Quantitative Prediction of Lower Order Faults Based on the Finite Element Method: A Case Study of the M35 Fault Block in the Western Hanliu Fault Zone in the Gaoyou Sag, East China. Issue 10 (3rd October 2018) - Liu, Jingshou; Ding, Wenlong; Dai, Junsheng; Wu, Zhonghu; Yang, Haimeng
Abstract: Lower order faults (LOFs) are characterized by small‐scale, strong concealment and difficult to identify in seismic data, which affects the accuracy of LOF interpretation. Due to the quality of the seismic data in the M35 fault block of the Gaoyou sag, Subei basin, the direction of the LOFs cannot be accurately identified, leading to the unclear relationship between the injection and production wells in the local oil fields and affecting the development of the remaining oil. In this paper, the formation mechanism of LOFs in the M35 fault block is determined from analysis of the fault activity and tectonic evolution, and a finite element geomechanical model is established to simulate the paleostress field during the formation of the LOFs. Based on the relationship between the areal density of LOFs and the stress parameters, the regions of LOF development are predicted by the minimum principal stress, the maximum and minimum principal stress difference (Δ σ ), normal stress ( σ n ), and the strain energy density; the shear stresses are used to predict the dip direction of the LOFs. Through the coordinate system transformation of the principal stress directions, the strikes of the LOFs are quantitatively predicted. Finally, the reliability of the prediction results is verified by the latest structural map of the M35 fault block. The method proposed in this paper can be widely applied to the quantitative prediction of multiple parameters of LOFs in complex fault blocks. Key Points: Quantitative prediction of lower order faults is based on the finite element method The regions of LOF development are predicted by the minimum principal stress, stress difference, normal stress, and the strain energy density The shear stresses are used to predict the dip direction of the LOFs