Publications

Benefits and Uplift of Focused Post-Migration Gather Conditioning Over Prospect Specific Areas - An Indonesian Case Study

Proceedings Title : Proc. Indon. Petrol. Assoc., 46th Ann. Conv., 2022

Many regional 3Ds cover large areas where the geological and geophysical settings can change from sub-basin to sub-basin. Because of these variations, the processing flow designed for these surveys is unlikely to be optimum for individual prospect areas. In this case study, a description of the application of an optimized gather conditioning work flow to 2019 regional 3d survey and subsequent pre-stack data analysis will be presented. The objective of this conditioning was to provide optimized gather volumes for predrill AVA analysis. The data and results of the interpretation provided input into prospect risking, resource estimates of the prospects, and increased our understanding of the rock physics parameters. Evaluation of the final angle stacks from a recent multi-client 3D in the Andaman Sea identified issues that could compromise the AVA fidelity of the data, and hence the need to perform gather conditioning. The input data for the conditioning were raw PSDM TWT (PSDM gathers converted to time) gathers which were analyzed using QC attributes to design an optimized conditioning work flow. This process included RMO, Radon Demultiple, Spectral Balancing, Random Noise Attenuation, Q-compensation, and Trim Statics. The QC attributes were computed to measure AVA compliance, residual moveout, gather flatness, seismic bandwidth, and coherent and incoherent noise contamination. The conditioned volumes were integrated with the available well control. Intercept and gradient volumes were used to generate various relative attribute volumes. Chi angle reflectivity and EEI colored inversion attributes provided insight into the relative bounding conditions and rock physics properties needed to generate the response observed on the seismic and identify a calibrated range of pre-drill scenarios. In summary, the gather conditioning improved the AVA fidelity of the data and provided an uplift in the understanding of the range of rock physics parameters and prospect risking.

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