatically pick up geology information and improve the interpretation precision in 3D seismic data.展开更多
Nowadays, it becomes very urgent to find remain oil under the oil shortage worldwide.However, most of simple reservoirs have been discovered and those undiscovered are mostly complex structural, stratigraphic and lith...Nowadays, it becomes very urgent to find remain oil under the oil shortage worldwide.However, most of simple reservoirs have been discovered and those undiscovered are mostly complex structural, stratigraphic and lithologic ones. Summarized in this paper is the integrated seismic processing/interpretation technique established on the basis of pre-stack AVO processing and interpretation.Information feedbacks occurred between the pre-stack and post-stack processes so as to improve the accuracy in utilization of data and avoid pitfalls in seismic attributes. Through the integration of seismic data with geologic data, parameters that were most essential to describing hydrocarbon characteristics were determined and comprehensively appraised, and regularities of reservoir generation and distribution were described so as to accurately appraise reservoirs, delineate favorite traps and pinpoint wells.展开更多
Formation pore pressure is the foundation of well plan,and it is related to the safety and efficiency of drilling operations in oil and gas development.However,the traditional method for predicting formation pore pres...Formation pore pressure is the foundation of well plan,and it is related to the safety and efficiency of drilling operations in oil and gas development.However,the traditional method for predicting formation pore pressure involves applying post-drilling measurement data from nearby wells to the target well,which may not accurately reflect the formation pore pressure of the target well.In this paper,a novel method for predicting formation pore pressure ahead of the drill bit by embedding petrophysical theory into machine learning based on seismic and logging-while-drilling(LWD)data was proposed.Gated recurrent unit(GRU)and long short-term memory(LSTM)models were developed and validated using data from three wells in the Bohai Oilfield,and the Shapley additive explanations(SHAP)were utilized to visualize and interpret the models proposed in this study,thereby providing valuable insights into the relative importance and impact of input features.The results show that among the eight models trained in this study,almost all model prediction errors converge to 0.05 g/cm^(3),with the largest root mean square error(RMSE)being 0.03072 and the smallest RMSE being 0.008964.Moreover,continuously updating the model with the increasing training data during drilling operations can further improve accuracy.Compared to other approaches,this study accurately and precisely depicts formation pore pressure,while SHAP analysis guides effective model refinement and feature engineering strategies.This work underscores the potential of integrating advanced machine learning techniques with domain-specific knowledge to enhance predictive accuracy for petroleum engineering applications.展开更多
The InSight mission has obtained seismic data from Mars,offering new insights into the planet’s internal structure and seismic activity.However,the raw data released to the public contain various sources of noise,suc...The InSight mission has obtained seismic data from Mars,offering new insights into the planet’s internal structure and seismic activity.However,the raw data released to the public contain various sources of noise,such as ticks and glitches,which hamper further seismological studies.This paper presents step-by-step processing of InSight’s Very Broad Band seismic data,focusing on the suppression and removal of non-seismic noise.The processing stages include tick noise removal,glitch signal suppression,multicomponent synchronization,instrument response correction,and rotation of orthogonal components.The processed datasets and associated codes are openly accessible and will support ongoing efforts to explore the geophysical properties of Mars and contribute to the broader field of planetary seismology.展开更多
Seismic data plays a pivotal role in fault detection,offering critical insights into subsurface structures and seismic hazards.Understanding fault detection from seismic data is essential for mitigating seismic risks ...Seismic data plays a pivotal role in fault detection,offering critical insights into subsurface structures and seismic hazards.Understanding fault detection from seismic data is essential for mitigating seismic risks and guiding land-use plans.This paper presents a comprehensive review of existing methodologies for fault detection,focusing on the application of Machine Learning(ML)and Deep Learning(DL)techniques to enhance accuracy and efficiency.Various ML and DL approaches are analyzed with respect to fault segmentation,adaptive learning,and fault detection models.These techniques,benchmarked against established seismic datasets,reveal significant improvements over classical methods in terms of accuracy and computational efficiency.Additionally,this review highlights emerging trends,including hybrid model applications and the integration of real-time data processing for seismic fault detection.By providing a detailed comparative analysis of current methodologies,this review aims to guide future research and foster advancements in the effectiveness and reliability of seismic studies.Ultimately,the study seeks to bridge the gap between theoretical investigations and practical implementations in fault detection.展开更多
Pore pressure is a decisive measure to assess the reservoir’s geomechanical properties,ensures safe and efficient drilling operations,and optimizes reservoir characterization and production.The conventional approache...Pore pressure is a decisive measure to assess the reservoir’s geomechanical properties,ensures safe and efficient drilling operations,and optimizes reservoir characterization and production.The conventional approaches sometimes fail to comprehend complex and persistent relationships between pore pressure and formation properties in the heterogeneous reservoirs.This study presents a novel machine learning optimized pore pressure prediction method with a limited dataset,particularly in complex formations.The method addresses the conventional approach's limitations by leveraging its capability to learn complex data relationships.It integrates the best Gradient Boosting Regressor(GBR)algorithm to model pore pressure at wells and later utilizes ContinuousWavelet Transformation(CWT)of the seismic dataset for spatial analysis,and finally employs Deep Neural Network for robust and precise pore pressure modeling for the whole volume.In the second stage,for the spatial variations of pore pressure in the thin Khadro Formation sand reservoir across the entire subsurface area,a three-dimensional pore pressure prediction is conducted using CWT.The relationship between the CWT and geomechanical properties is then established through supervised machine learning models on well locations to predict the uncertainties in pore pressure.Among all intelligent regression techniques developed using petrophysical and elastic properties for pore pressure prediction,the GBR has provided exceptional results that have been validated by evaluation metrics based on the R^(2) score i.e.,0.91 between the calibrated and predicted pore pressure.Via the deep neural network,the relationship between CWT resultant traces and predicted pore pressure is established to analyze the spatial variation.展开更多
The Belt and Road global navigation satellite system(B&R GNSS)network is the first large-scale deployment of Chinese GNSS equipment in a seismic system.Prior to this,there have been few systematic assessments of t...The Belt and Road global navigation satellite system(B&R GNSS)network is the first large-scale deployment of Chinese GNSS equipment in a seismic system.Prior to this,there have been few systematic assessments of the data quality of Chinese GNSS equipment.In this study,data from four representative GNSS sites in different regions of China were analyzed using the G-Nut/Anubis software package.Four main indicators(data integrity rate,data validity ratio,multi-path error,and cycle slip ratio)used to systematically analyze data quality,while evaluating the seismic monitoring capabilities of the network based on earthquake magnitudes estimated from high-frequency GNSS data are evaluated by estimating magnitude based on highfrequency GNSS data.The results indicate that the quality of the data produced by the three types of Chinese receivers used in the network meets the needs of earthquake monitoring and the new seismic industry standards,which provide a reference for the selection of equipment for future new projects.After the B&R GNSS network was established,the seismic monitoring capability for earthquakes with magnitudes greater than M_(W)6.5 in most parts of the Sichuan-Yunnan region improved by approximately 20%.In key areas such as the Sichuan-Yunnan Rhomboid Block,the monitoring capability increased by more than 25%,which has greatly improved the effectiveness of regional comprehensive earthquake management.展开更多
Branching river channels and the coexistence of valleys, ridges, hiils, and slopes＇as the result of long-term weathering and erosion form the unique loess topography. The Changqing Geophysical Company, working in the...Branching river channels and the coexistence of valleys, ridges, hiils, and slopes＇as the result of long-term weathering and erosion form the unique loess topography. The Changqing Geophysical Company, working in these complex conditions, has established a suite of technologies for high-fidelity processing and fine interpretation of seismic data. This article introduces the processes involved in the data processing and interpretation and illustrates the results.展开更多
During drilling operations,the low resolution of seismic data often limits the accurate characterization of small-scale geological bodies near the borehole and ahead of the drill bit.This study investigates high-resol...During drilling operations,the low resolution of seismic data often limits the accurate characterization of small-scale geological bodies near the borehole and ahead of the drill bit.This study investigates high-resolution seismic data processing technologies and methods tailored for drilling scenarios.The high-resolution processing of seismic data is divided into three stages:pre-drilling processing,post-drilling correction,and while-drilling updating.By integrating seismic data from different stages,spatial ranges,and frequencies,together with information from drilled wells and while-drilling data,and applying artificial intelligence modeling techniques,a progressive high-resolution processing technology of seismic data based on multi-source information fusion is developed,which performs simple and efficient seismic information updates during drilling.Case studies show that,with the gradual integration of multi-source information,the resolution and accuracy of seismic data are significantly improved,and thin-bed weak reflections are more clearly imaged.The updated seismic information while-drilling demonstrates high value in predicting geological bodies ahead of the drill bit.Validation using logging,mud logging,and drilling engineering data ensures the fidelity of the processing results of high-resolution seismic data.This provides clearer and more accurate stratigraphic information for drilling operations,enhancing both drilling safety and efficiency.展开更多
High-resolution shallow seismic methods are the most widely used geophysical methods in near surface characterization. However, in many cases interpreting the seismic images can be misleading. In this article, we pres...High-resolution shallow seismic methods are the most widely used geophysical methods in near surface characterization. However, in many cases interpreting the seismic images can be misleading. In this article, we present three case studies where results from P-wave seismic reflection, SH-wave seismic reflection, and multi-channel analysis of surface wave （MASW） surveys were incorrectly interpreted because of inadequate constraints on either the surveyed sites surface or subsurface conditions. A P-wave reflection survey feature was first interpreted as a shallow fault zone but it was later determined to result from a high level of background noise as the acquisition passed through a road intersection. A SH-wave seismic reflection survey feature was interpreted to be a reverse dip-slip fault but targeted drilling showed it was deep local erosion into the bedrock surface. Finally, in an MASW survey, a steeply dipping feature was first interpreted as a bedrock valley. However, later exploratory drilling showed the feature to be a shallow layer of very soft lake sediment that severely damped most of the applied surface wave frequency band. Although initial interpretations were incorrect, they stimulated discussions among geophysicists and geologists and underscored the need for meaningful cooperation and discourse between the scientists before, during, and after geophysical data acquisition.展开更多
The loess plateau covering the North Shaanxi slope and Tianhuan depression consists of a regional monocline, high in the east and low in the west, with dips of less than 1^0, Structural movement in this region was wea...The loess plateau covering the North Shaanxi slope and Tianhuan depression consists of a regional monocline, high in the east and low in the west, with dips of less than 1^0, Structural movement in this region was weak so that faults and local structures were not well developed. As a result, numerous wide and gentle noses and small traps with magnitudes less than 50 m were developed on the large westward-dipping monocline. Reservoirs, including Mesozoic oil reservoirs and Paleozoic gas reservoirs in the Ordos Basin, are dominantly lithologic with a small number of structural reservoirs. Single reservoirs are characterized as thin with large lateral variations, strong anisotropy, low porosity, low permeability, and low richness. A series of approaches for predicting reservoir thickness, physical properties, and hydrocarbon potential of subtle lithologic reservoirs was established based on the interpretation of erosion surfaces.展开更多
Through analyzing the needs of seismic data processing and interpretation,a system model based on CSCW is designed.Using the technology of CSCW to build the environment of cooperative work allows the field data acquis...Through analyzing the needs of seismic data processing and interpretation,a system model based on CSCW is designed.Using the technology of CSCW to build the environment of cooperative work allows the field data acquisition to possess the functions of remote real-time guidance by experts and remote real-time processing of the data.展开更多
3D seismic and petrophysical log data interpretation of reservoir sands in “SIMA” Field, onshore Niger Delta has been undertaken in this study to ascertain the reservoir characteristics in terms of favourable struct...3D seismic and petrophysical log data interpretation of reservoir sands in “SIMA” Field, onshore Niger Delta has been undertaken in this study to ascertain the reservoir characteristics in terms of favourable structural and petrophysical parameters suitable for hydrocarbon accumulation and entrapment in the field. Horizon and fault interpretation were carried out for subsurface structural delineation. In all, seven faults (five normal and two listric faults) were mapped in the seismic section. These faults were major structure building faults corresponding to the growth and antithetic faults in the area within the well control. The antithetic fault trending northwest-southeast and the normal fault trending northeast-southwest on the structural high in the section act as good trapping mechanisms for hydrocarbon accumulations in the reservoir. From the manual and auto-tracking methods applied, several horizons were identified and mapped. The section is characterized by high amplitude with moderate-to-good continuity reflections appearing parallel to sub-parallel, mostly disturbed by some truncations which are more fault related than lithologic heterogeneity. The southwestern part is, however, characterized by low-to-high or variable amplitude reflections with poor-to-low continuity. Normal faults linked to roll-over anticlines were identified. Some fault truncations were observed due to lithologic heterogeneity. The combination of these faults acts as good traps for hydrocarbon accumulations in the reservoir. Reservoir favourable petrophysical qualities, having average NTG, porosity, permeability and water saturation of 5 m, 0.20423, 1128.219 kD and 0.458 respectively.展开更多
Modem oil industry is on the way of complication of the geological structure to use the latest technologies to analyze available geological and geophysical algorithm---continuous wavelet transform in example of synthe...Modem oil industry is on the way of complication of the geological structure to use the latest technologies to analyze available geological and geophysical algorithm---continuous wavelet transform in example of synthetic and real data. of the deposits. This trend requires specialists information. The article describes a new展开更多
Irregular seismic data causes problems with multi-trace processing algorithms and degrades processing quality. We introduce the Projection onto Convex Sets （POCS） based image restoration method into the seismic data...Irregular seismic data causes problems with multi-trace processing algorithms and degrades processing quality. We introduce the Projection onto Convex Sets （POCS） based image restoration method into the seismic data reconstruction field to interpolate irregularly missing traces. For entire dead traces, we transfer the POCS iteration reconstruction process from the time to frequency domain to save computational cost because forward and reverse Fourier time transforms are not needed. In each iteration, the selection threshold parameter is important for reconstruction efficiency. In this paper, we designed two types of threshold models to reconstruct irregularly missing seismic data. The experimental results show that an exponential threshold can greatly reduce iterations and improve reconstruction efficiency compared to a linear threshold for the same reconstruction result. We also analyze the anti- noise and anti-alias ability of the POCS reconstruction method. Finally, theoretical model tests and real data examples indicate that the proposed method is efficient and applicable.展开更多
Data mining is the process of extracting implicit but potentially useful information from incomplete, noisy, and fuzzy data. Data mining offers excellent nonlinear modeling and self-organized learning, and it can play...Data mining is the process of extracting implicit but potentially useful information from incomplete, noisy, and fuzzy data. Data mining offers excellent nonlinear modeling and self-organized learning, and it can play a vital role in the interpretation of well logging data of complex reservoirs. We used data mining to identify the lithologies in a complex reservoir. The reservoir lithologies served as the classification task target and were identified using feature extraction, feature selection, and modeling of data streams. We used independent component analysis to extract information from well curves. We then used the branch-and- bound algorithm to look for the optimal feature subsets and eliminate redundant information. Finally, we used the C5.0 decision-tree algorithm to set up disaggregated models of the well logging curves. The modeling and actual logging data were in good agreement, showing the usefulness of data mining methods in complex reservoirs.展开更多
In multi-component seismic exploration, the horizontal and vertical components both contain P- and SV-waves. The P- and SV-wavefields in a seismic record can be separated by their horizontal and vertical displacements...In multi-component seismic exploration, the horizontal and vertical components both contain P- and SV-waves. The P- and SV-wavefields in a seismic record can be separated by their horizontal and vertical displacements when upgoing P- and SV-waves arrive at the sea floor. If the sea floor P wave velocity, S wave velocity, and density are known, the separation can be achieved in ther-p domain. The separated wavefields are then transformed to the time domain. A method of separating P- and SV-wavefields is presented in this paper and used to effectively separate P- and SV-wavefields in synthetic and real data. The application to real data shows that this method is feasible and effective. It also can be used for free surface data.展开更多
The Pearl River Estuary(PRE) is located at the onshore-offshore transition zone between South China and South China Sea Basin, and it is of great significant value in discussing tectonic relationships between South Ch...The Pearl River Estuary(PRE) is located at the onshore-offshore transition zone between South China and South China Sea Basin, and it is of great significant value in discussing tectonic relationships between South China block and South China Sea block and seismic activities along the offshore active faults in PRE. However, the researches on geometric characteristics of offshore faults in this area are extremely lacking. To investigate the offshore fault distribution and their geometric features in the PRE in greater detail, we acquired thirteen seismic reflection profiles in 2015. Combining the analysis of the seismic reflection and free-air gravity anomaly data, this paper revealed the location, continuity, and geometry of the littoral fault zone and other offshore faults in PRE. The littoral fault zone is composed of the major Dangan Islands fault and several parallel, high-angle, normal faults, which mainly trend northeast to northeast-to-east and dip to the southeast with large displacements. The fault zone is divided into three different segments by the northwest-trending faults. Moreover, the basement depth around Dangan Islands is very shallow, while it suddenly increases along the islands westward and southward. These has resulted in the islands and neighboring areas becoming the places where the stress accumulates easily. The seismogenic pattern of this area is closely related to the comprehensive effect of intersecting faults together with the low velocity layer.展开更多
In this paper, a new concept called numerical structure of seismic data is introduced and the difference between numerical structure and numerical value of seismic data is explained. Our study shows that the numerical...In this paper, a new concept called numerical structure of seismic data is introduced and the difference between numerical structure and numerical value of seismic data is explained. Our study shows that the numerical seismic structure is closely related to oil and gas-bearing reservoir, so it is very useful for a geologist or a geophysicist to precisely interpret the oil-bearing layers from the seismic data. This technology can be applied to any exploration or production stage. The new method has been tested on a series of exploratory or development wells and proved to be reliable in China. Hydrocarbon-detection with this new method for 39 exploration wells on 25 structures indi- cates a success ratio of over 80 percent. The new method of hydrocarbon prediction can be applied for: (1) depositional environment of reservoirs with marine fades, delta, or non-marine fades (including fluvial facies, lacustrine fades); (2) sedimentary rocks of reservoirs that are non-marine clastic rocks and carbonate rock; and (3) burial depths range from 300 m to 7000 m, and the minimum thickness of these reservoirs is over 8 m (main frequency is about 50 Hz).展开更多
The field seismic data is disturbed by the interferential information, which has low signal to noise ratio (SNR). That is disadvantage for seismic data interpretation. So it is important to remove the noise of seismic...The field seismic data is disturbed by the interferential information, which has low signal to noise ratio (SNR). That is disadvantage for seismic data interpretation. So it is important to remove the noise of seismic data. Independent component analysis (ICA) can remove most of the noise interference. However, ICA has some defects in noise reduction, because it needs some conditions that seismic data is independent reciprocally for denoising. To solve these defects, this paper proposes an improved ICA algorithm to noise reduction. Through simulation experiments, it can be obtained that the best decomposition levels of the new algorithm is 3. At last, the proposed improved ICA is applied to deal with the actual seismic data. The results show that it can effectively eliminate most of seismic noise such as random noise, linear interference, surface waves, and so on. The improved ICA is not only easy to denoising, but also has excellent mathematical theoretical properties.展开更多
文摘In order to detect fault exactly and quickly, cusp catastrophe theory is used to interpret 3D coal seismic data in this paper. By establishing a cusp model, seismic signal is transformed into standard form of cusp catastrophe and catastrophe parameters, including time-domain catastrophe potential, time-domain catastrophe time, frequency-domain catastrophe potential and frequency- domain degree, are calculated. Catastrophe theory is used in 3D seismic structural interpretation in coal mine. The results show that the position of abnormality of the catastrophe parameter profile or curve is related to the location of fault, and the cusp catastrophe theory is effective to automatically pick up geology information and improve the interpretation precision in 3D seismic data.
文摘Nowadays, it becomes very urgent to find remain oil under the oil shortage worldwide.However, most of simple reservoirs have been discovered and those undiscovered are mostly complex structural, stratigraphic and lithologic ones. Summarized in this paper is the integrated seismic processing/interpretation technique established on the basis of pre-stack AVO processing and interpretation.Information feedbacks occurred between the pre-stack and post-stack processes so as to improve the accuracy in utilization of data and avoid pitfalls in seismic attributes. Through the integration of seismic data with geologic data, parameters that were most essential to describing hydrocarbon characteristics were determined and comprehensively appraised, and regularities of reservoir generation and distribution were described so as to accurately appraise reservoirs, delineate favorite traps and pinpoint wells.
基金supported by the National Natural Science Foundation of China(Grant numbers:52174012,52394250,52394255,52234002,U22B20126,51804322).
文摘Formation pore pressure is the foundation of well plan,and it is related to the safety and efficiency of drilling operations in oil and gas development.However,the traditional method for predicting formation pore pressure involves applying post-drilling measurement data from nearby wells to the target well,which may not accurately reflect the formation pore pressure of the target well.In this paper,a novel method for predicting formation pore pressure ahead of the drill bit by embedding petrophysical theory into machine learning based on seismic and logging-while-drilling(LWD)data was proposed.Gated recurrent unit(GRU)and long short-term memory(LSTM)models were developed and validated using data from three wells in the Bohai Oilfield,and the Shapley additive explanations(SHAP)were utilized to visualize and interpret the models proposed in this study,thereby providing valuable insights into the relative importance and impact of input features.The results show that among the eight models trained in this study,almost all model prediction errors converge to 0.05 g/cm^(3),with the largest root mean square error(RMSE)being 0.03072 and the smallest RMSE being 0.008964.Moreover,continuously updating the model with the increasing training data during drilling operations can further improve accuracy.Compared to other approaches,this study accurately and precisely depicts formation pore pressure,while SHAP analysis guides effective model refinement and feature engineering strategies.This work underscores the potential of integrating advanced machine learning techniques with domain-specific knowledge to enhance predictive accuracy for petroleum engineering applications.
基金supported by the National Key R&D Program of China(Nos.2022YFF 0503203 and 2024YFF0809900)the Research Funds of the Institute of Geophysics,China Earthquake Administration(No.DQJB24X28)the National Natural Science Foundation of China(Nos.42474226 and 42441827).
文摘The InSight mission has obtained seismic data from Mars,offering new insights into the planet’s internal structure and seismic activity.However,the raw data released to the public contain various sources of noise,such as ticks and glitches,which hamper further seismological studies.This paper presents step-by-step processing of InSight’s Very Broad Band seismic data,focusing on the suppression and removal of non-seismic noise.The processing stages include tick noise removal,glitch signal suppression,multicomponent synchronization,instrument response correction,and rotation of orthogonal components.The processed datasets and associated codes are openly accessible and will support ongoing efforts to explore the geophysical properties of Mars and contribute to the broader field of planetary seismology.
文摘Seismic data plays a pivotal role in fault detection,offering critical insights into subsurface structures and seismic hazards.Understanding fault detection from seismic data is essential for mitigating seismic risks and guiding land-use plans.This paper presents a comprehensive review of existing methodologies for fault detection,focusing on the application of Machine Learning(ML)and Deep Learning(DL)techniques to enhance accuracy and efficiency.Various ML and DL approaches are analyzed with respect to fault segmentation,adaptive learning,and fault detection models.These techniques,benchmarked against established seismic datasets,reveal significant improvements over classical methods in terms of accuracy and computational efficiency.Additionally,this review highlights emerging trends,including hybrid model applications and the integration of real-time data processing for seismic fault detection.By providing a detailed comparative analysis of current methodologies,this review aims to guide future research and foster advancements in the effectiveness and reliability of seismic studies.Ultimately,the study seeks to bridge the gap between theoretical investigations and practical implementations in fault detection.
基金funded by the Basic Science Centre Project of the National Natural Science Foundation of China(Grant No.72088101)supported by the Higher Education Commission,Pakistan(Grant No.20-14925/NRPU/R&D/HEC/2021-2021)+1 种基金the Researchers Supporting Project Number(Grant No.RSP2025R351)King Saud University,Riyadh,Saudi Arabia,for funding this research article.
文摘Pore pressure is a decisive measure to assess the reservoir’s geomechanical properties,ensures safe and efficient drilling operations,and optimizes reservoir characterization and production.The conventional approaches sometimes fail to comprehend complex and persistent relationships between pore pressure and formation properties in the heterogeneous reservoirs.This study presents a novel machine learning optimized pore pressure prediction method with a limited dataset,particularly in complex formations.The method addresses the conventional approach's limitations by leveraging its capability to learn complex data relationships.It integrates the best Gradient Boosting Regressor(GBR)algorithm to model pore pressure at wells and later utilizes ContinuousWavelet Transformation(CWT)of the seismic dataset for spatial analysis,and finally employs Deep Neural Network for robust and precise pore pressure modeling for the whole volume.In the second stage,for the spatial variations of pore pressure in the thin Khadro Formation sand reservoir across the entire subsurface area,a three-dimensional pore pressure prediction is conducted using CWT.The relationship between the CWT and geomechanical properties is then established through supervised machine learning models on well locations to predict the uncertainties in pore pressure.Among all intelligent regression techniques developed using petrophysical and elastic properties for pore pressure prediction,the GBR has provided exceptional results that have been validated by evaluation metrics based on the R^(2) score i.e.,0.91 between the calibrated and predicted pore pressure.Via the deep neural network,the relationship between CWT resultant traces and predicted pore pressure is established to analyze the spatial variation.
基金supported by grants from the National Natural Science Foundation of China(No.42004010)the B&R Seismic Monitoring Network Project of the China Earthquake Networks Center(No.5007).
文摘The Belt and Road global navigation satellite system(B&R GNSS)network is the first large-scale deployment of Chinese GNSS equipment in a seismic system.Prior to this,there have been few systematic assessments of the data quality of Chinese GNSS equipment.In this study,data from four representative GNSS sites in different regions of China were analyzed using the G-Nut/Anubis software package.Four main indicators(data integrity rate,data validity ratio,multi-path error,and cycle slip ratio)used to systematically analyze data quality,while evaluating the seismic monitoring capabilities of the network based on earthquake magnitudes estimated from high-frequency GNSS data are evaluated by estimating magnitude based on highfrequency GNSS data.The results indicate that the quality of the data produced by the three types of Chinese receivers used in the network meets the needs of earthquake monitoring and the new seismic industry standards,which provide a reference for the selection of equipment for future new projects.After the B&R GNSS network was established,the seismic monitoring capability for earthquakes with magnitudes greater than M_(W)6.5 in most parts of the Sichuan-Yunnan region improved by approximately 20%.In key areas such as the Sichuan-Yunnan Rhomboid Block,the monitoring capability increased by more than 25%,which has greatly improved the effectiveness of regional comprehensive earthquake management.
文摘Branching river channels and the coexistence of valleys, ridges, hiils, and slopes＇as the result of long-term weathering and erosion form the unique loess topography. The Changqing Geophysical Company, working in these complex conditions, has established a suite of technologies for high-fidelity processing and fine interpretation of seismic data. This article introduces the processes involved in the data processing and interpretation and illustrates the results.
基金Supported by the National Natural Science Foundation of China(U24B2031)National Key Research and Development Project(2018YFA0702504)"14th Five-Year Plan"Science and Technology Project of CNOOC(KJGG2022-0201)。
文摘During drilling operations,the low resolution of seismic data often limits the accurate characterization of small-scale geological bodies near the borehole and ahead of the drill bit.This study investigates high-resolution seismic data processing technologies and methods tailored for drilling scenarios.The high-resolution processing of seismic data is divided into three stages:pre-drilling processing,post-drilling correction,and while-drilling updating.By integrating seismic data from different stages,spatial ranges,and frequencies,together with information from drilled wells and while-drilling data,and applying artificial intelligence modeling techniques,a progressive high-resolution processing technology of seismic data based on multi-source information fusion is developed,which performs simple and efficient seismic information updates during drilling.Case studies show that,with the gradual integration of multi-source information,the resolution and accuracy of seismic data are significantly improved,and thin-bed weak reflections are more clearly imaged.The updated seismic information while-drilling demonstrates high value in predicting geological bodies ahead of the drill bit.Validation using logging,mud logging,and drilling engineering data ensures the fidelity of the processing results of high-resolution seismic data.This provides clearer and more accurate stratigraphic information for drilling operations,enhancing both drilling safety and efficiency.
文摘High-resolution shallow seismic methods are the most widely used geophysical methods in near surface characterization. However, in many cases interpreting the seismic images can be misleading. In this article, we present three case studies where results from P-wave seismic reflection, SH-wave seismic reflection, and multi-channel analysis of surface wave （MASW） surveys were incorrectly interpreted because of inadequate constraints on either the surveyed sites surface or subsurface conditions. A P-wave reflection survey feature was first interpreted as a shallow fault zone but it was later determined to result from a high level of background noise as the acquisition passed through a road intersection. A SH-wave seismic reflection survey feature was interpreted to be a reverse dip-slip fault but targeted drilling showed it was deep local erosion into the bedrock surface. Finally, in an MASW survey, a steeply dipping feature was first interpreted as a bedrock valley. However, later exploratory drilling showed the feature to be a shallow layer of very soft lake sediment that severely damped most of the applied surface wave frequency band. Although initial interpretations were incorrect, they stimulated discussions among geophysicists and geologists and underscored the need for meaningful cooperation and discourse between the scientists before, during, and after geophysical data acquisition.
文摘The loess plateau covering the North Shaanxi slope and Tianhuan depression consists of a regional monocline, high in the east and low in the west, with dips of less than 1^0, Structural movement in this region was weak so that faults and local structures were not well developed. As a result, numerous wide and gentle noses and small traps with magnitudes less than 50 m were developed on the large westward-dipping monocline. Reservoirs, including Mesozoic oil reservoirs and Paleozoic gas reservoirs in the Ordos Basin, are dominantly lithologic with a small number of structural reservoirs. Single reservoirs are characterized as thin with large lateral variations, strong anisotropy, low porosity, low permeability, and low richness. A series of approaches for predicting reservoir thickness, physical properties, and hydrocarbon potential of subtle lithologic reservoirs was established based on the interpretation of erosion surfaces.
文摘Through analyzing the needs of seismic data processing and interpretation,a system model based on CSCW is designed.Using the technology of CSCW to build the environment of cooperative work allows the field data acquisition to possess the functions of remote real-time guidance by experts and remote real-time processing of the data.
文摘3D seismic and petrophysical log data interpretation of reservoir sands in “SIMA” Field, onshore Niger Delta has been undertaken in this study to ascertain the reservoir characteristics in terms of favourable structural and petrophysical parameters suitable for hydrocarbon accumulation and entrapment in the field. Horizon and fault interpretation were carried out for subsurface structural delineation. In all, seven faults (five normal and two listric faults) were mapped in the seismic section. These faults were major structure building faults corresponding to the growth and antithetic faults in the area within the well control. The antithetic fault trending northwest-southeast and the normal fault trending northeast-southwest on the structural high in the section act as good trapping mechanisms for hydrocarbon accumulations in the reservoir. From the manual and auto-tracking methods applied, several horizons were identified and mapped. The section is characterized by high amplitude with moderate-to-good continuity reflections appearing parallel to sub-parallel, mostly disturbed by some truncations which are more fault related than lithologic heterogeneity. The southwestern part is, however, characterized by low-to-high or variable amplitude reflections with poor-to-low continuity. Normal faults linked to roll-over anticlines were identified. Some fault truncations were observed due to lithologic heterogeneity. The combination of these faults acts as good traps for hydrocarbon accumulations in the reservoir. Reservoir favourable petrophysical qualities, having average NTG, porosity, permeability and water saturation of 5 m, 0.20423, 1128.219 kD and 0.458 respectively.
文摘Modem oil industry is on the way of complication of the geological structure to use the latest technologies to analyze available geological and geophysical algorithm---continuous wavelet transform in example of synthetic and real data. of the deposits. This trend requires specialists information. The article describes a new
基金financially supported by National 863 Program (Grants No.2006AA 09A 102-09)National Science and Technology of Major Projects ( Grants No.2008ZX0 5025-001-001)
文摘Irregular seismic data causes problems with multi-trace processing algorithms and degrades processing quality. We introduce the Projection onto Convex Sets （POCS） based image restoration method into the seismic data reconstruction field to interpolate irregularly missing traces. For entire dead traces, we transfer the POCS iteration reconstruction process from the time to frequency domain to save computational cost because forward and reverse Fourier time transforms are not needed. In each iteration, the selection threshold parameter is important for reconstruction efficiency. In this paper, we designed two types of threshold models to reconstruct irregularly missing seismic data. The experimental results show that an exponential threshold can greatly reduce iterations and improve reconstruction efficiency compared to a linear threshold for the same reconstruction result. We also analyze the anti- noise and anti-alias ability of the POCS reconstruction method. Finally, theoretical model tests and real data examples indicate that the proposed method is efficient and applicable.
基金sponsored by the National Science and Technology Major Project(No.2011ZX05023-005-006)
文摘Data mining is the process of extracting implicit but potentially useful information from incomplete, noisy, and fuzzy data. Data mining offers excellent nonlinear modeling and self-organized learning, and it can play a vital role in the interpretation of well logging data of complex reservoirs. We used data mining to identify the lithologies in a complex reservoir. The reservoir lithologies served as the classification task target and were identified using feature extraction, feature selection, and modeling of data streams. We used independent component analysis to extract information from well curves. We then used the branch-and- bound algorithm to look for the optimal feature subsets and eliminate redundant information. Finally, we used the C5.0 decision-tree algorithm to set up disaggregated models of the well logging curves. The modeling and actual logging data were in good agreement, showing the usefulness of data mining methods in complex reservoirs.
基金This research is sponsored by National Natural Science Foundation of China （No. 40272041） and Innovative Foundation of CNPC （N0. 04E702）.
文摘In multi-component seismic exploration, the horizontal and vertical components both contain P- and SV-waves. The P- and SV-wavefields in a seismic record can be separated by their horizontal and vertical displacements when upgoing P- and SV-waves arrive at the sea floor. If the sea floor P wave velocity, S wave velocity, and density are known, the separation can be achieved in ther-p domain. The separated wavefields are then transformed to the time domain. A method of separating P- and SV-wavefields is presented in this paper and used to effectively separate P- and SV-wavefields in synthetic and real data. The application to real data shows that this method is feasible and effective. It also can be used for free surface data.
基金supported by the National Natural Science Foundation of China(Nos.41506046,41376060,41706054)the Opening Foundation of Key Laboratory of Ocean and Marginal Sea Geology,CAS(No.MSGL15-05)+1 种基金WPOS(No.XDA11030102-02)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA13010101)
文摘The Pearl River Estuary(PRE) is located at the onshore-offshore transition zone between South China and South China Sea Basin, and it is of great significant value in discussing tectonic relationships between South China block and South China Sea block and seismic activities along the offshore active faults in PRE. However, the researches on geometric characteristics of offshore faults in this area are extremely lacking. To investigate the offshore fault distribution and their geometric features in the PRE in greater detail, we acquired thirteen seismic reflection profiles in 2015. Combining the analysis of the seismic reflection and free-air gravity anomaly data, this paper revealed the location, continuity, and geometry of the littoral fault zone and other offshore faults in PRE. The littoral fault zone is composed of the major Dangan Islands fault and several parallel, high-angle, normal faults, which mainly trend northeast to northeast-to-east and dip to the southeast with large displacements. The fault zone is divided into three different segments by the northwest-trending faults. Moreover, the basement depth around Dangan Islands is very shallow, while it suddenly increases along the islands westward and southward. These has resulted in the islands and neighboring areas becoming the places where the stress accumulates easily. The seismogenic pattern of this area is closely related to the comprehensive effect of intersecting faults together with the low velocity layer.
基金Mainly presented at the 6-th international meeting of acoustics in Aug. 2003, and The 1999 SPE Asia Pacific Oil and GasConference and Exhibition held in Jakarta, Indonesia, 20-22 April 1999, SPE 54274.
文摘In this paper, a new concept called numerical structure of seismic data is introduced and the difference between numerical structure and numerical value of seismic data is explained. Our study shows that the numerical seismic structure is closely related to oil and gas-bearing reservoir, so it is very useful for a geologist or a geophysicist to precisely interpret the oil-bearing layers from the seismic data. This technology can be applied to any exploration or production stage. The new method has been tested on a series of exploratory or development wells and proved to be reliable in China. Hydrocarbon-detection with this new method for 39 exploration wells on 25 structures indi- cates a success ratio of over 80 percent. The new method of hydrocarbon prediction can be applied for: (1) depositional environment of reservoirs with marine fades, delta, or non-marine fades (including fluvial facies, lacustrine fades); (2) sedimentary rocks of reservoirs that are non-marine clastic rocks and carbonate rock; and (3) burial depths range from 300 m to 7000 m, and the minimum thickness of these reservoirs is over 8 m (main frequency is about 50 Hz).
基金Funded by the Project of China Geological Survey (No.1212010916040)the Sichuan Science and Technology Program (No.2017JY0051)the Sichuan Science and Technology Program (No.2018GZ0200)
文摘The field seismic data is disturbed by the interferential information, which has low signal to noise ratio (SNR). That is disadvantage for seismic data interpretation. So it is important to remove the noise of seismic data. Independent component analysis (ICA) can remove most of the noise interference. However, ICA has some defects in noise reduction, because it needs some conditions that seismic data is independent reciprocally for denoising. To solve these defects, this paper proposes an improved ICA algorithm to noise reduction. Through simulation experiments, it can be obtained that the best decomposition levels of the new algorithm is 3. At last, the proposed improved ICA is applied to deal with the actual seismic data. The results show that it can effectively eliminate most of seismic noise such as random noise, linear interference, surface waves, and so on. The improved ICA is not only easy to denoising, but also has excellent mathematical theoretical properties.
