本文關(guān)鍵詞：火山巖儲(chǔ)層縫洞測(cè)井自動(dòng)識(shí)別和定量評(píng)價(jià)　出處：《吉林大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 火山巖 裂縫識(shí)別 常規(guī)測(cè)井 成像測(cè)井 識(shí)別因子 分水嶺算法 孔洞識(shí)別 參數(shù)計(jì)算

【摘要】：隨著世界經(jīng)濟(jì)發(fā)展越來越快,人們對(duì)油氣資源的需求量越來越大,油氣資源的重要性與日俱增,縫洞性油氣藏作為當(dāng)下重要的開采對(duì)象,一直是國(guó)內(nèi)外研究的熱點(diǎn)。目前,國(guó)內(nèi)外對(duì)復(fù)雜巖性儲(chǔ)層構(gòu)造裂縫的測(cè)井識(shí)別和解釋研究不僅僅包括碳酸鹽巖,近年來又?jǐn)U展到火成巖、變質(zhì)巖,甚至是致密砂巖,泥頁巖,針對(duì)火山巖儲(chǔ)層構(gòu)造裂縫的測(cè)井識(shí)別和解釋還缺乏系統(tǒng)化和定量化;火山巖孔洞的測(cè)井識(shí)別和解釋同樣缺乏系統(tǒng)化和定量化。裂縫與孔洞的準(zhǔn)確識(shí)別一直以來是個(gè)難題,火山巖儲(chǔ)層巖性復(fù)雜,利用常規(guī)測(cè)井資料識(shí)別裂縫準(zhǔn)確率低,利用成像測(cè)井人眼識(shí)別費(fèi)時(shí)費(fèi)力,自動(dòng)識(shí)別方面研究較少并且縫洞識(shí)別準(zhǔn)確率方面效果較差。本文依據(jù)常規(guī)測(cè)井資料和成像測(cè)井資料,以王府?dāng)嘞莼鹕綆r儲(chǔ)層為研究對(duì)象,對(duì)裂縫和孔洞的自動(dòng)識(shí)別及定量評(píng)價(jià)展開研究�？p、洞的自動(dòng)識(shí)別會(huì)大大提高火山巖儲(chǔ)層開發(fā)的效率,并且這些研究對(duì)其他復(fù)雜巖性儲(chǔ)層的裂縫和孔洞的識(shí)別具有借鑒和指導(dǎo)意義。在裂縫識(shí)別方面,首先針對(duì)電成像測(cè)井縱向分辨率高但裂縫人工識(shí)別繁瑣以及常規(guī)測(cè)井裂縫識(shí)別方便但準(zhǔn)確度低的情況,提出了一種新方法進(jìn)行儲(chǔ)層裂縫自動(dòng)識(shí)別,利用經(jīng)處理后常規(guī)測(cè)井?dāng)?shù)據(jù)和經(jīng)預(yù)處理后的電成像微電導(dǎo)率資料建立常規(guī)儲(chǔ)層測(cè)井裂縫綜合識(shí)別因子Y1和電成像儲(chǔ)層裂縫識(shí)別因子Y2,然后綜合利用兩個(gè)因子建立儲(chǔ)層裂縫識(shí)別因子Y。該方法結(jié)合了常規(guī)和成像測(cè)井識(shí)別裂縫的優(yōu)點(diǎn),能自動(dòng)識(shí)別裂縫發(fā)育層段,解決了成像測(cè)井人工拾取裂縫費(fèi)時(shí)費(fèi)力缺點(diǎn);可以剔除無效裂縫干擾,識(shí)別出有效裂縫;提高了裂縫識(shí)別準(zhǔn)確度。將其應(yīng)用到王府地區(qū)井中得到了較好的應(yīng)用效果。在孔洞識(shí)別方面,以成像測(cè)井資料為切入點(diǎn),將分水嶺算法引用到了孔洞的自動(dòng)識(shí)別中來,并將分水嶺算法進(jìn)行了改進(jìn),通過matlab實(shí)現(xiàn)分水嶺算法對(duì)孔洞的識(shí)別,并定量計(jì)算出孔洞的面孔率,統(tǒng)計(jì)出孔洞尺寸的分布譜圖。最后將新提出的裂縫識(shí)別方法和孔洞識(shí)別方法應(yīng)用到了王府?dāng)嘞軽X地區(qū)實(shí)際資料進(jìn)行了處理,對(duì)識(shí)別裂縫和孔洞進(jìn)行了定量參數(shù)計(jì)算,取得了不錯(cuò)的效果。建立了裂縫和孔洞識(shí)別以及定量解釋評(píng)價(jià)方法。
[Abstract]:With the rapid development of the world economy, the demand for oil and gas resources is increasing, and the importance of oil and gas resources is increasing. At present, the logging identification and interpretation of structural fractures in complex lithologic reservoirs include not only carbonate rocks, but also igneous rocks and metamorphic rocks in recent years. Even for tight sandstone and shale, the logging identification and interpretation of structural fractures in volcanic reservoir are still lack of systematization and quantification. The logging identification and interpretation of volcanic pores are also lack of systematization and quantification. Accurate identification of fractures and pores has always been a difficult problem, and the lithology of volcanic reservoir is complex. The accuracy of identifying fractures by conventional logging data is low, and the identification of human eyes by imaging logging is time-consuming and laborious. Based on the conventional logging data and imaging logging data, this paper takes the volcanic reservoir of Wangfu fault depression as the research object. The automatic identification and quantitative evaluation of fractures and voids are studied. The automatic identification of fractures and cavities will greatly improve the efficiency of volcanic reservoir development. And these studies have reference and guidance significance for the identification of fractures and pores in other complex lithologic reservoirs. Aiming at the situation of high vertical resolution of electric imaging logging but complicated manual identification of fractures and convenient but low accuracy of conventional logging, a new method for automatic recognition of reservoir fractures is proposed. Based on the processed conventional logging data and the pre-processed electrical imaging microconductivity data, the conventional logging fracture recognition factor Y1 and the electrical imaging reservoir fracture recognition factor Y2 are established. Then two factors are synthetically used to establish the reservoir fracture identification factor Y. this method combines the advantages of conventional and imaging logging to identify fractures automatically. It solves the problem that it takes time and effort to pick up fractures manually by imaging logging. The invalid cracks can be eliminated and the effective cracks can be identified. The accuracy of fracture identification has been improved. The application of this method to the well of Wangfu area has been better. In the respect of hole recognition, the imaging logging data is taken as the breakthrough point. The watershed algorithm is applied to the automatic recognition of the holes, and the watershed algorithm is improved. The recognition of the holes is realized by the watershed algorithm by matlab, and the hole face ratio is calculated quantitatively. Finally, the new fracture identification method and hole recognition method are applied to the actual data processing in the XX area of Wangfu fault depression. The quantitative parameter calculation for identifying fractures and holes has been carried out, and good results have been obtained, and a method for identification and quantitative interpretation and evaluation of fractures and holes has been established.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：P618.13;P631.81

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