本文選題：裂縫預(yù)測 + 儲層預(yù)測　； 參考：《長江大學(xué)》2015年碩士論文

【摘要】：裂縫型油氣藏的油氣產(chǎn)量占全世界油氣總產(chǎn)量的一半以上,國內(nèi)近些年勘探發(fā)現(xiàn)的裂縫油氣藏也越來越多。隨著勘探程度的不斷提高,裂縫型等非構(gòu)造油氣藏的勘探已逐漸成為我國各大油田的主攻方向。大民屯凹陷地區(qū)位于遼河盆地的北部,三維資料基本覆蓋了整個(gè)大民屯凹陷,從鉆探情況來看,研究區(qū)具有較高勘探和研究價(jià)值。本論文主要是從地震屬性基礎(chǔ)理論知識出發(fā),將裂縫預(yù)測的技術(shù)應(yīng)用到大民屯凹陷潛山區(qū)塊中,并以測井和地質(zhì)兩方面的資料為基礎(chǔ)進(jìn)行巖石物性分析,了解其儲層物性參數(shù)的關(guān)系,為地震正演模型的建立提供有力的理論基礎(chǔ),通過地震模型正演和地球物理響應(yīng)特征分析,研究地震方法對裂縫發(fā)育區(qū)的可識別性；并對地震屬性進(jìn)行分析,并篩選出敏感屬性,將分析結(jié)果與地質(zhì)、鉆井資料進(jìn)行對比分析,最后應(yīng)用疊后相干體裂縫檢測技術(shù)、螞蟻?zhàn)粉櫦夹g(shù)、多尺度邊緣檢測技術(shù)以及多屬性神經(jīng)網(wǎng)絡(luò)等綜合分析技術(shù),對裂縫的有利發(fā)育區(qū)進(jìn)行預(yù)測。在利用地震屬性進(jìn)行裂縫預(yù)測前,開展了裂縫段成像測井特征分析,利用成像測井刻度常規(guī)測井,提高常規(guī)測井識別裂縫的精度。同時(shí),通過特征曲線統(tǒng)計(jì)結(jié)合測井原理分析,總結(jié)不同角度裂縫測井(速度、密度、電阻率、伽馬、中子)響應(yīng)特征,篩選對于裂縫敏感的測井資料,建立裂縫與測井響應(yīng)之間關(guān)系。同時(shí)針對不同密度、不同發(fā)育級別的裂縫理想模型以及研究區(qū)實(shí)際地質(zhì)模型進(jìn)行正演模擬,以此為基礎(chǔ)分析不同巖性、不同速度、不同裂縫級別等情況下疊后地震響應(yīng)特征。論文在對地震屬性進(jìn)行簡要分析后,有針對性的對目前較為常用的地震屬性方法做了一些研究分析,進(jìn)一步利用疊后相干體、螞蟻體追蹤技術(shù)、邊緣檢測技術(shù)對裂縫進(jìn)行了預(yù)測研究。(1)相干體裂縫預(yù)測是對一定時(shí)窗內(nèi)地震波形縱向和橫向相似性的判別,揭示相對宏觀的斷裂信息；(2)用螞蟻?zhàn)粉欉M(jìn)行了裂縫預(yù)測,在螞蟻體屬性上可見明顯的裂縫分布,且裂縫傾角顯示清晰,表現(xiàn)為高角度、近平行分布的特征；(3)利用小波多尺度邊緣檢測技術(shù)預(yù)測了裂縫發(fā)育區(qū),針對實(shí)際工區(qū)的資料分析得出其小波邊緣檢測閾值分別為F1=0.012376及F2=0.137816,大于F2的為裂縫發(fā)育區(qū)；大于F1小于F2的為裂縫次發(fā)育區(qū),小于F1為裂縫不發(fā)育區(qū)。(4)利用相關(guān)性和屬性特征強(qiáng)度綜合分析方法,優(yōu)選出7種屬性進(jìn)行分析,并利用神經(jīng)網(wǎng)絡(luò)技術(shù)預(yù)測了裂縫的主要發(fā)育部位。最后論文通過一系列的研究在本區(qū)變質(zhì)巖裂縫預(yù)測方法研究方面主要獲得了以下幾點(diǎn)認(rèn)識：(1)總結(jié)出了該區(qū)對裂縫有敏感響應(yīng)的測井曲線,在裂縫發(fā)育區(qū),雙側(cè)向電阻率曲線存在大的正差異,聲波時(shí)差變化大；而在裂縫不發(fā)育處,雙側(cè)向曲線差異小,聲波時(shí)差變化小。(2)對裂縫段進(jìn)行正演模擬,建立了5類23個(gè)不同裂縫參數(shù)的裂縫儲層地震地質(zhì)模型,并對這些模型進(jìn)行了波動(dòng)方程正演模擬研究和地震屬性分析。結(jié)果表明：裂縫發(fā)育密度和裂縫等效速度是影響地震波場特征的首要因素,裂縫發(fā)育區(qū)的地震反射雜亂。裂縫密度越大,速度與圍巖的差別越大,裂縫響應(yīng)越明顯。裂縫厚度和寬度也對其地震響應(yīng)產(chǎn)生一定的影響,厚度和寬度越大則反射越強(qiáng)。(3)疊后屬性分析中,沿潛山頂界面對地震數(shù)據(jù)體提取了振幅類、復(fù)地震道統(tǒng)計(jì)類、層序統(tǒng)計(jì)類、頻譜類等39種屬性,利用相關(guān)性和屬性特征強(qiáng)度綜合分析方法,優(yōu)選出7種屬性進(jìn)行分析,并利用神經(jīng)網(wǎng)絡(luò)技術(shù)預(yù)測了裂縫的主要發(fā)育部位,并根據(jù)裂縫密度分區(qū)平面圖,將工區(qū)劃分為三類區(qū)塊。作為驗(yàn)證井的哈20、哈30-28-28、沈303、沈269及哈31-16-18,其相對誤差在2%～19%之間,平均誤差8%,預(yù)測結(jié)果較好。(4)總體來看,屬性預(yù)測方法較多,預(yù)測結(jié)果差異不大,裂縫主要發(fā)育在平安堡潛山、勝西低潛山、東勝堡潛山構(gòu)造帶。對于疊后多屬性預(yù)測,預(yù)測誤差相對較小,精度相對較高,是相對較好的裂縫預(yù)測方法。
[Abstract]:The oil and gas production in the fractured reservoir accounts for more than half of the total oil and gas production in the world. There are more and more fractured oil and gas reservoirs found in China in recent years. With the continuous improvement of the exploration degree, the exploration of fracture type and other non tectonic oil and gas reservoirs has gradually become the main direction of the major oil fields in our country. The damun depression area is located in the Liaohe basin. In the north, the three dimensional data basically covered the whole damtun sag. From the point of view of drilling, the research area has high exploration and research value. This paper, based on the basic theoretical knowledge of seismic attributes, applies the technology of fracture prediction to the Qianshan block in damun depression, and is based on the data of two aspects of logging and geology. The relationship between physical properties of rock and physical properties of the reservoir is analyzed, which provides a strong theoretical basis for the establishment of the seismic forward modeling. Through the analysis of seismic model forward and geophysical response characteristics, the identification of the seismic method to the fracture development zone is studied, and the seismic attributes are analyzed and the sensitive attributes are screened out and the analysis knot will be analyzed. The results are compared with the geological and drilling data. Finally, the fracture detection technique, the ant tracking technique, the multi-scale edge detection technology and the multi attribute neural network are used to predict the favorable development area of the fracture. The fractured section imaging logging is carried out before the fracture prediction is carried out by the use of the seismological property. Feature analysis, using conventional logging logging to improve the accuracy of identifying cracks in conventional logging. At the same time, through the analysis of characteristics curve statistics and logging principle analysis, the response characteristics of different angle fractures (velocity, density, resistivity, gamma, neutron) are summarized, and the sensitive logging data are screened for cracks and the response of fractures and logs is established. At the same time, in the light of different density, different development level of crack ideal model and the actual geological model in the study area, a forward simulation is carried out to analyze the characteristics of post stack seismic response under different lithology, different velocity and different crack levels. The more commonly used seismic attribute methods have done some research and analysis, further using post stack coherent body, ant body tracking technique and edge detection technology to predict the crack. (1) the prediction of the coherent body crack is the discrimination of the longitudinal and transverse similarity of the seismic waves in a certain time window, and reveals the relative macroscopic fracture information; (2) the ants are used to use ants. The fracture prediction is carried out, and the obvious crack distribution is visible on the ant body properties, and the fracture angle is clearly displayed, which is characterized by high angle and near parallel distribution. (3) the fracture development zone is predicted by the wavelet multiscale edge detection technology, and the threshold of the wavelet edge detection is F1=0.0 for the data analysis of the actual work area. 12376 and F2=0.137816, greater than F2 for fracture development zone; more than F1 less than F2 for the secondary zone of fracture development, less than F1 as the fracture undeveloped zone. (4) the use of correlation and attribute characteristics strength comprehensive analysis method, the optimization of the 7 properties of the analysis, and the use of neural network technology to pre test the main parts of the fracture. A series of studies have mainly acquired the following points in the study of fracture prediction methods of metamorphic rocks in this area: (1) the well logging curves that have sensitive response to cracks are summed up in this area. In the zone of fracture development, there is a large positive difference between the two lateral resistivity curves, and the variation of sonic time difference is large, while in the undeveloped cracks, the difference of the bilateral curve is small. The acoustic wave time difference is small. (2) the fracture section is forward simulated, and 5 types of fractured reservoir seismic geological models with 23 different fracture parameters are established, and the wave equation forward modeling and seismic attribute analysis are carried out. The results show that the density of fracture and the equivalent velocity of cracks are the primary factors affecting the characteristics of seismic wave fields. The greater the density of the cracks, the greater the density of the cracks, the greater the difference between the velocity and the surrounding rock, the more obvious the response of the cracks. The thickness and width of the cracks also have a certain effect on the seismic response, and the greater the thickness and width, the stronger the reflection. (3) in the post stack attribute analysis, the amplitude class is extracted along the interface of the submersible peak to the seismic data body. 39 attributes, such as seismic trace statistics, sequence statistics and spectrum, are used to analyze the 7 attributes by using the comprehensive analysis method of correlation and attribute characteristics strength. The main parts of the fracture are predicted by the neural network technology, and the area is divided into three types of blocks according to the partition plane map of the density of the fracture density. 20, ha 30-28-28, Shen 303, Shen 269 and ha 31-16-18, their relative errors are between 2% and 19%, the average error is 8%, and the prediction results are good. (4) in general, the property prediction methods are more, the prediction results are different, the cracks are mainly developed in Ping'an Qianshan, Shenxi low Qianshan, Dongsheng Fort Qianshan structural belt. Relatively small, relatively high accuracy, is a relatively good method of crack prediction.
【學(xué)位授予單位】：長江大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：P618.13

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