STRUCTURE-CORRECTION METHOD WITH SEISMIC DATA AND ITS APPLICATION TO IGNEOUS ROCK AREAS
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摘要:
渤海海域BZ油田区新生界广泛发育火成岩。由于不同期次的高速火成岩纵横向分布极不均衡，造成其下伏构造受影响程度存在很大差异，常规的时深转换方法无法真实反映地下的构造形态。笔者提出了一种新的火成岩下构造恢复的方法：首先利用数值模拟分析不同厚度火成岩对下伏构造的影响程度，建立火成岩厚度与时间校正量的数学关系式，然后运用层速度约束反演方法定量识别火成岩的累计厚度，进而得到其引起的时间校正量，最终采用去除火成岩影响的时深关系进行时深转换得到更精确的深度域构造图。实践表明，该方法有效提高了火成岩发育区的构造成图精度，为渤海海域内首次开展新生界火成岩下油田评价提供了有力的技术支撑，具有较好的推广应用价值。
Abstract:Cenozoic igneous rocks are widely and unevenly distributed in the BZ Oilfield of the Bohai Sea. The underground structure of igneous rocks varies with depth. It is not able to correctly describe the underground structure by the conventional time-depth conversion method with seismic data, and as the result it will increase the risk and uncertainty in hydrocarbon exploration and development. In this paper, a new method for structure correction is proposed specifically for igneous rock areas. Firstly, the impact of igneous rock is studied by means of numerical simulation method so as to establish the relationship between the igneous rock thickness and the time span to be corrected. Secondly, the total thickness of igneous rocks is calculated using the interval velocity constrained inversion, then the time-correction for seismic events is obtained. Finally, time-depth relationship is adopted to eliminate the effects of igneous rock, and get more accurate structural maps by time-depth conversion. The drilling results show that this method can effectively improve the precision of structural mapping and may provide strong technical support for the first time to carry out the oilfield evaluation under the Cenozoic igneous rocks in the Bohai Sea.
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表 1 W3、W4井处校正前后结果误差对比
Table 1. The error of traditional method and the new method of Well-W3 and Well-W4
T3层 井名 实钻海拔/m 常规方法/m 本文方法/m 常规方法误差/m 本文方法误差/m 精度提高 T3层 W3 −2 953.2 −2 963.6 −2 951.4 10.4 −1.8 82.6% T4层 W4 −29.6 −2 954.6 −2 942.7 20 8.1 59.5% T4层 W3 −3 055.2 −3 066.6 −3 062.8 11.4 7.6 33.3% T5层 W4 −3 039.9 −3 054.1 −3 036.9 14.2 −3 78.9% T5层 W3 −3 156.2 −3 184 −3 165.3 27.8 9.1 67.3% W4 −31.6 −3 144.7 — — — 27.8% 
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