本文關(guān)鍵詞：微地震位置和震源機制的快速波形反演及搜索引擎算法的研究　出處：《中國科學(xué)技術(shù)大學(xué)》2016年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 微地震 震源定位 震源機制 搜索引擎 鄰域算法

【摘要】：徽地震監(jiān)測已經(jīng)被廣泛應(yīng)用于礦場,地?zé)?和油氣行業(yè)。比如,它是頁巖氣開發(fā)中用來成像注水壓裂的裂縫分布的非常好的工具,微地震位置和震源機制等可以為現(xiàn)場工程師提供重要的信息來評估注水壓裂的效力等等。本文主要目的在于利用全波形匹配的方法來推斷微震位置和震源機制解,分別從兩個不同的方法出來研究這個問題。一方面,從波形反演的角度來同時獲得微震的位置和震源機制解。我們首先介紹一種基于梯度的方法來同時反演震源位置和震源機制,為了克服這種基于梯度的方法的局部極小值的問題,我們同時提出一種基于一種全局最優(yōu)化算法的快速波形反演算法。另一方面,從快速搜索的觀點來研究這個問題,我們提出應(yīng)用計算機科學(xué)行業(yè)的搜索引擎的概念來解決微震波形的匹配問題。本文中主要研究的兩個方法可以總結(jié)如下：1,微震位置和震源機制的快速彈性波全波形反演算法給定一個速度模型,我們首先在可能的震源位置網(wǎng)格點上計算好格林函數(shù)庫。反演過程中我們計算一個基于離散和預(yù)先準(zhǔn)備好的格林函數(shù)庫的近似的目標(biāo)函數(shù)。由于提前計算好了格林函數(shù),合成波形的計算變得快捷,從而使得我們能夠利用一種全局最優(yōu)化算法,鄰域算法,來實現(xiàn)同時反演震源位置和震源機制。該方法中的目標(biāo)函數(shù)應(yīng)用了包絡(luò)相關(guān)的概念來匹配高頻的波形數(shù)據(jù)。在事件檢測后,該方法并不需要拾取P和S波走時,我們利用波形殘差和相關(guān)系數(shù)來評價波形的擬合程度。我們利用合成和實際數(shù)據(jù)例子測試了該方法,在輸入數(shù)據(jù)中包含噪音和速度模型存在誤差的情況下,合成數(shù)據(jù)例子表明能夠較好的恢復(fù)出真實模型。我們同時測試了452個實際數(shù)據(jù)微震事件,并且和走時網(wǎng)格搜索算法進行了對比,快速波形反演得到的微震位置分布能夠和走時網(wǎng)格搜索算法結(jié)果一致。2.微震搜索引擎算法類似于互聯(lián)網(wǎng)搜索引擎,該方法能夠在1s內(nèi)同時估計出微震事件的位置和震源機制,來檢測注水壓裂過程。對于給定的采集系統(tǒng)和速度模型,我們首先在所有可能的位置網(wǎng)格點上計算所有可能的微震事件波形,從而建立一個搜索數(shù)據(jù)庫。然后通過計算機快速搜索技術(shù),多個隨機K維樹方法,根據(jù)數(shù)據(jù)庫中波形數(shù)據(jù)的振幅和相位信息來排列并建立一個索引。當(dāng)一個微震事件發(fā)生時,和輸入波形近似的最佳波形能夠通過匹配數(shù)據(jù)庫的特征很快地找到。該方法不僅僅返回一個最佳解,而是類似于互聯(lián)網(wǎng)搜索中的一個解集,因此我們可以利用得到的解集來進一步研究結(jié)果的置信度和解析度。同樣類似于互聯(lián)網(wǎng)搜索引擎,微震搜索引擎不需要其他輸入?yún)?shù)和處理經(jīng)驗：這樣,對于任何用戶結(jié)果都會一樣。我們同樣利用合成數(shù)據(jù)和實際數(shù)據(jù)例子驗證了該方法,結(jié)果顯示微震搜索引擎有很大的潛力應(yīng)用于微地震的實時監(jiān)測問題。
[Abstract]:Hui seismic monitoring has been widely used in mining, geothermal, and oil and gas industries. For example, it is a very good tool for imaging the distribution of fracturing fractures in shale gas development. The microseismic location and focal mechanism can provide important information for field engineers to evaluate the effectiveness of waterflooding fracturing. The main purpose of this paper is to infer the microseismic location and focal mechanism solution by using the method of full waveform matching. . Two different ways to study the problem. On the one hand. From the angle of waveform inversion, the location and focal mechanism of microearthquakes are obtained simultaneously. Firstly, we introduce a gradient-based method for simultaneous inversion of focal positions and focal mechanisms. In order to overcome the problem of local minima of this gradient-based method, we also propose a fast waveform inversion algorithm based on a global optimization algorithm. Look at this from the point of view of fast search. We put forward the concept of search engine in computer science industry to solve the problem of matching microseismic waveforms. The two main methods in this paper can be summarized as follows: 1. The fast elastic wave inversion algorithm for the location and focal mechanism of microearthquakes is given a velocity model. We first calculate the Green's function library on the grid point of the possible focal point. In the inversion we calculate an approximate objective function based on discrete and pre-prepared Green's function library. Lin function. The computation of synthetic waveforms becomes faster, which enables us to use a global optimization algorithm, neighborhood algorithm. The objective function of the method uses the concept of envelope correlation to match the high frequency waveform data. After event detection, the method does not need to pick up P and S wave travel time. We use waveform residuals and correlation coefficients to evaluate the fitting degree of waveforms. We use synthetic and practical data examples to test the method when the noise and velocity model errors are included in the input data. The synthetic data examples show that the real model can be recovered better. We also tested 452 actual data microseismic events and compared with the traveling time grid search algorithm. The microseismic location distribution obtained by fast waveform inversion can be consistent with the results of walking time grid search algorithm. 2.The microseismic search engine algorithm is similar to the Internet search engine. This method can simultaneously estimate the location and focal mechanism of microseismic events in 1 s to detect the fracturing process of water injection. For a given acquisition system and velocity model. We first calculate the possible microseismic event waveforms on all possible grid points, and then establish a search database. Then, through the computer fast search technique, several random K-dimensional tree methods are used. Arrange and build an index based on the amplitude and phase information of the waveform data in the database. When a microseismic event occurs. The best waveform similar to the input waveform can be quickly found by matching the features of the database. This method not only returns an optimal solution, but is similar to a solution set in Internet search. So we can use the solution set to further study the confidence and resolution of the results. Similar to the Internet search engine, the microseismic search engine does not need other input parameters and processing experience: so. For any user the results are the same. We also use synthetic data and real data examples to verify the method. The results show that the microseismic search engine has great potential to be applied to the real-time monitoring of micro-seismic problems.
【學(xué)位授予單位】：中國科學(xué)技術(shù)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：TE357.6;P631.4

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相關(guān)期刊論文 前1條

1 ;Seismogram Synthesis in Multi-layered Half-space Part Ⅰ. Theoretical Formulations[J];Earthquake Research in China;1999年02期

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本文編號：1359007