In the Ken 71 development block, fluvial facies of the Neogene Guantao Formation and delta facies of the Paleogene Dongying Formation are the main pay beds. It is a multiple oil and water system which is complicated b...In the Ken 71 development block, fluvial facies of the Neogene Guantao Formation and delta facies of the Paleogene Dongying Formation are the main pay beds. It is a multiple oil and water system which is complicated by faults. Characteristics of the block include a dense well network, thin reservoirs, complicated horizontal relationships, and small velocity difference between reservoir and non-reservoir. Therefore, it is difficult to conduct detailed reservoir description for subsequent development project adjustment. We demonstrate a stochastic seismic inversion which aims at detailed reservoir description. It is a technology which utilizes multiple wells, seismic data, and geological calibration and integrates with 3D structural interpretation results to build a 3D multi-fault detailed and constrained geological model. On this basis, we adopted stochastic seismic inversion to conduct a multi-stratum parameters inversion such as impedance and lithology. As a result, thin interbedded strata in the block were well resolved and the results demonstrated the importance of detailed reservoir inversion for oilfield development.展开更多
In order to improve the fine structure inversion ability of igneous rocks for the exploration of underlying strata, based on particle swarm optimization(PSO), we have developed a method for seismic wave impedance inve...In order to improve the fine structure inversion ability of igneous rocks for the exploration of underlying strata, based on particle swarm optimization(PSO), we have developed a method for seismic wave impedance inversion. Through numerical simulation, we tested the effects of different algorithm parameters and different model parameterization methods on PSO wave impedance inversion, and analyzed the characteristics of PSO method. Under the conclusions drawn from numerical simulation, we propose the scheme of combining a cross-moving strategy based on a divided block model and high-frequency filtering technology for PSO inversion. By analyzing the inversion results of a wedge model of a pitchout coal seam and a coal coking model with igneous rock intrusion, we discuss the vertical and horizontal resolution, stability and reliability of PSO inversion. Based on the actual seismic and logging data from an igneous area, by taking a seismic profile through wells as an example, we discuss the characteristics of three inversion methods, including model-based wave impedance inversion, multi-attribute seismic inversion based on probabilistic neural network(PNN) and wave impedance inversion based on PSO.And we draw the conclusion that the inversion based on PSO method has a better result for this igneous area.展开更多
文摘In the Ken 71 development block, fluvial facies of the Neogene Guantao Formation and delta facies of the Paleogene Dongying Formation are the main pay beds. It is a multiple oil and water system which is complicated by faults. Characteristics of the block include a dense well network, thin reservoirs, complicated horizontal relationships, and small velocity difference between reservoir and non-reservoir. Therefore, it is difficult to conduct detailed reservoir description for subsequent development project adjustment. We demonstrate a stochastic seismic inversion which aims at detailed reservoir description. It is a technology which utilizes multiple wells, seismic data, and geological calibration and integrates with 3D structural interpretation results to build a 3D multi-fault detailed and constrained geological model. On this basis, we adopted stochastic seismic inversion to conduct a multi-stratum parameters inversion such as impedance and lithology. As a result, thin interbedded strata in the block were well resolved and the results demonstrated the importance of detailed reservoir inversion for oilfield development.
基金provided by the National Science and Technology Major Project(No.2011ZX05004-004)China National Petroleum Corporation Key Projects(No.2014E2105)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)
文摘In order to improve the fine structure inversion ability of igneous rocks for the exploration of underlying strata, based on particle swarm optimization(PSO), we have developed a method for seismic wave impedance inversion. Through numerical simulation, we tested the effects of different algorithm parameters and different model parameterization methods on PSO wave impedance inversion, and analyzed the characteristics of PSO method. Under the conclusions drawn from numerical simulation, we propose the scheme of combining a cross-moving strategy based on a divided block model and high-frequency filtering technology for PSO inversion. By analyzing the inversion results of a wedge model of a pitchout coal seam and a coal coking model with igneous rock intrusion, we discuss the vertical and horizontal resolution, stability and reliability of PSO inversion. Based on the actual seismic and logging data from an igneous area, by taking a seismic profile through wells as an example, we discuss the characteristics of three inversion methods, including model-based wave impedance inversion, multi-attribute seismic inversion based on probabilistic neural network(PNN) and wave impedance inversion based on PSO.And we draw the conclusion that the inversion based on PSO method has a better result for this igneous area.
