CAJ | 학술논문

肯吉亚克油田石炭系油藏属特低孔渗、异常高压碳酸盐岩油藏,它除了具有埋深大,非均质性强,油气成藏控制因素复杂等特点外,其上还覆盖巨厚盐丘,造成盐下地震反射时间和振幅畸变严重,地震成像差、信噪比低和分辨率低,给储层预测工作带来极大困难.如何正确预测油藏高产带分布规律是高效开发这类油藏的关键,本文研究从分析形成碳酸盐岩油哺卟闹骺匾蛩厝胧?通过井震标定,优选反映碳酸盐岩岩相、岩溶、物性和裂缝的地震属性,结合地震、地质、测井、油藏工程和钻井资料,把盐下特低孔渗碳酸盐岩油藏高产带预测问题分解成构造解释、岩相预测、岩溶预测、物性预测、裂缝预测和综合评价等六个环节.宏观上,通过建立断裂、岩相、岩溶模式,定性预测储层分布有利区带;微观上,通过多参数储层特征反演和多属性综合分析,定量、半定量预测有利储层分布,有效解决盐下碳酸盐岩油藏高产带预测难题,基本搞清本区碳酸盐岩油藏高产带分布规律,为优选有利勘探和开发目标提供依据.文中提出的方法和技术对解决国内外碳酸盐岩油藏高产带预测和其他复杂储层预测问题有借鉴作用.
긍길아극유전석탄계유장속특저공삼、이상고압탄산염암유장,타제료구유매심대,비균질성강,유기성장공제인소복잡등특점외,기상환복개거후염구,조성염하지진반사시간화진폭기변엄중,지진성상차、신조비저화분변솔저,급저층예측공작대래겁대곤난.여하정학예측유장고산대분포규률시고효개발저류유장적관건,본문연구종분석형성탄산염암유포계료후변공조롱?통과정진표정,우선반영탄산염암암상、암용、물성화렬봉적지진속성,결합지진、지질、측정、유장공정화찬정자료,파염하특저공삼탄산염암유장고산대예측문제분해성구조해석、암상예측、암용예측、물성예측、렬봉예측화종합평개등륙개배절.굉관상,통과건립단렬、암상、암용모식,정성예측저층분포유리구대;미관상,통과다삼수저층특정반연화다속성종합분석,정량、반정량예측유리저층분포,유효해결염하탄산염암유장고산대예측난제,기본고청본구탄산염암유장고산대분포규률,위우선유리감탐화개발목표제공의거.문중제출적방법화기술대해결국내외탄산염암유장고산대예측화기타복잡저층예측문제유차감작용.
The Carboniferous reservoir in KJ oilfield is a carbonate reservoir with extremely low porosity and permeability and high-pressure. The reservoir has severe heterogeneity, is deeply buried, has complex master control factors, is covered with thick salt, all of which result in the serious distortion of reflection time and amplitudes under the salt, the poor seismic imaging, and the low S/N ratio and resolution. The key to developing this kind of reservoir is to correctly predict the distribution of highly profitable oil zones. In this paper we start by analyzing the master control factors, perform seismic-log calibration, optimize the seismic attributes indicating the lithofacies, karst, petrophysical properties,and fractures, and combine these results with the seismic, geology, log, oil reservoir engineering, and well data. We decompose the seismic prediction into six key areas: structural interpretation, prediction of lithofacies, karst, petrophysical properties, fractures, and then perform an integrated assessment.First, based on building the models of faults and fractures, sedimentary facies, and karst, we predict the distribution of the most favorable reservoir zones qualitatively. Then, using multi-parameter inversion and integrated multi-attribute analysis, we predict the favorable reservoir distribution quantitatively and semi-quantitatively to clarify the distribution of high-yield zones. We finally have a reliable basis for optimal selection of exploration and development targets.