Abstract

The ultra-deep fault-karst structure discovered in the Tarim Basin in Western China is a fractured-vuggy carbonate reservoir with great potential for development. The diffraction generated by fractures, small-scale caves and vugs is often used for reservoir identification and seismic interpretation. Since the diffraction is much weaker than the reflection, it is difficult to separate the diffraction from the full wavefield. We use a plane-wave destruction (PWD) filter to extract the diffraction from the full data. In order to obtain a high-accuracy and amplitude-preserving imaging profile, we use the least-squares reverse time migration (LSRTM) method to image the separated diffraction. The large amount of calculation is the most challenging problem of the LSRTM algorithm. In view of this, we develop an adaptive sampling strategy to improve computing efficiency and reduce memory requirement. We use a fault model, a vugs-fractures model, and a fault-karst model to demonstrate the effectiveness and practicability of the proposed method. The numerical examples show that the proposed method can enhance the imaging resolution of the fault-karst structure and save computing cost without losing accuracy. In addition, a test on field data processing demonstrates the advantages of our algorithm.

Highlights

  • The marine carbonate reservoirs have produced abundant oil and gas resources globally (Loucks and Anderson, 1985; Soudet et al, 1994; Tian et al, 2016)

  • The complete workflow of the AS-D-least-squares reverse time migration (LSRTM) method is divided into the following steps: 1) separating the diffraction from the full wavefield by plane-wave destruction (PWD) filter method; 2) performing irregular grid discretization applying adaptive sampling; 3) imaging the diffraction using LSRTM

  • We propose a high-accuracy and high-efficiency AS-DLSRTM method, which contains three main parts

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Summary

Introduction

The marine carbonate reservoirs have produced abundant oil and gas resources globally (Loucks and Anderson, 1985; Soudet et al, 1994; Tian et al, 2016). The complete workflow of the AS-D-LSRTM method is divided into the following steps: 1) separating the diffraction from the full wavefield by PWD filter method; 2) performing irregular grid discretization applying adaptive sampling; 3) imaging the diffraction using LSRTM.

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