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Application Of Prestack Stochastic Inversion Technique In Fine Characterization Of Thin-bedded Sandbody

Posted on:2024-06-08Degree:DoctorType:Dissertation
Country:ChinaCandidate:Z ChenFull Text:PDF
GTID:1520307148484014Subject:Mineral prospecting and exploration
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With the decrease of conventional oil and gas reservoir production,the focus of oil and gas reservoir exploration has gradually shifted to the search for subtle oil and gas reservoir,thin interbed oil and gas reservoir and the fine characterization of underground distribution of oil and gas reservoir,which requires the improvement of corresponding exploration technology.Seismic inversion technology can realize the complementary advantages of logging and seismic,significantly improve the longitudinal resolution of 3D seismic data,and can adapt to more and more complex geological environment and exploration tasks.Xihu Sag is the main oil-bearing sag found in the East China Sea shelf basin,which has excellent exploration potential Pinghu Formation is the main oil-bearing and gas-bearing interval in Xihu Depression.Due to the interaction of rivers and tides,the Marine and continental transitional facies sedimentary system is widely developed in Pinghu Formation.The lithology association is characterized by the thin interbed of sand,mud and coal in the delta-tidal flat transitional facies.In the middle of the Baoshu slope belt in the Xihu Sag,WYT area,the sandstone of Pinghu Formation in this area is buried deeply,thin sand bodies are multi-layered,fast transverse changes,sand and mudstone interbedding develops and coal seam interferes,and the overall physical property is strongly heterogeneous.The p-wave impedance range of tight sandstone and mudstone with low porosity and low permeability is overlapped.Conventional post-stack seismic inversion method has low resolution and strong multi-solution,which depends on the initial model,and cannot be applied to thin bed prediction in this area.In view of these technical difficulties,how to maximize the accuracy of reservoir prediction and delineate favorable zones are urgent problems to be solved in the exploration and development of this area.Guided by the theory of sequence stratigraphy and sedimentology,this paper constructs the corresponding geophysical model on the basis of the establishment of the high-precision geological model of sequence stratigraphy and sedimentary facies,and combines the inversion method based on the sedimentary facies model constraint of prestack simultaneous inversion and nonlinear stochastic simulation theory to quantitatively predict the sand body thickness of Pinghu Formation reservoir in WYT area.Combined with the structural characteristics and the law of porosity and permeability,the advantageous target area is evaluated comprehensively,which effectively reduces the multi-solution of seismic inversion and improves the effect of earthquake prediction essentially FThe main research contents and conclusions are as follows:(1)Using core,seismic and drilling and logging data comprehensively,the main sequence interface of Pinghu Formation in WYT and surrounding areas of Xihu Depression was redefined,sand body correlation was carried out under isochronous lattice,the isochronous stratigraphic framework of Pinghu Formation was established,and sedimentary geological model and sequence control sand model map which can guide seismic inversion sand body prediction were extracted,including the following five kinds:There are graben-barrier type,transition belt type and multi-fault slope type in the fault control period of Pingxia member.Gentle slope type and multistage slope type in the mid-upper slope control period.(2)A detailed optimization process of pre-stack seismic data was established in the study area,and the Radon transform and residual static correction algorithms to eliminate random noise and improve the signal to noise ratio of pre-stack CRP were implemented through independent programming.The complex multiple wave combination suppression and wavelet zero phase defrothing processing technology were used for broadband amplitude-preserving processing,which effectively removed multiple waves and broadened the low and high frequency information.It provides good basic data for subsequent inversion.The parameters of each step in the process of pre-stack inversion are analyzed in detail and the rationality of the inversion results is guaranteed by various quality control means.(3)The prediction accuracy and efficiency of S-wave velocity can be effectively improved by using the depth feedforward neural network method.The correlation performance between the predicted S-wave and the measured S-wave reaches 0.978,which overcomes the defect of incomplete S-wave data in the study area and provides necessary basic data for simultaneous pre-stack inversion.Moreover,the sensitive elastic parameters of the reservoir are analyzed in the study area.The Pinghu Formation sandstone is characterized by low Poisson’s ratio,low transverse and transverse wave velocity ratio,low density and high Young’s modulus,which provides an accurate threshold value for the subsequent quantitative interpretation of random inversion results.(4)Prestack simultaneous inversion is an inversion method based on prestack track set,which has higher transverse resolution and lower longitudinal resolution.Random inversion is a kind of inversion method which takes logging data as the simulation control point and is constrained by seismic data between wells.It retains the characteristics of logging data and some seismic data,and has a high longitudinal resolution and a certain horizontal resolution.The combination of the two inversion methods can learn from each other and obtain the lithology prediction results with high vertical and horizontal resolution,which can accurately characterize thin sandstone reservoirs and solve the problems of thin reservoir identification and reservoir description.(5)On the basis of petrophysical analysis and geological understanding,the quantitative prediction of sand body thickness of 12 sand groups in Pinghu Formation is carried out by using prestack random inversion.The predicted results are more than95% consistent with the actual drilling results,and the controlling effects of global sea level,regional structure,paleoclimate and paleomorphology on the development and evolution of sand bodies in the study area are systematically analyzed.The inversion results show that the spatial distribution of sand bodies in Pinghu Formation changes from NE-SE to NW-SE.The thickness of sand bodies in lower Pinghu member is large,and the horizontal continuity is good.Mudstone is the main sandbody in the middle section,and the sandbody is isolated and has poor continuity.In the upper section,there are more sand bodies,the thickness of single layer is thin,and the transverse continuity is good.The vertical resolution of sand body prediction results can reach 1~2m.The pre-stack random inversion effectively solves the problem of thin layer sand body identification in WYT area,Xihu Sag,and provides important support for favorable reservoir prediction in the study area.(6)Based on the petrophysical analysis,the porosity and permeability of the study area were reasonably predicted by using the multi-attribute fitting technique,and combined with the sedimentary,structural and spatial distribution characteristics of sand bodies,the favorable area of composite trap was predicted.The results show that the favorable areas of the middle and lower Pinghu Formation are mainly distributed in the area south of well W-3 to well W5-W2 in the middle and northern tectonic high,and the W-4 well in the northeast sub-high with thick sand bodies and better composite traps and pore permeability,which are favorable areas for further exploration.Sand bodies are developed from the north of well W-2 to the south of well W-4 in the upper Pinghu Formation,but the composite traps are poor,which are mainly structural traps and can also be used as the next exploration target.
Keywords/Search Tags:WYT area of Xihu Sag, Pinghu Formation, Reservoir prediction, Prestack random inversion, Shear wave prediction, Sand body prediction
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