The connectivity of sandbodies is a key constraint to the exploration effectiveness of Bohai A Oilfield.Conventional connectivity studies often use methods such as seismic attribute fusion,while the development of con...The connectivity of sandbodies is a key constraint to the exploration effectiveness of Bohai A Oilfield.Conventional connectivity studies often use methods such as seismic attribute fusion,while the development of contiguous composite sandbodies in this area makes it challenging to characterize connectivity changes with conventional seismic attributes.Aiming at the above problem in the Bohai A Oilfield,this study proposes a big data analysis method based on the Deep Forest algorithm to predict the sandbody connectivity.Firstly,by compiling the abundant exploration and development sandbodies data in the study area,typical sandbodies with reliable connectivity were selected.Then,sensitive seismic attribute were extracted to obtain training samples.Finally,based on the Deep Forest algorithm,mapping model between attribute combinations and sandbody connectivity was established through machine learning.This method achieves the first quantitative determination of the connectivity for continuous composite sandbodies in the Bohai Oilfield.Compared with conventional connectivity discrimination methods such as high-resolution processing and seismic attribute analysis,this method can combine the sandbody characteristics of the study area in the process of machine learning,and jointly judge connectivity by combining multiple seismic attributes.The study results show that this method has high accuracy and timeliness in predicting connectivity for continuous composite sandbodies.Applied to the Bohai A Oilfield,it successfully identified multiple sandbody connectivity relationships and provided strong support for the subsequent exploration potential assessment and well placement optimization.This method also provides a new idea and method for studying sandbody connectivity under similar complex geological conditions.展开更多
Core, well logging and seismic data were used to investigate sandbody architectural characteristics within Lower Member of Minghuazhen Formation in Neogene, Bohai BZ25 Oilfield, and to analyze the sedimentary microfac...Core, well logging and seismic data were used to investigate sandbody architectural characteristics within Lower Member of Minghuazhen Formation in Neogene, Bohai BZ25 Oilfield, and to analyze the sedimentary microfacies, distribution and internal architecture characteristics of the bar finger within shoal water delta front. The branched sand body within shoal water delta front is the bar finger, consisting of the mouth bar, distributary channel over bar, and levee. The distributary channel cuts through the mouth bar, and the thin levee covers the mouth bar which is located at both sides of distributary channel. The bar finger is commonly sinuous and its sinuosity increases basinward. The distributary channel changes from deeply incising the mouth bar to shallowly incising top of the mouth bar.The aspect ratio ranges from 25 to 50 and there is a double logarithmic linear positive relationship between the width and thickness for the bar finger, which is controlled by base-level changing in study area. For the bar finger, injection and production in the same distributary channel should be avoided during water flooding development. In addition, middle–upper distributary channel and undrilled mouth bar are focus of tapping remaining oil.展开更多
Objective China＇s petroleum exploration has entered a new stage of finding deeply buried thin sandbodies lbr the abundant oil resources they contain. Here thin sandbodies refer to those less than 10 m in thickness, ...Objective China＇s petroleum exploration has entered a new stage of finding deeply buried thin sandbodies lbr the abundant oil resources they contain. Here thin sandbodies refer to those less than 10 m in thickness, or even less than 1-2 m. It is difficult to depict thin-layer sandbodies of different genetic types using conventional core, well logging and seismic data due to their limited vertical resolution in petroliferous basins. However, seismic sedimentology provides a new research method especially tbr thin sandbody interpretation, i.e., validating interpreted sedimentary sandbodies from 3D seismic data based on horizontal resolution, stratal slice and seismic geomorphology interpretation. At present, a series of studies on seismic sedimentology in North America marine basins and elsewhere have been completed successfully and are relevant to the exploration and development of oil and gas fields.展开更多
文摘The connectivity of sandbodies is a key constraint to the exploration effectiveness of Bohai A Oilfield.Conventional connectivity studies often use methods such as seismic attribute fusion,while the development of contiguous composite sandbodies in this area makes it challenging to characterize connectivity changes with conventional seismic attributes.Aiming at the above problem in the Bohai A Oilfield,this study proposes a big data analysis method based on the Deep Forest algorithm to predict the sandbody connectivity.Firstly,by compiling the abundant exploration and development sandbodies data in the study area,typical sandbodies with reliable connectivity were selected.Then,sensitive seismic attribute were extracted to obtain training samples.Finally,based on the Deep Forest algorithm,mapping model between attribute combinations and sandbody connectivity was established through machine learning.This method achieves the first quantitative determination of the connectivity for continuous composite sandbodies in the Bohai Oilfield.Compared with conventional connectivity discrimination methods such as high-resolution processing and seismic attribute analysis,this method can combine the sandbody characteristics of the study area in the process of machine learning,and jointly judge connectivity by combining multiple seismic attributes.The study results show that this method has high accuracy and timeliness in predicting connectivity for continuous composite sandbodies.Applied to the Bohai A Oilfield,it successfully identified multiple sandbody connectivity relationships and provided strong support for the subsequent exploration potential assessment and well placement optimization.This method also provides a new idea and method for studying sandbody connectivity under similar complex geological conditions.
基金Supported by the National Natural Science Foundation of China(41772101)China National Science and Technology Major Project(2017ZX05009001-002)
文摘Core, well logging and seismic data were used to investigate sandbody architectural characteristics within Lower Member of Minghuazhen Formation in Neogene, Bohai BZ25 Oilfield, and to analyze the sedimentary microfacies, distribution and internal architecture characteristics of the bar finger within shoal water delta front. The branched sand body within shoal water delta front is the bar finger, consisting of the mouth bar, distributary channel over bar, and levee. The distributary channel cuts through the mouth bar, and the thin levee covers the mouth bar which is located at both sides of distributary channel. The bar finger is commonly sinuous and its sinuosity increases basinward. The distributary channel changes from deeply incising the mouth bar to shallowly incising top of the mouth bar.The aspect ratio ranges from 25 to 50 and there is a double logarithmic linear positive relationship between the width and thickness for the bar finger, which is controlled by base-level changing in study area. For the bar finger, injection and production in the same distributary channel should be avoided during water flooding development. In addition, middle–upper distributary channel and undrilled mouth bar are focus of tapping remaining oil.
基金financially supported by the National Science Foundation of China(Grant No.41272133)
文摘Objective China＇s petroleum exploration has entered a new stage of finding deeply buried thin sandbodies lbr the abundant oil resources they contain. Here thin sandbodies refer to those less than 10 m in thickness, or even less than 1-2 m. It is difficult to depict thin-layer sandbodies of different genetic types using conventional core, well logging and seismic data due to their limited vertical resolution in petroliferous basins. However, seismic sedimentology provides a new research method especially tbr thin sandbody interpretation, i.e., validating interpreted sedimentary sandbodies from 3D seismic data based on horizontal resolution, stratal slice and seismic geomorphology interpretation. At present, a series of studies on seismic sedimentology in North America marine basins and elsewhere have been completed successfully and are relevant to the exploration and development of oil and gas fields.
