發(fā)布時(shí)間：2018-05-17 02:01

  本文選題：致密儲(chǔ)層 + 巖性識(shí)別��； 參考：《東北石油大學(xué)》2015年碩士論文

【摘要】：隨著油田勘探開發(fā)程度的不斷深入,復(fù)雜油氣藏逐漸成為油田增儲(chǔ)上產(chǎn)的主要來(lái)源。大民屯凹陷沙四段致密油儲(chǔ)層屬于低孔隙度、低滲透率的致密儲(chǔ)層,巖性多樣,孔隙結(jié)構(gòu)復(fù)雜,泥質(zhì)含量高,束縛水飽和度高。為后續(xù)的巖性劃分及飽和度求取增加了難度。本文在巖電實(shí)驗(yàn)數(shù)據(jù)和測(cè)井資料的基礎(chǔ)上,采用統(tǒng)計(jì)方法對(duì)大民屯凹陷沙四段致密油儲(chǔ)層的巖性、物性和孔隙結(jié)構(gòu)等特征進(jìn)行了研究,表明該區(qū)塊為巖性多樣,物性差,孔隙結(jié)構(gòu)復(fù)雜的致密儲(chǔ)層�；�于該區(qū)塊不同巖性的地質(zhì)及測(cè)井響應(yīng)特征,將該區(qū)塊致密油儲(chǔ)層巖性劃分為油頁(yè)巖、粉砂巖和泥質(zhì)云巖3類。通過(guò)統(tǒng)計(jì)方法對(duì)3類巖性測(cè)井曲線的敏感性進(jìn)行分析,優(yōu)選出聲波時(shí)差、密度和自然伽馬等測(cè)井曲線�；�于敏感測(cè)井響應(yīng),分別建立了測(cè)井響應(yīng)交會(huì)圖巖性識(shí)別方法以及決策樹和量子神經(jīng)網(wǎng)絡(luò)巖性識(shí)別模型,結(jié)果顯示基于數(shù)據(jù)挖掘方法的決策樹模型和量子神經(jīng)網(wǎng)絡(luò)模型的巖性識(shí)別效果優(yōu)于傳統(tǒng)的測(cè)井響應(yīng)交會(huì)圖法�；�于巖心分析資料和測(cè)井資料,分別建立了致密砂巖儲(chǔ)層、泥質(zhì)云巖儲(chǔ)層和油頁(yè)巖的泥質(zhì)含量、孔隙度等參數(shù)解釋模型�；�于巖電實(shí)驗(yàn)數(shù)據(jù),結(jié)合致密砂巖儲(chǔ)層、泥質(zhì)云巖儲(chǔ)層和油頁(yè)巖特征研究成果,采用改進(jìn)的等效巖石元素理論結(jié)合通用阿爾奇理論建立了大民屯凹陷沙四段致密砂巖儲(chǔ)層導(dǎo)電模型,應(yīng)用連通導(dǎo)電方程結(jié)合混合導(dǎo)電定律建立了大民屯凹陷沙四段泥質(zhì)云巖儲(chǔ)層導(dǎo)電模型,利用有效介質(zhì)對(duì)稱導(dǎo)電理論建立了大民屯凹陷沙四段油頁(yè)巖導(dǎo)電模型。對(duì)模型中參數(shù)的敏感性進(jìn)行了分析,利用巖電實(shí)驗(yàn)數(shù)據(jù)和測(cè)井資料確定了模型中的參數(shù),并給出了模型求取含水飽和度的方法。利用本文所建立的參數(shù)解釋模型和導(dǎo)電模型對(duì)該區(qū)塊致密砂巖儲(chǔ)層、泥質(zhì)云巖儲(chǔ)層和油頁(yè)巖的實(shí)際測(cè)井資料進(jìn)行了處理,結(jié)果表明,該模型能夠很好地用于大民屯凹陷沙四段致密油儲(chǔ)層的測(cè)井解釋評(píng)價(jià)。
[Abstract]:With the deepening of exploration and development, complex reservoirs are becoming the main source of increasing reservoir production. The tight oil reservoir of the fourth member of Shahejie formation in Damingtun depression belongs to the tight reservoir with low porosity and low permeability. The lithology is diverse, the pore structure is complex, the content of mud is high, and the irreducible water saturation is high. It increases the difficulty for the subsequent lithologic division and saturation calculation. Based on the experimental data of rock and electricity and logging data, the lithology, physical properties and pore structure of the tight oil reservoir of the fourth member of Shahejie formation in Damingtun depression are studied by using statistical method. The results show that the block is of diverse lithology and poor physical property. Tight reservoir with complex pore structure. Based on the geological and logging response characteristics of different lithology in this block, the lithology of tight oil reservoir in this block is divided into three categories: oil shale, siltstone and shaly dolomite. The sensitivity of three kinds of lithologic logging curves is analyzed by statistical method, and acoustic moveout, density and natural gamma logging curves are selected. Based on the sensitive logging response, the lithologic identification method of cross plot, decision tree and quantum neural network lithology identification model are established, respectively. The results show that the lithology recognition effect of decision tree model and quantum neural network model based on data mining method is better than that of traditional well logging response cross plot method. Based on the core analysis data and logging data, the interpretation models of shale content and porosity of tight sandstone reservoir, argillaceous dolomite reservoir and oil shale are established respectively. Based on the experimental data of rock and electricity, combined with the research results of tight sandstone reservoir, argillaceous dolomite reservoir and oil shale, Based on the improved equivalent rock element theory and the universal Archie theory, a conductive model for the tight sandstone reservoir of the fourth member of Sha in the Damingtun Sag is established. The conductive model of shaly dolomite reservoir in the fourth member of Shahejie formation in Damingtun sag is established by using the connected conductive equation and the mixed conductive law. The oil shale conductive model of the fourth member of Shahejie formation in Damingtun sag is established by using the theory of symmetric conductivity of effective medium. The sensitivity of the parameters in the model is analyzed, the parameters in the model are determined by using the experimental data of rock electricity and logging data, and the method of calculating the saturation of water in the model is given. The actual logging data of tight sandstone reservoir, argillaceous dolomite reservoir and oil shale in this block are processed by using the parameter interpretation model and conductive model established in this paper. The results show that, The model can be applied to the logging interpretation and evaluation of the tight oil reservoirs in the fourth member of Shahejie formation in Damingtun Sag.
【學(xué)位授予單位】：東北石油大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：P618.13;P631.81

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