Data-driven based variable geometry design

Conventionally, the method to make up for the missing data of middle-shallow layer in the obstacle area is by variable geometry, for example, deviating physical points and adding sources and receivers. And the missing data of middle-shallow layer is evaluated according to the effective coverage of the target layer. Since the traditional method doesn't consider the actual seismic data, it is impossible to actually predict the gap of section and the imaging effect. The paper proposes the evaluation method of data-driven based variable geometry: Firstly, the obstacle avoidance design is realized according to the coordinate range and safe distance of the obstacle area; Secondly, the local similarity of each common image gather (CIG) is calculated, and the contribution of the sources and receivers to the target area is also calculated; Thirdly, according to the variable geometry design, choose the required trace to perform sorting and stacking according to the contribution of the sources and receivers in the CIG, the stack data volume of the whole work area is generated; finally, evaluate the missing data in the obstacle area by the extracted seismic stacked sections in different direction and guide the designer in the infilling plan. Meanwhile, for area with very low signal to noise ratio (SNR), the new method can be used to evaluate the imaging potential and guide the survey design. The new method has achieved very good effect in the production, and the analysis result is very consistent with the processed result of the actual seismic data.