小波边缘分析与建模的波阻抗反演算法的改进——以中国MOU气田盒8段储层分布预测为例
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摘要
为解决复杂地质条件下基于小波边缘分析与建模的波阻抗反演(AIW)运算效率偏低的难题,基于AIW基本原理,对其原有算法进行改进,即采用改进的非常快速模拟退火算法(modified very fast simulated annealing algorithm,MVFSA)替代AIW原有算法,并于MOU气田盒8段开展储层分布预测以验证改进算法的可行性.以MVFSA为基本算法对原始地震数据进行AIW获取波阻抗数据体,并统计工区盒8段测井交会图建立储层预测判别模式进行储层分布预测.研究结果表明:在保持原有AIW基本特性的前提下,采用改进算法获得的AIW剖面不仅纵向分辨率得到一定程度的提高,横向分辩率的变化也真实自然,而且反演运算效率提高了25%~30%,解决了复杂地质条件下原有AIW反演算法运算效率偏低的难题;采用改进算法的AIW储层预测结果与实际地质情况及钻孔资料吻合较好,证实了改进算法的可行性.
To improve the computational efficiency of acoustic impedance inversion based on wavelet edge analysis and modelling(AIW)under complex geological conditions,based on the fundamental principle of AIW,the original algorithm of AIW was substituted by the modified very fast simulated annealing(MVFSA),and the feasibility of the MVFSA algorithm was verified by the reservoir distribution prediction in h8 segment of MOU gas field.The data of acoustic impedance were acquired by using AIW that based on the MVFSA algorithm,and the discriminated pattern of h8segment reservoir was established through analyzing the characteristic of logging-cross-plot in the research field,for predicting the reservoir distribution of h8segment.The result indicated that,while maintaining of the original AIW,not only the axial resolution of the AIW profiles is improved and the variation of lateral resolution was true and nature,but also the computational efficiency of AIW was increased 25%to 30%by using the MVFSA algorithm.Furthermore,the reservoir prediction results of AIW by using the MVFSA algorithm were in agreement with the local geological conditions and logging data,which verified the reliability of this modified algorithm.
To improve the computational efficiency of acoustic impedance inversion based on wavelet edge analysis and modelling(AIW)under complex geological conditions,based on the fundamental principle of AIW,the original algorithm of AIW was substituted by the modified very fast simulated annealing(MVFSA),and the feasibility of the MVFSA algorithm was verified by the reservoir distribution prediction in h8 segment of MOU gas field.The data of acoustic impedance were acquired by using AIW that based on the MVFSA algorithm,and the discriminated pattern of h8segment reservoir was established through analyzing the characteristic of logging-cross-plot in the research field,for predicting the reservoir distribution of h8segment.The result indicated that,while maintaining of the original AIW,not only the axial resolution of the AIW profiles is improved and the variation of lateral resolution was true and nature,but also the computational efficiency of AIW was increased 25%to 30%by using the MVFSA algorithm.Furthermore,the reservoir prediction results of AIW by using the MVFSA algorithm were in agreement with the local geological conditions and logging data,which verified the reliability of this modified algorithm.
引文
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[11]PENNA T J P.Traveling salesman problem and Tsallis statistics[J].Physical Review E,1995,51(1):1-3.
[2]INGBER L.Very fast simulated annealing[J].Mathematical Computer Modeling,1989,12(8):967-973.
[3]陈华根,李丽华,许惠平,等.改进的非常快速模拟退火算法[J].同济大学学报:自然科学版,2006,34(8):1121-1125.CHEN Hua-gen,LI Li-hua,XU Hui-ping,et al.Modified very fast simulated annealing algorithm[J].Journal of Tongji University:Natural Science,2006,34(8):1121-1125.
[4]谢裕江,郑金明,刘高.改进的多参数优化快速模拟退火法反演在储层预测中的应用[J].石油天然气学报,2012,34(3):190-193.XIE Yu-jiang,ZHENG Jin-ming,LIU Gao.Application of modified and rapid simulated annealing wave impedance inversion through multi-parameter optimization in reservoir prediction[J].Journal of Oil and Gas Technology,2012,34(3):190-193.
[5]吕铁良,王永刚,谢万学,等.稀疏脉冲反演技术在井间地震反演中的应用[J].石油物探,2007,46(1):58-63.LV Tie-liang,WANG Yong-gang,XIE Wan-xue,et al.Application of sparse pulse inversion in crosswell seismic data[J].Geophysical Prospecting for Petroleum,2007,46(1):58-63.
[6]张永刚.地震波阻抗反演技术的现状和发展[J].石油物探,2002,41(4):385-390.ZHANG Yong-gang.The present and future of wave impedance inversion techniques[J].Geophysical Prospecting for Petroleum,2002,41(4):385-390.
[7]SUBHASHLS M,XURI H,JEFFREY L,et al.Hybrid seismic inversion:A reconnaissance tool for deepwater exploration[J].The Leading Edge,2000,19(11):1230-1237.
[8]LINES L R.Inversion of geophysical data[M].Tulsa:Society of Exploration Geophysicist,1992.
[9]HUANG X R,KELKAE M,CHOPRA A,et al.Wavelet sensitivity study on inversion using heuristic combinatorial algorithms[C]∥SEG Annual Meeting Expanded Technical Program Abstracts with Biographies 65.Houston,Texas:Society of Exploration Geophysicists,1995:1088-1090.
[10]顾汉明,江涛,王家映.改进快速模拟退火方法进行AVO岩性参数反演[J].地球科学-中国地质大学学报,1999,24(4):418-422.GU Han-min,JIANG Tao,WANG Jia-ying.Improvement of fast simulated annealing algorithm and its application to inversion of AVO lithological parameters[J].Earth Science(Journal of China University of Geosciences),1999,24(4):418-422.
[11]PENNA T J P.Traveling salesman problem and Tsallis statistics[J].Physical Review E,1995,51(1):1-3.
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