【摘要】：在地質勘探中,為了獲得油氣等資源的分布情況,需要對地震數據進行解釋,而斷層解釋是地震數據解釋的重要內容。斷層是由于地下巖石層因為受到一定程度的壓力而產生破裂,并且沿著破裂面的方向產生相對錯位移動的地質現象。斷層導致油田的產生和分布,既是斷塊的油田的分界處,還是油氣移動的通路。在勘探石油、天然氣等資源的末期或者在開發(fā)這些資源時,解釋和弄清斷層在地下的大小和分布狀況,不管是對評估產量、產量建設,還是對于油藏的挖潛和管理都具有重大意義。本文通過對地震數據進行研究,對地下斷層大小和分布情況進行估計。常規(guī)的斷層解釋方法是用人工方法解釋,這種方法不僅工作量大,周期長,并且非常依賴解釋人員的專業(yè)知識和解釋經驗。因此,迫切需要一種斷層自動解釋方法。目前,國外商業(yè)軟件中只有斯倫貝謝(Schlumberger)公司開發(fā)的Petrel軟件實現了三維地震圖像上的斷層自動識別解釋,但是國內在這一領域尚屬空白,Petrel中斷層自動識別解釋的具體實現過程由于知識產權國內也無法獲得。本文以Petrel的處理方法和螞蟻追蹤算法為基礎,主要進行了如下工作:1、開發(fā)了基于螞蟻追蹤算法的三維地震圖像斷層自動識別方法。本文借鑒了Petrel的思想方法,首先用斷層增強屬性體進行預處理,突出斷層并抑制非斷層,然后用螞蟻追蹤算法在斷層增強屬性體上追蹤斷層,實現了斷層的自動識別。2、針對Petrel追蹤得到的結果中含有很多噪聲干擾的問題,本文從螞蟻追蹤算法模型角度入手,引入人工種子點和梯度一致性,結合基于帶精英策略的螞蟻追蹤算法和基于排序的螞蟻追蹤算法,對不同置信度的人工螞蟻給予不同的信息素更新策略,使人工螞蟻盡量在大斷層上追蹤,減少在非斷層結構上的追蹤。實際測試表明,該方法能有效抑制噪聲干擾。針對追蹤得到的斷層面上留有毛刺、空洞、分叉、缺口等問題,本文還運用數學形態(tài)學方法平滑和填補斷層面,并用三維地震圖像骨骼化算法細化斷層。實際測試表明,該方法能使斷層面更加清晰完整。3、為了評估本文方法的效果,我們用實際地震工區(qū)數據進行測試。實際測試表明,本文的方法能有效識別地震圖像上的斷層。相比Petrel,本文方法識別出的斷層連續(xù)性更好,大斷層更加清晰明顯,并且有效減少了噪聲的干擾。
[Abstract]:In geological exploration, in order to obtain the distribution of oil and gas resources, seismic data need to be interpreted, and fault interpretation is an important part of seismic data interpretation. Fault is a geological phenomenon that the underground lithosphere is fractured because of a certain degree of pressure and is relatively dislocated along the direction of the fracture surface. The formation and distribution of oil field caused by fault is not only the boundary of fault block oil field, but also the path of oil and gas migration. At the end of exploration for oil, natural gas and other resources, or in the development of these resources, explain and understand the size and distribution of faults underground, whether it is for assessing production, production construction, Or for the reservoir to tap potential and management are of great significance. In this paper, the size and distribution of underground faults are estimated by studying seismic data. The conventional fault interpretation method is interpreted by manual method. This method not only has a large workload and long period, but also relies heavily on the professional knowledge and interpretation experience of the interpreters. Therefore, there is an urgent need for an automatic fault interpretation method. At present, only the Petrel software developed by Schlumberger (Schlumberger) Company has realized automatic fault recognition and interpretation on 3D seismic images in foreign commercial software, but this field is still blank in China. The realization process of automatic fault identification and interpretation in Petrel is not available because of intellectual property rights. Based on the processing method of Petrel and ant tracking algorithm, the main work of this paper is as follows: 1. The automatic recognition method of 3D seismic image fault based on ant tracking algorithm is developed. This paper draws lessons from Petrel's thought and method, first uses fault enhancement attribute body to pre-process, protrudes fault and suppresses non-fault, then uses ant tracing algorithm to trace fault on fault enhancement attribute body, realizes automatic fault recognition. In order to solve the problem of noise disturbance in the result of Petrel tracking, this paper introduces artificial seed points and gradient consistency from the point of view of ant tracking algorithm model. Combined with ant tracking algorithm with elite strategy and ant tracking algorithm based on sorting, different pheromone updating strategies are given to artificial ants with different confidence levels, so that artificial ants can be traced on large faults as far as possible. Reduce tracking on non-fault structures. The experimental results show that the proposed method can effectively suppress noise interference. Aiming at the problems of burr, cavity, bifurcation and gap on the fault plane obtained by tracing, this paper also uses mathematical morphology method to smooth and fill the fault plane, and thinning the fault with three-dimensional seismic image skeleton algorithm. The actual test shows that the method can make fault plane more clear and complete. 3. In order to evaluate the effect of this method, we use the actual seismic data to test. Practical tests show that the proposed method can effectively identify faults in seismic images. Compared with the Petrel, method, the fault continuity is better, the large fault is clearer and more obvious, and the noise interference is reduced effectively.
【學位授予單位】：電子科技大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：P631.44;TP391.41

【參考文獻】

相關碩士學位論文 前1條

1 周彬;基于數學形態(tài)學的圖像處理算法研究[D];華北電力大學（北京）;2008年

，

本文編號：2304955