本文選題：微地震勘探　切入點(diǎn)：初至自動(dòng)拾取　出處：《吉林大學(xué)》2017年碩士論文

【摘要】：利用水力壓裂技術(shù)對(duì)低滲透型油氣藏壓裂注水時(shí)會(huì)引發(fā)變化的地下應(yīng)力場(chǎng),致使地下巖層錯(cuò)動(dòng)開(kāi)裂而誘發(fā)微地震事件。目前國(guó)內(nèi)外微地震監(jiān)測(cè)技術(shù)是處理水力壓裂最為重要的手段,主要是通過(guò)在壓裂井附近排布三分量檢波器,對(duì)微地震有效事件進(jìn)行連續(xù)記錄,從而實(shí)現(xiàn)開(kāi)斷裂縫和油氣藏位置的實(shí)時(shí)監(jiān)測(cè)。微地震監(jiān)測(cè)技術(shù)以其獨(dú)有的優(yōu)勢(shì)能夠?qū)Φ叵铝芽p和壓裂效果進(jìn)行合理的解釋與評(píng)價(jià),進(jìn)一步為利用水力壓裂技術(shù)調(diào)整改造低滲透型油氣田提供理論依據(jù)和技術(shù)支持。微地震監(jiān)測(cè)技術(shù)需要實(shí)時(shí)、自動(dòng)的對(duì)檢波器接收的高密度微地震勘探資料進(jìn)行解釋,實(shí)現(xiàn)震源的高精度定位。而微地震初至拾取是實(shí)現(xiàn)高精度定位震源的重要環(huán)節(jié),在保證微地震記錄精度的基礎(chǔ)上,設(shè)計(jì)實(shí)時(shí)快速自動(dòng)穩(wěn)定的初至拾取算法,是提高微地震資料處理速度與野外監(jiān)測(cè)分析效率的關(guān)鍵。實(shí)際微地震資料有效信號(hào)的主要特點(diǎn)是頻率高、能量弱、持續(xù)時(shí)間短,且受復(fù)雜強(qiáng)隨機(jī)噪聲的嚴(yán)重干擾,導(dǎo)致信噪比極低。人工拾取微地震初至效率低且不能適應(yīng)實(shí)際生產(chǎn)的實(shí)時(shí)處理需求。傳統(tǒng)自動(dòng)拾取微地震初至算法如能量比算法、Akaike信息準(zhǔn)則(AIC)算法等,在拾取高信噪比微地震記錄初至?xí)r有一定的效果,但是在微地震資料質(zhì)量較差時(shí),其拾取結(jié)果難以滿意。本文從微地震有效信號(hào)與復(fù)雜噪聲的特征差異入手,分析了微地震隨機(jī)干擾的類型和特性,并對(duì)有效信號(hào)的時(shí)間特性進(jìn)行了全面系統(tǒng)的研究,并以此為基礎(chǔ)提出了基于模糊C-均值聚類(FCM)的微地震初至自動(dòng)拾取算法。該算法以微地震有效信號(hào)與噪聲的特征差異為理論基礎(chǔ),通過(guò)不斷優(yōu)化目標(biāo)函數(shù)得到能夠表征數(shù)據(jù)相似性程度的隸屬度矩陣。隸屬度矩陣的值大于某一預(yù)先設(shè)定的閾值時(shí),其值對(duì)應(yīng)的樣本點(diǎn)被劃分為有效信號(hào)類,認(rèn)為微地震數(shù)據(jù)的初至?xí)r刻是有效信號(hào)類的起始時(shí)刻。此外本文還給出了所選模糊指標(biāo)和隸屬度矩陣初始化參數(shù)的數(shù)值大小和原因,并詳細(xì)論證了所選參數(shù)的可行性和有效性。本文全面分析了FCM算法的拾取性能以及模擬與實(shí)際微地震資料的拾取效果。通過(guò)繪制受試者工作特征(ROC)曲線與誤差統(tǒng)計(jì)直方圖驗(yàn)證了本文算法拾取初至的可靠性與準(zhǔn)確性,最低能夠處理信噪比為-8d B的微地震數(shù)據(jù),且準(zhǔn)確率高達(dá)86%。將該算法應(yīng)用于模擬與實(shí)際微地震資料初至拾取,并與能量比算法和AIC算法進(jìn)行對(duì)比,對(duì)比結(jié)果表明本文算法拾取結(jié)果的準(zhǔn)確率優(yōu)于其他兩種算法,解決了傳統(tǒng)初至拾取算法在低信噪比時(shí)難以有效拾取微地震初至的難題。
[Abstract]:Using hydraulic fracturing technology, the underground stress field will change when fracturing water injection in low permeability reservoirs. At present, microseismic monitoring technology is the most important means to deal with hydraulic fracturing, mainly by arranging three-component geophone near fracturing wells. The effective events of microearthquakes are recorded continuously, so as to realize the real-time monitoring of fracture breaking and oil and gas reservoir location. The microseismic monitoring technology can explain and evaluate the underground fractures and fracturing effect reasonably with its unique advantages. It provides theoretical basis and technical support for the adjustment and reconstruction of low permeability oil and gas fields by hydraulic fracturing technology. Micro-seismic monitoring technology needs to interpret the high-density microseismic exploration data received by geophone in real time and automatically. To realize the high precision location of the earthquake source, and the detection of the first arrival of the micro-earthquake is an important link to realize the high-precision location of the earthquake source. On the basis of guaranteeing the precision of the micro-seismic record, a real-time, fast, automatic and stable algorithm of the first arrival pickup is designed. It is the key to improve the processing speed of microseismic data and the efficiency of field monitoring and analysis. The main characteristics of the effective signal of practical microseismic data are high frequency, weak energy, short duration and serious interference by complex and strong random noise. As a result, the signal-to-noise ratio (SNR) is extremely low. The initial arrival efficiency of manual pickup microearthquakes is low and can not meet the real time processing requirements. The traditional automatic pickup micro-seismic first arrival algorithm, such as the energy ratio algorithm and Akaike information criterion (AICI) algorithm, is used in this paper. There is a certain effect in picking up high signal-to-noise ratio (SNR) microseismic records, but when the quality of microseismic data is poor, it is difficult to obtain satisfactory results. This paper starts with the difference of the characteristics between the effective signals of micro-earthquakes and the complex noises. The types and characteristics of random interference of microearthquakes are analyzed, and the time characteristics of effective signals are studied systematically. Based on this algorithm, a fuzzy C- mean clustering algorithm for automatic pickup of microearthquakes is proposed. The algorithm is based on the differences between the characteristics of effective signals and noises of micro-earthquakes. Through continuous optimization of the objective function, a membership matrix can be obtained, which can represent the degree of similarity of the data. When the value of the membership matrix is larger than a predetermined threshold, the sample points corresponding to the values are divided into effective signal classes. It is considered that the initial arrival time of the microseismic data is the starting point of the effective signal class. In addition, the numerical value and reason of the initialization parameters of the selected fuzzy index and membership matrix are also given in this paper. The feasibility and validity of the selected parameters are demonstrated in detail. In this paper, the picking performance of the FCM algorithm and the pickup effect of simulated and actual microseismic data are comprehensively analyzed. The histogram verifies the reliability and accuracy of the algorithm. Microseismic data with a signal-to-noise ratio of -8dB can be processed at the minimum, and the accuracy is as high as 86. The algorithm is applied to the first arrival pickup of simulated and actual microseismic data, and compared with the energy ratio algorithm and the AIC algorithm. The comparison results show that the accuracy of the proposed algorithm is better than that of the other two algorithms, which solves the problem that the traditional first arrival pick-up algorithm is difficult to effectively pick up the initial arrival of micro-earthquakes at low SNR.
【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)】：TE357.1;P631.4

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