基于匹配追踪算法的强反射分离技术在元坝地区茅三段储层预测中的应用
Reservoir Prediction of Mao 3 Member in Yuanba Area Using Strong Reflection Separation Technology Based on Matching Pursuit Algorithm

四川盆地茅口组储层普遍具有埋藏深、厚度薄的特点。受吴家坪底部泥岩与茅三段灰岩形成的强反射界面影响，元坝地区茅三段滩相储层响应特征无法有效识别，严重制约了对该区目的层段储层的刻画和认识。本文开展基于匹配追踪的强反射分离方法研究，目的是弱化强阻抗界面的影响，增强储层有效信号。结合单井质控及二维模型正演模拟，确定了该方法的有效性和合理性。同时针对滩相储层受相带控制的特点，在不同沉积相带加入不同强反射分离系数。通过对比去除强反射屏蔽层前后的剖面及平面属性，表明强反射层分离后，元坝地区茅三段滩体展布特征更加清晰。在此基础上识别的沉积微相细节丰富、边界清晰，可为后续储层预测提供较可靠的定性参考。
The reservoir of Maokou Formation in the Sichuan Basin generally has the characteristics of deep burial and thin thickness. The strong reflection energy generated by the unconformity interface on the top of Maokou Formation shields the seismic response of the reservoir below, which leads to weak effective signal energy and severely restricts the description and understanding of the reservoirs in the target interval in this area. We carried out research on strong reflection separation method based on matching tracking, the purpose of which is to weaken the influence of the strong impedance interface and enhance the effective signal of the reservoir. Through single-well quality control and two-dimensional model forward modeling, the effectiveness and rationality of the method are confirmed. At the same time, in view of the characteristics of reef-shoal facies reservoirs controlled by facies belts, different strong reflection separation coefficients are added to different sedimentary facies belts. By comparing the profile and plane attributes before and after removing the strong reflective energy, it shows that after the strong reflection layer is separated, the distribution characteristics of the reef and shoal bodies of the third member of Maokou’s section in Yuanba area are more clear and objective. The identification of sedimentary microfacies on this basis can provide a more reliable qualitative reference for subsequent reservoir prediction.