Analysis of acquisition parameters and geometry quality

High-quality seismic geometry is the key to obtain high-quality seismic data, and can affect the accuracy of data processing and imaging. Based on the analysis of the relationship between the quality of the geometry and the four acquisition parameters(the number of traces, shot line spacing, and the space and number of receiver lines), a quality evaluation method of the geometry based on comprehensive quality factor(CQF) is proposed, and the relationship between the geometry quality and the four parameters is given. We use field data collected in an oil field in Western China with complex geology: First we use a wide azimuth geometry. Then, we calculate the relationship curve between geometry and data quality by varying each parameter while keeping the rest fixed. and the analysis results are given by using the CQF evaluation method. The results show that the shot-line spacing has the greatest effect on the quality of the geometry, and the increase of the receiver line spacing can appropriately improve the quality of the geometry, and the increase of the number of receiving traces can improve the geometry quality. The different acquisition parameters have different effects on the imaging quality of shallow and deep events. The model forward and prestack depth migration are used to generate prestack depth migration profiles with different acquisition parameters. The imaging results are consistent with the above calculated results. According to the depth of the target layer, the quality factor evaluation method is applied to guide the design of the geometry and optimize the acquisition parameters to improve the imaging accuracy of seismic data.

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.