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基于巖石物理參數(shù)正演的儲層預(yù)測方法研究

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  本文選題:巖石物理參數(shù)正演 + 疊后反演�。� 參考:《中國地質(zhì)大學(xué)(北京)》2017年碩士論文


【摘要】:隨著勘探技術(shù)的逐步發(fā)展,勘探的方向也隨之發(fā)生了轉(zhuǎn)變,勘探的目標(biāo)由傳統(tǒng)尋找構(gòu)造油氣藏逐步轉(zhuǎn)向?qū)ふ規(guī)r性油氣藏。而對巖性油氣藏的預(yù)測又十分注重地下彈性參數(shù)的質(zhì)量。本論文針對區(qū)塊地質(zhì)構(gòu)造復(fù)雜,地震資料分辨率低的巖性地層油氣藏K地區(qū)開展研究,制定一套適用于該地區(qū)的研究方案。針對不同地質(zhì)條件及資料品質(zhì)的區(qū)塊,采用不同的儲層預(yù)測方法。K研究區(qū)構(gòu)造變形較弱,構(gòu)造圈閉類型與數(shù)量較少,且幅度較低,同時儲層反射弱、地震分辨率低、超覆點(diǎn)難以識別,若使用疊前反演則地震資料的質(zhì)量沒有達(dá)到要求。因此本論文基于疊后反演展開儲層預(yù)測方法研究。根據(jù)研究區(qū)塊的特點(diǎn),綜合采用巖石物理參數(shù)正演、地震疊后反演技術(shù)以及地震屬性分析技術(shù)。巖石物理分析將測井同儲層反演關(guān)聯(lián)起來,測井中的測井特征及其所反映的地球物理規(guī)律皆可通過巖石物理的系統(tǒng)分析展示出來。一方面,通過巖石物理參數(shù)正演技術(shù)可以對缺損信息的井資料進(jìn)行校正,通過計(jì)算,重構(gòu)出完善的縱、橫波速度以及密度等信息,更大程度的提高工區(qū)井資料的有效利用,同時為后續(xù)的儲層預(yù)測提供充足的研究數(shù)據(jù)。另一方面,利用流體替換技術(shù),可以研究不同流體介質(zhì)環(huán)境中的地球物理響應(yīng)特征。與此同時,通過巖石物理的敏感參數(shù)分析,對比分析出識別砂泥巖效果好的參數(shù),從而對后續(xù)儲層反演工作指明方向。本文通過基于巖石物理分析的疊后反演方法刻畫研究區(qū)有利儲層的空間展布形態(tài)及分布特征,落實(shí)研究區(qū)薄儲層的平面分布特征。結(jié)合多種地震屬性的分析與提取用以約束儲層預(yù)測結(jié)果的不確定性,形成一套適用于埋藏深度大、儲層厚度薄、上部存在屏蔽層地區(qū)的有利儲層預(yù)測技術(shù)手段和方法。
[Abstract]:With the gradual development of exploration technology, the direction of exploration has also changed, and the target of exploration has gradually shifted from traditional structural oil and gas reservoirs to lithologic reservoirs. The prediction of lithologic reservoir pays much attention to the quality of underground elastic parameters. In this paper, the lithostratigraphic reservoir K area with complex geological structure and low resolution of seismic data is studied, and a set of research scheme suitable for this area is worked out. For the blocks with different geological conditions and data quality, the structural deformation is weaker, the type and number of structural traps are less, the amplitude is lower, the reservoir reflection is weak, and the seismic resolution is low in the study area using different reservoir prediction methods. Overlying points are difficult to identify, and if prestack inversion is used, the quality of seismic data does not meet the requirements. Therefore, this paper develops reservoir prediction methods based on poststack inversion. According to the characteristics of the studied block, the forward modeling of rock physical parameters, post-stack inversion and seismic attribute analysis are adopted. The petrophysical analysis correlates logging with reservoir inversion. The logging characteristics and the geophysical laws reflected in logging can be demonstrated by systematic analysis of rock physics. On the one hand, through the technique of forward modeling of rock physical parameters, the well data of defective information can be corrected, and the perfect information of longitudinal, shear wave velocity and density can be reconstructed by calculation, so as to improve the effective utilization of well data in the working area to a greater extent. At the same time, sufficient research data are provided for the subsequent reservoir prediction. On the other hand, geophysical response characteristics in different fluid environments can be studied by using fluid replacement technique. At the same time, through the analysis of the sensitive parameters of rock physics, the parameters with good effect of identifying sand and mudstone are compared and analyzed, thus pointing out the direction of the subsequent reservoir inversion work. In this paper, the spatial distribution and distribution characteristics of favorable reservoirs in the study area are described by post-stack inversion method based on petrophysical analysis, and the plane distribution characteristics of thin reservoirs in the study area are realized. Combined with the analysis and extraction of various seismic attributes to constrain the uncertainty of reservoir prediction results, a set of favorable reservoir prediction techniques and methods suitable for large buried depth, thin reservoir thickness and the existence of shielding layer in the upper part of the reservoir are formed.
【學(xué)位授予單位】:中國地質(zhì)大學(xué)(北京)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2017
【分類號】:P618.13

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