Due to the complexity and variability of carbonate formation leakage zones, lost circulation prediction and control is one of the major challenges of carbonate drilling. It raises well-control risks and production exp...Due to the complexity and variability of carbonate formation leakage zones, lost circulation prediction and control is one of the major challenges of carbonate drilling. It raises well-control risks and production expenses. This research utilizes the H oilfield as an example, employs seismic features to analyze mud loss prediction, and produces a complete set of pre-drilling mud loss prediction solutions. Firstly, 16seismic attributes are calculated based on the post-stack seismic data, and the mud loss rate per unit footage is specified. The sample set is constructed by extracting each attribute from the seismic trace surrounding 15 typical wells, with a ratio of 8:2 between the training set and the test set. With the calibration results for mud loss rate per unit footage, the nonlinear mapping relationship between seismic attributes and mud loss rate per unit size is established using the mixed density network model.Then, the influence of the number of sub-Gausses and the uncertainty coefficient on the model's prediction is evaluated. Finally, the model is used in conjunction with downhole drilling conditions to assess the risk of mud loss in various layers and along the wellbore trajectory. The study demonstrates that the mean relative errors of the model for training data and test data are 6.9% and 7.5%, respectively, and that R2is 90% and 88%, respectively, for training data and test data. The accuracy and efficacy of mud loss prediction may be greatly enhanced by combining 16 seismic attributes with the mud loss rate per unit footage and applying machine learning methods. The mud loss prediction model based on the MDN model can not only predict the mud loss rate but also objectively evaluate the prediction based on the quality of the data and the model.展开更多
The carbonate reservoirs in the Tarim Basin are characterized by anisotropy and strong heterogeneity.Combined with an integrated analysis of data from seismic,geology,and drilling results,a series of attributes which ...The carbonate reservoirs in the Tarim Basin are characterized by anisotropy and strong heterogeneity.Combined with an integrated analysis of data from seismic,geology,and drilling results,a series of attributes which are suitable for fractured and caved carbonate reservoir prediction is discussed,including amplitude,coherence analysis,spectra decomposition,seismic absorption attenuation analysis and impedance inversion.Moreover,3-D optimization of these attributes is achieved by integration of multivariate discriminant analysis and principle component analysis,where the logging data are taken as training samples.Using the optimized results,the spatial distribution and configuration features of the caved reservoirs can be characterized in detail.This technique not only improves the understanding of the spatial distribution of current reservoirs but also provides a significant basis for the discovery and production of carbonate reservoirs in the Tarim Basin.展开更多
The theoretical and practical analysis of reservoir thickness and oil-bearing information of thin reservoirs is performed by using seismic attributes and forward modelling. The results show that thin reservoir can be ...The theoretical and practical analysis of reservoir thickness and oil-bearing information of thin reservoirs is performed by using seismic attributes and forward modelling. The results show that thin reservoir can be recognized using seismic attributes technique when its thickness is less than 1/4 of wavelength. Through analyzing the influence of tuning effect, the relationship between thin layer thickness and tuning amplitude is well revealed. A precise structure interpretation is conducted using relative amplitude preserved high-resolution seismic data. By taking the geologic condition and well data into account, the distribution of oil and gas of HD4 oilfield is analyzed and predicted. based on seismic attributes. The result is helpful to promote the exploration and development in this oilfield.展开更多
In contrast to marine deposits, continental deposits in China are characterized by diverse sedimentary types, rapid changes in sedimentary facies, complex lithology, and thin, small sand bodies. In seismic sedimentolo...In contrast to marine deposits, continental deposits in China are characterized by diverse sedimentary types, rapid changes in sedimentary facies, complex lithology, and thin, small sand bodies. In seismic sedimentology studies on continental lacustrine basins, new thinking and more detailed and effective technical means are needed to generate lithological data cubes and conduct seismic geo- morphologic analyses. Based on a series of tests and studies, this paper presents the concepts of time-equivalent seismic attributes and seismic sedimentary bodies and a ＂four-step approach＂ for the seismic sedimentologic study of conti- nental basins： Step 1, build a time-equivalent stratigraphic framework based on vertical analysis and horizontal corre- lation of lithofacies, electrofacies, seismic facies, and pale- ontological combinations; Step 2, further build a sedimentary facies model based on the analysis of single- well facies with outcrop, coring, and lab test data; Step 3, convert the seismic data into a lithological data cube reflecting different lithologies by means of seismic tech- niques; and Step 4, perform a time-equivalent attribute analysis and convert the planar attribute into a sedimentary facies map under the guidance of the sedimentary facies model. The whole process, highlighting the verification and calibration of geological data, is an iteration and feedback procedure of geoseismic data. The key technologies include the following： （1） a seismic data-lithology conversion technique applicable to complex lithology, which can convert the seismic reflection from interface types to rock layers; and （2） time-equivalent seismic unit analysis and a time- equivalent seismic attribute extraction technique. Finally, this paper demonstrates the validity of the approach with an example from the Qikou Sag in the Bohai Bay Basin and subsequent drilling results.展开更多
The first generation coherence algorithm （the C1 algorithm） that calculates the coherence of seismic data in-line and cross-line was developed using statistical cross-correlation theory, and it has the limitation th...The first generation coherence algorithm （the C1 algorithm） that calculates the coherence of seismic data in-line and cross-line was developed using statistical cross-correlation theory, and it has the limitation that the technique can only be applied to horizons. Based on the texture technique, the texture coherence algorithm uses seismic information in different directions and differences among multiple traces. It can not only calculate seismic coherence in in-line and cross-line directions but also in all other directions. In this study, we suggested first an optimization method and a criterion for constructing the gray level co-occurrence matrix of the seismic texture coherence algorithm. Then the co-occurrence matrix was prepared to evaluate differences among multiple traces. Compared with the C1 algorithm, the seismic texture coherence algorithm suggested in this paper is better than the C1 in its information extraction and application. Furthermore, it implements the multi-direction information fusion and it, also has the advantage of simplicity and effectiveness, and improves the resolution of the seismic profile. Application of the method to field data shows that the texture coherence attribute is superior to that of C 1 and that it has merits in identification of faults and channels.展开更多
Reflected wave seismology has the following defects:the acquisition design is based on the assumption of layered media,the signal processing suppresses weak signals such as diffracted wave and scattered wave,and the s...Reflected wave seismology has the following defects:the acquisition design is based on the assumption of layered media,the signal processing suppresses weak signals such as diffracted wave and scattered wave,and the seismic wave band after the image processing is narrow.They limit the full utilization of broadband raw data.The concept of full wave seismic exploration is redefined based on the idea of balanced utilization of reflected wave,diffracted wave and scattered wave information,its characteristics and adaptive conditions are clarified.A set of key technologies suitable for full wave seismic exploration are put forward.During seismic acquisition period,it is necessary to adopt multi geometry,i.e.embed small bin,small offset and small channel interval data in conventional geometry.By discretizing of common midpoint(CMP)gathers,small offset with high coverage,the weak signals such as diffracted wave and scattered wave in the raw seismic data can be enhanced.During seismic processing,the signal and noise in the original seismic data need to be redefined at first.The effective signals of seismic data are enhanced through merging of multi-geometry data.By means of differential application of data with different bin sizes and different arrangement modes,different regimes of seismic waves can be effectively decomposed and imaged separately.During seismic interpretation stage,making the most of the full wave seismic data,and adopting well-seismic calibration on multi-scale and multi-dimension,the seismic attributes in multi-regimes and multi-domains are interpreted to reveal interior information of complex lithology bodies and improve the lateral resolution of non-layered reservoirs.展开更多
The distribution of sedimentary microfacies in the eighth member of the Shihezi formation（the H8 member） in the Sul4 3D seismic test area was investigated.A Support Vector Machine（SVM） model was introduced for the...The distribution of sedimentary microfacies in the eighth member of the Shihezi formation（the H8 member） in the Sul4 3D seismic test area was investigated.A Support Vector Machine（SVM） model was introduced for the first time as a way of predicting sandstone thickness in the study area.The model was constructed by analysis and optimization of measured seismic attributes.The distribution of the sedimentary microfacies in the study area was determined from predicted sandstone thickness and an analysis of sedimentary characteristics of the area.The results indicate that sandstone thickness predictions in the study area using an SVM method are good.The distribution of the sedimentary microfacies in the study area has been depicted at a fine scale.展开更多
基金the financially supported by the National Natural Science Foundation of China(Grant No.52104013)the China Postdoctoral Science Foundation(Grant No.2022T150724)。
文摘Due to the complexity and variability of carbonate formation leakage zones, lost circulation prediction and control is one of the major challenges of carbonate drilling. It raises well-control risks and production expenses. This research utilizes the H oilfield as an example, employs seismic features to analyze mud loss prediction, and produces a complete set of pre-drilling mud loss prediction solutions. Firstly, 16seismic attributes are calculated based on the post-stack seismic data, and the mud loss rate per unit footage is specified. The sample set is constructed by extracting each attribute from the seismic trace surrounding 15 typical wells, with a ratio of 8:2 between the training set and the test set. With the calibration results for mud loss rate per unit footage, the nonlinear mapping relationship between seismic attributes and mud loss rate per unit size is established using the mixed density network model.Then, the influence of the number of sub-Gausses and the uncertainty coefficient on the model's prediction is evaluated. Finally, the model is used in conjunction with downhole drilling conditions to assess the risk of mud loss in various layers and along the wellbore trajectory. The study demonstrates that the mean relative errors of the model for training data and test data are 6.9% and 7.5%, respectively, and that R2is 90% and 88%, respectively, for training data and test data. The accuracy and efficacy of mud loss prediction may be greatly enhanced by combining 16 seismic attributes with the mud loss rate per unit footage and applying machine learning methods. The mud loss prediction model based on the MDN model can not only predict the mud loss rate but also objectively evaluate the prediction based on the quality of the data and the model.
基金co-supported by the National Basic Resarch Program of China (Grant No.2011CB201103)the National Scince and Technology Major Project (Grant No.2011ZX05004003)
文摘The carbonate reservoirs in the Tarim Basin are characterized by anisotropy and strong heterogeneity.Combined with an integrated analysis of data from seismic,geology,and drilling results,a series of attributes which are suitable for fractured and caved carbonate reservoir prediction is discussed,including amplitude,coherence analysis,spectra decomposition,seismic absorption attenuation analysis and impedance inversion.Moreover,3-D optimization of these attributes is achieved by integration of multivariate discriminant analysis and principle component analysis,where the logging data are taken as training samples.Using the optimized results,the spatial distribution and configuration features of the caved reservoirs can be characterized in detail.This technique not only improves the understanding of the spatial distribution of current reservoirs but also provides a significant basis for the discovery and production of carbonate reservoirs in the Tarim Basin.
文摘The theoretical and practical analysis of reservoir thickness and oil-bearing information of thin reservoirs is performed by using seismic attributes and forward modelling. The results show that thin reservoir can be recognized using seismic attributes technique when its thickness is less than 1/4 of wavelength. Through analyzing the influence of tuning effect, the relationship between thin layer thickness and tuning amplitude is well revealed. A precise structure interpretation is conducted using relative amplitude preserved high-resolution seismic data. By taking the geologic condition and well data into account, the distribution of oil and gas of HD4 oilfield is analyzed and predicted. based on seismic attributes. The result is helpful to promote the exploration and development in this oilfield.
基金supported by the Key Scientific and Technological Project‘‘Seismic-Sedimentology Software System Investigation and Application’’of Petro China Company Limited(2012B-3709)
文摘In contrast to marine deposits, continental deposits in China are characterized by diverse sedimentary types, rapid changes in sedimentary facies, complex lithology, and thin, small sand bodies. In seismic sedimentology studies on continental lacustrine basins, new thinking and more detailed and effective technical means are needed to generate lithological data cubes and conduct seismic geo- morphologic analyses. Based on a series of tests and studies, this paper presents the concepts of time-equivalent seismic attributes and seismic sedimentary bodies and a ＂four-step approach＂ for the seismic sedimentologic study of conti- nental basins： Step 1, build a time-equivalent stratigraphic framework based on vertical analysis and horizontal corre- lation of lithofacies, electrofacies, seismic facies, and pale- ontological combinations; Step 2, further build a sedimentary facies model based on the analysis of single- well facies with outcrop, coring, and lab test data; Step 3, convert the seismic data into a lithological data cube reflecting different lithologies by means of seismic tech- niques; and Step 4, perform a time-equivalent attribute analysis and convert the planar attribute into a sedimentary facies map under the guidance of the sedimentary facies model. The whole process, highlighting the verification and calibration of geological data, is an iteration and feedback procedure of geoseismic data. The key technologies include the following： （1） a seismic data-lithology conversion technique applicable to complex lithology, which can convert the seismic reflection from interface types to rock layers; and （2） time-equivalent seismic unit analysis and a time- equivalent seismic attribute extraction technique. Finally, this paper demonstrates the validity of the approach with an example from the Qikou Sag in the Bohai Bay Basin and subsequent drilling results.
基金supported by National "973" Program (No. 2013CB228600)
文摘The first generation coherence algorithm （the C1 algorithm） that calculates the coherence of seismic data in-line and cross-line was developed using statistical cross-correlation theory, and it has the limitation that the technique can only be applied to horizons. Based on the texture technique, the texture coherence algorithm uses seismic information in different directions and differences among multiple traces. It can not only calculate seismic coherence in in-line and cross-line directions but also in all other directions. In this study, we suggested first an optimization method and a criterion for constructing the gray level co-occurrence matrix of the seismic texture coherence algorithm. Then the co-occurrence matrix was prepared to evaluate differences among multiple traces. Compared with the C1 algorithm, the seismic texture coherence algorithm suggested in this paper is better than the C1 in its information extraction and application. Furthermore, it implements the multi-direction information fusion and it, also has the advantage of simplicity and effectiveness, and improves the resolution of the seismic profile. Application of the method to field data shows that the texture coherence attribute is superior to that of C 1 and that it has merits in identification of faults and channels.
基金Supported by the Sinopec Ministry of Science and Technology Project(P21038-3)。
文摘Reflected wave seismology has the following defects:the acquisition design is based on the assumption of layered media,the signal processing suppresses weak signals such as diffracted wave and scattered wave,and the seismic wave band after the image processing is narrow.They limit the full utilization of broadband raw data.The concept of full wave seismic exploration is redefined based on the idea of balanced utilization of reflected wave,diffracted wave and scattered wave information,its characteristics and adaptive conditions are clarified.A set of key technologies suitable for full wave seismic exploration are put forward.During seismic acquisition period,it is necessary to adopt multi geometry,i.e.embed small bin,small offset and small channel interval data in conventional geometry.By discretizing of common midpoint(CMP)gathers,small offset with high coverage,the weak signals such as diffracted wave and scattered wave in the raw seismic data can be enhanced.During seismic processing,the signal and noise in the original seismic data need to be redefined at first.The effective signals of seismic data are enhanced through merging of multi-geometry data.By means of differential application of data with different bin sizes and different arrangement modes,different regimes of seismic waves can be effectively decomposed and imaged separately.During seismic interpretation stage,making the most of the full wave seismic data,and adopting well-seismic calibration on multi-scale and multi-dimension,the seismic attributes in multi-regimes and multi-domains are interpreted to reveal interior information of complex lithology bodies and improve the lateral resolution of non-layered reservoirs.
基金Financial support for this work,provided by the Major National Science and Technology Special Projects(No.2008ZX05008)
文摘The distribution of sedimentary microfacies in the eighth member of the Shihezi formation（the H8 member） in the Sul4 3D seismic test area was investigated.A Support Vector Machine（SVM） model was introduced for the first time as a way of predicting sandstone thickness in the study area.The model was constructed by analysis and optimization of measured seismic attributes.The distribution of the sedimentary microfacies in the study area was determined from predicted sandstone thickness and an analysis of sedimentary characteristics of the area.The results indicate that sandstone thickness predictions in the study area using an SVM method are good.The distribution of the sedimentary microfacies in the study area has been depicted at a fine scale.
