裂縫性儲(chǔ)層數(shù)值模擬與預(yù)測(cè)
發(fā)布時(shí)間:2018-08-15 13:06
【摘要】:裂縫性儲(chǔ)層作為重要的油氣儲(chǔ)層,正確認(rèn)識(shí)其空間分布規(guī)律及內(nèi)部構(gòu)造特征可實(shí)現(xiàn)油氣高效開采。裂縫性儲(chǔ)層是在不同的地質(zhì)力作用形成的,其物性與圍巖之間差異較大,空間分布規(guī)律及內(nèi)部構(gòu)造特征復(fù)雜多變。目前已發(fā)展了多種基于疊前、疊后地震資料的裂縫檢測(cè)方法,如曲率、相干等。但利用這些方法得到的裂縫性儲(chǔ)層空間分布規(guī)律及內(nèi)部構(gòu)造特征也因此不夠精細(xì),這些方法的檢測(cè)精度有待進(jìn)一步提高。為提高對(duì)裂縫性儲(chǔ)層的認(rèn)識(shí),本文從數(shù)值模擬和裂縫檢測(cè)(主要應(yīng)用曲率分析)兩個(gè)方面入手,對(duì)常規(guī)數(shù)值模擬和裂縫檢測(cè)方法進(jìn)行改進(jìn)優(yōu)化,提高數(shù)值模擬和裂縫檢測(cè)的精度。本文主要研究?jī)?nèi)容與認(rèn)識(shí)如下:(1)分析了構(gòu)造濾波方法對(duì)裂縫檢測(cè)的影響。對(duì)比分析原始等時(shí)切片和構(gòu)造濾波等時(shí)地震切片之間的差異,并分別計(jì)算原始地震數(shù)據(jù)和經(jīng)構(gòu)造濾波后地震數(shù)據(jù)的相干屬性,通過對(duì)比等時(shí)地震切片和相干屬性探討了構(gòu)造濾波方法對(duì)裂縫檢測(cè)的影響。(2)分析了地震數(shù)據(jù)的分辨率對(duì)裂縫檢測(cè)的影響。利用數(shù)值模擬方法模擬了幾組不同頻率子波的合成記錄,分別計(jì)算各合成記錄的曲率屬性,通過對(duì)比曲率屬性討論了分辨率對(duì)裂縫檢測(cè)的影響。(3)提出了基于螞蟻?zhàn)粉櫟慕7椒ê徒A鞒獭?shù)值模擬是我們認(rèn)識(shí)特定地質(zhì)體的常用手段之一,通過分析常規(guī)的建模流程得到的模擬剖面,可知常規(guī)的建模方式過多依賴于人工地震層位對(duì)比追蹤和斷層解釋的結(jié)果,其準(zhǔn)確度相對(duì)較低,模擬結(jié)果相似度不高。螞蟻?zhàn)粉櫦夹g(shù)相比其他裂縫識(shí)別方法能夠更精確識(shí)別裂縫,通過改變螞蟻?zhàn)粉櫶幚砹鞒毯蛯?duì)比分析不同參數(shù)組合的螞蟻?zhàn)粉櫧Y(jié)果,可得出地質(zhì)構(gòu)造特征明確的螞蟻剖面,將人工地震層位對(duì)比追蹤和斷層解釋的結(jié)果與螞蟻?zhàn)粉櫧Y(jié)果相結(jié)合可建立更精細(xì)的模型,有利于提高數(shù)值模擬結(jié)果的精度。運(yùn)用螞蟻?zhàn)粉櫦夹g(shù)對(duì)常規(guī)數(shù)值模擬方法改進(jìn)優(yōu)化,有利于對(duì)裂縫地震響應(yīng)特征的認(rèn)識(shí)。(4)發(fā)展了基于玫瑰圖分析的方位曲率檢測(cè)裂縫方法。常規(guī)的曲率屬性各向異性特征明顯,不能突顯出特定角度上裂縫發(fā)育的特征。方位曲率屬性是在基于掃描傾角體曲率計(jì)算方法基礎(chǔ)上推導(dǎo)而來的,方位曲率屬性能夠加強(qiáng)某一特定方向上的裂縫特征在曲率屬性上的顯示,可提供檢測(cè)和展示特定方向上裂縫發(fā)育特征的手段。裂縫發(fā)育規(guī)律復(fù)雜,方位角角度信息不易得到,玫瑰圖分析是通過統(tǒng)計(jì)研究區(qū)域不同裂縫強(qiáng)度出現(xiàn)的頻率得出其對(duì)應(yīng)角度信息,較其他方法相比,玫瑰圖分析角度信息更為準(zhǔn)確,為方位曲率分析方法中的特定方位角信息提供解決方案,也提高了特定方向上方位曲率屬性對(duì)裂縫發(fā)育特征的描述。
[Abstract]:Fractured reservoir is an important oil and gas reservoir, which can be exploited efficiently by correctly understanding its spatial distribution law and internal structural characteristics. Fractured reservoir is formed by different geological forces, and its physical properties differ greatly from surrounding rocks. Its spatial distribution law and internal structural characteristics are complex and changeable. Fracture detection methods of pre-stack and post-stack seismic data, such as curvature, coherence, etc. But the spatial distribution and internal structural characteristics of fractured reservoirs obtained by these methods are not precise enough, and the detection accuracy of these methods needs to be further improved. In order to improve the understanding of fractured reservoirs, this paper focuses on numerical simulation and fracture detection. In order to improve the accuracy of numerical simulation and fracture detection, the curvature analysis should be used to improve the conventional numerical simulation and fracture detection methods. By comparing the coherence attributes of the original seismic data and the filtered seismic data, the influence of the tectonic filtering method on the fracture detection is discussed. (2) The influence of the resolution of seismic data on the fracture detection is analyzed. Several numerical simulations are carried out. The curvature attributes of each synthetic record are calculated and the effect of resolution on fracture detection is discussed by comparing the curvature attributes. (3) A modeling method and process based on ant tracking are proposed. Ant tracing technology can identify fractures more accurately than other methods. Ant tracing technology can identify fractures more accurately by changing ant tracing process and correlation. Ant tracing results of different parameter combinations are analyzed, and ant profiles with clear geological structure characteristics can be obtained. Combining the results of artificial seismic horizon correlation tracing and fault interpretation with the results of ant tracing, a more precise model can be established, which is helpful to improve the accuracy of numerical simulation results. (4) An azimuthal curvature detection method based on rosette analysis is developed. The conventional curvature attributes have obvious anisotropic characteristics and can not highlight the characteristics of fracture development at specific angles. The azimuthal curvature attributes are the basis of the curvature calculation method based on scanning dip. The azimuthal curvature attribute can enhance the display of the crack characteristics in a particular direction on the curvature attribute and provide a means to detect and display the crack development characteristics in a particular direction. Comparing with other methods, Rosette analysis is more accurate, which provides a solution for the azimuth information of azimuth curvature analysis method, and also improves the description of fracture development characteristics by azimuth curvature attributes in specific directions.
【學(xué)位授予單位】:成都理工大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2015
【分類號(hào)】:P618.13;P631.4
本文編號(hào):2184291
[Abstract]:Fractured reservoir is an important oil and gas reservoir, which can be exploited efficiently by correctly understanding its spatial distribution law and internal structural characteristics. Fractured reservoir is formed by different geological forces, and its physical properties differ greatly from surrounding rocks. Its spatial distribution law and internal structural characteristics are complex and changeable. Fracture detection methods of pre-stack and post-stack seismic data, such as curvature, coherence, etc. But the spatial distribution and internal structural characteristics of fractured reservoirs obtained by these methods are not precise enough, and the detection accuracy of these methods needs to be further improved. In order to improve the understanding of fractured reservoirs, this paper focuses on numerical simulation and fracture detection. In order to improve the accuracy of numerical simulation and fracture detection, the curvature analysis should be used to improve the conventional numerical simulation and fracture detection methods. By comparing the coherence attributes of the original seismic data and the filtered seismic data, the influence of the tectonic filtering method on the fracture detection is discussed. (2) The influence of the resolution of seismic data on the fracture detection is analyzed. Several numerical simulations are carried out. The curvature attributes of each synthetic record are calculated and the effect of resolution on fracture detection is discussed by comparing the curvature attributes. (3) A modeling method and process based on ant tracking are proposed. Ant tracing technology can identify fractures more accurately than other methods. Ant tracing technology can identify fractures more accurately by changing ant tracing process and correlation. Ant tracing results of different parameter combinations are analyzed, and ant profiles with clear geological structure characteristics can be obtained. Combining the results of artificial seismic horizon correlation tracing and fault interpretation with the results of ant tracing, a more precise model can be established, which is helpful to improve the accuracy of numerical simulation results. (4) An azimuthal curvature detection method based on rosette analysis is developed. The conventional curvature attributes have obvious anisotropic characteristics and can not highlight the characteristics of fracture development at specific angles. The azimuthal curvature attributes are the basis of the curvature calculation method based on scanning dip. The azimuthal curvature attribute can enhance the display of the crack characteristics in a particular direction on the curvature attribute and provide a means to detect and display the crack development characteristics in a particular direction. Comparing with other methods, Rosette analysis is more accurate, which provides a solution for the azimuth information of azimuth curvature analysis method, and also improves the description of fracture development characteristics by azimuth curvature attributes in specific directions.
【學(xué)位授予單位】:成都理工大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2015
【分類號(hào)】:P618.13;P631.4
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,本文編號(hào):2184291
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