• 应用地球物理学Ⅰ •

### 井震联合预测白云深水区海相烃源岩TOC

1. 中海油研究总院, 北京 100028
• 收稿日期:2016-03-09 修回日期:2016-07-10 出版日期:2016-10-20 发布日期:2016-10-20
• 作者简介:张益明,男,1964年生,中海油研究总院首席工程师,主要从事地震储层预测、烃类检测和地球物理综合方法研究.(E-mail:zhangym1@cnooc.com.cn)

### Marine source rocks TOC prediction with a joint logging and seismic method in Baiyun deepwater area

ZHANG Yi-ming, HAN Li, LIU Chun-cheng, YE Yun-fei

1. CNOOC Research Institute, Beijing 100028, China
• Received:2016-03-09 Revised:2016-07-10 Online:2016-10-20 Published:2016-10-20

Abstract:

With the increasing demand of energy and rapid development of science and technology, oil and gas exploration develop from land to ocean, from shallow water to deep water. Deep water is becoming a hot area of oil and gas exploration. Baiyun Sag has been proved to be a hydrocarbon-rich sag in deepwater area of northern South China Sea. The reservoir distributions are affected by many factors, the most important one of which in this area is the distribution and quality of source rocks. However, conventional source rocks prediction methods are limited in the deep water area, due to the less of drilling data, the poor quality of seismic data and difficulties in calculating the velocity field. To solve these problems and reduce the cost of exploration, a marine source rocks prediction method based on the relationship of P-wave impedance and the source rocks TOC in Baiyun deepwater area is studied in this paper. A technical workflow of joint logging and seismic method for TOC prediction under less well condition is proposed. The workflow consists of four steps. First of all, predict a continuous TOC curve with multiple attribute fusion technology (named TOC well prediction). In this paper, we use the "EMERGE" module of HRS software to optimize the selection of sensitive attributes. The logRT、DT and Sqrt (GR) are finally chosen to predict the continuous TOC curve. Secondly, establish the fitting relationship of predicted TOC curve and the elastic parameters by cross analysis (named rock physical analysis of source rocks). The cross analysis results indicate that, the P-wave velocity and P-wave impedance perform nonlinear decreasing with the increase of TOC, and the density performs linear decreasing. The rock physical analysis provides the foundation of predicting TOC with P-wave impedance. The third step, introduce the no well constrained high-precision grid tomographic velocity inversion technology to obtain velocity spectrum, which is used to calculate the p-wave impedance (named seismic inversion process). The no well constrained tomographic velocity inversion technology avoids the problem of less well data in deepwater, which limits the conventional seismic inversion. Finally, predict the source rocks distribution and organic matter abundance based on the fitting relationship and calculated p-wave impedance. The impedance inversion results have a good relation with observed TOC at well position, which verified the effective of the proposed method.