本文選題：橫波分裂　切入點：裂縫屬性識別　出處：《吉林大學》2015年碩士論文　論文類型：學位論文

【摘要】：隨著我國經(jīng)濟的快速發(fā)展，，對油氣資源的需求也逐年增大。由于優(yōu)質(zhì)構(gòu)造型油氣藏勘探、開發(fā)目標的不斷減少，油氣勘探的方向開始轉(zhuǎn)向非常規(guī)油氣藏。裂縫性油氣藏分布范圍廣，已經(jīng)成為一個重要的勘探領域。與其它類型的油氣藏相比，裂縫性油氣藏具有裂縫系統(tǒng)分布復雜、儲層基質(zhì)物性較差、滲透性較差、原油采收率較低的特點，因此裂縫性油氣藏的開發(fā)具有相當大的難度，對裂縫屬性的識別研究是當前油氣勘探領域的重要課題之一。 當橫波在裂縫介質(zhì)中傳播時會發(fā)生橫波分裂現(xiàn)象，分裂成偏振方向相互垂直的快橫波和慢橫波。在通過多層裂縫介質(zhì)時，快橫波和慢橫波會發(fā)生再分裂現(xiàn)象，使波的傳播過程更加復雜。利用橫波分裂現(xiàn)象可以獲得地層的裂縫走向和裂縫密度信息，對裂縫性油氣藏研究有著重要意義。 本文用使用二維三分量HTI介質(zhì)正演模擬程序?qū)M波在雙層介質(zhì)中的再分裂現(xiàn)象進行模擬，探討了裂縫密度和裂縫方位角對橫波再分裂現(xiàn)象的影響。 在裂縫屬性識別方法中Pearson相關系數(shù)法具有抗噪性強，穩(wěn)定性高的特點。而Pearson相關系數(shù)法中對Pearson相關系數(shù)的求取是一個最優(yōu)化問題，粒子群算法是一種解決非線性最優(yōu)化問題的有效手段，因此本文將粒子群算法與Pearson相關系數(shù)法相結(jié)合對裂縫屬性進行識別，通過迭代自動識別出裂縫方位角和時差。 首先本文使用粒子群與Pearson相關系數(shù)相結(jié)合的方法對單道地震記錄進行裂縫屬性識別，結(jié)果表明該方法能對裂縫屬性進行很好地識別。然后，為了驗證該方法在噪聲環(huán)境下的有效性，對加入噪音的多道地震記錄其進行處理，并對識別結(jié)果進行統(tǒng)計分析，結(jié)果表明在噪聲環(huán)境下該方法也能很好地對識別裂縫屬性。通過將在噪聲環(huán)境下多道地震數(shù)據(jù)的識別結(jié)果與互相關法進行對比，該方法的抗噪性更強，識別效果更好。最后對上層為各向同性介質(zhì)下層為HTI介質(zhì)的雙層模型的地震記錄進行屬性識別也獲得了良好的識別效果。
[Abstract]:With the rapid development of China's economy, the demand for oil and gas resources has increased year by year. The direction of oil and gas exploration begins to turn to unconventional oil and gas reservoirs. The fractured reservoirs are widely distributed and have become an important exploration field. Compared with other types of reservoirs, fractured reservoirs have complex distribution of fracture systems. Because of the poor physical properties of reservoir matrix, poor permeability and low oil recovery, the development of fractured reservoirs is very difficult, and the identification of fracture attributes is one of the most important topics in the field of oil and gas exploration. When the shear wave propagates in the fractured medium, the shear wave splits into fast shear wave and slow shear wave, which are perpendicular to each other in the polarization direction. The wave propagation process is more complicated, and the information of fracture strike and fracture density can be obtained by using the shear wave splitting phenomenon, which is of great significance to the study of fractured oil and gas reservoirs. In this paper, the phenomenon of S-wave resplitting in double-layer medium is simulated by using two-dimensional three-component HTI medium forward simulation program, and the influence of crack density and crack azimuth on S-wave resplitting is discussed. In the fracture attribute identification method, the Pearson correlation coefficient method has the characteristics of strong noise resistance and high stability. However, the calculation of Pearson correlation coefficient in the Pearson correlation coefficient method is an optimization problem. Particle swarm optimization (PSO) is an effective method to solve nonlinear optimization problem. Therefore, this paper combines PSO with Pearson correlation coefficient method to identify fracture attributes, and automatically identify the azimuth and time difference of cracks by iterative method. Firstly, the method of particle swarm optimization combined with Pearson correlation coefficient is used to identify the fracture attributes of single channel seismic records. The results show that the method can identify the fracture attributes well. In order to verify the effectiveness of the method in noisy environment, the multi-channel seismic records with noise are processed, and the recognition results are statistically analyzed. The results show that the method can also be used to identify fracture attributes in noisy environment. By comparing the recognition results of multi-channel seismic data in noisy environment with the cross-correlation method, the method is more robust to noise. Finally, a good recognition effect is obtained for the seismic records of a bilayer model with isotropic medium in the upper layer and a HTI medium in the lower layer.
【學位授予單位】：吉林大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：P631.4;P618.13

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