本文選題：多重網(wǎng)格 + 泊松方程��； 參考：《電子科技大學(xué)》2017年碩士論文

【摘要】：地質(zhì)資料解釋在地質(zhì)基礎(chǔ)研究以及地質(zhì)石油研究領(lǐng)域有著廣泛的應(yīng)用,包括地質(zhì)構(gòu)造學(xué)、地質(zhì)地層學(xué)等。而三維地質(zhì)曲面的重建過(guò)程又是在工區(qū)范圍內(nèi)的地質(zhì)資料解釋過(guò)程中非常重要的一個(gè)環(huán)節(jié),它可以將地質(zhì)采集到的散點(diǎn)數(shù)據(jù)以更形象的方式呈現(xiàn)給地質(zhì)分析人員,進(jìn)而更好地了解地表以下的地質(zhì)形態(tài)以做出準(zhǔn)確的分析和判斷�，F(xiàn)階段對(duì)于三維點(diǎn)云曲面重建有兩種解決方法:第一種方法是利用三維可視化的建模軟件Petrel等利用點(diǎn)云曲面上各點(diǎn)的標(biāo)量函數(shù)值恢復(fù)出曲面;第二種方法則是利用點(diǎn)云中各點(diǎn)的法向量的方法重建出三維點(diǎn)云曲面,例如通過(guò)移動(dòng)立方體算法進(jìn)行三角面片的劃分進(jìn)而提取出等值面的方法來(lái)恢復(fù)出被采樣物體的表面。在對(duì)三維地質(zhì)曲面的實(shí)際采樣過(guò)程中,往往會(huì)混入大量大噪聲點(diǎn)和冗余點(diǎn),所在對(duì)點(diǎn)云曲面重建之前,先要對(duì)其進(jìn)行預(yù)處理。然而現(xiàn)有的解決辦法都是將點(diǎn)云各部分區(qū)域看作是無(wú)厚度且均勻分布的,并且沒(méi)有結(jié)合能夠體現(xiàn)點(diǎn)云數(shù)據(jù)拓?fù)涮卣鞯男畔?所以曲面恢復(fù)出的效果往往和實(shí)際需求有一定的差距。根據(jù)實(shí)際地質(zhì)曲面的情況,本文提出了相應(yīng)的基于多重網(wǎng)格的點(diǎn)云預(yù)處理及其表面重建的方法,并利用實(shí)際工區(qū)中的地質(zhì)曲面信息對(duì)本文提出的方案進(jìn)行了驗(yàn)證。本文完成的主要工作如下:1.在對(duì)地質(zhì)中常見(jiàn)的三維幾何體采樣過(guò)程中會(huì)混入噪聲點(diǎn)和冗余點(diǎn)以及重復(fù)采樣的現(xiàn)象,導(dǎo)致閉曲面點(diǎn)云的局部區(qū)域會(huì)出現(xiàn)一定的厚度,且厚度不均勻,針對(duì)這種情況,本文結(jié)合多重網(wǎng)格的思想以及點(diǎn)云中各點(diǎn)到各網(wǎng)格之間映射的思想提出了一種基于泊松方程的曲面重建方法。首先對(duì)帶厚度的閉曲面點(diǎn)云進(jìn)行一定的精簡(jiǎn)處理,包括在三維空間構(gòu)造立方體網(wǎng)格、將點(diǎn)云中各點(diǎn)至各單元網(wǎng)格映射、構(gòu)造邊長(zhǎng)為二倍步長(zhǎng)的網(wǎng)格以及構(gòu)造結(jié)構(gòu)元素的方法對(duì)點(diǎn)云進(jìn)行一系列的精簡(jiǎn)。得到簡(jiǎn)化后的點(diǎn)云之后,利用協(xié)方差法對(duì)點(diǎn)云中各點(diǎn)求法向量并使其方向朝向一致。然后將調(diào)整后的法向量的散度帶入三維泊松方程進(jìn)行多重網(wǎng)格迭代求解。最后利用移動(dòng)立方體算法將等值面提取出來(lái)。2.在對(duì)地質(zhì)勘探中常見(jiàn)的開(kāi)曲面的采樣過(guò)程中,容易混入大量的噪聲點(diǎn),導(dǎo)致采樣得到的開(kāi)曲面點(diǎn)云表面非常不平滑。為了將曲面重建后得到滿意的效果,所以需要對(duì)開(kāi)曲面點(diǎn)云進(jìn)行平滑處理,具體步驟包括:在工區(qū)內(nèi)的地質(zhì)開(kāi)曲面上進(jìn)行網(wǎng)格剖分、計(jì)算點(diǎn)云中各點(diǎn)的曲率信息、構(gòu)造二維泊松方程對(duì)點(diǎn)云坐標(biāo)進(jìn)行多重網(wǎng)格迭代。得到平滑后的點(diǎn)云之后,利用協(xié)方差法求出點(diǎn)云中各點(diǎn)的法向量信息并做一致化調(diào)整,并將調(diào)整后的法向量的散度帶入三維泊松方程進(jìn)行多重網(wǎng)格迭代求解,最終利用移動(dòng)立方體算法進(jìn)行等值面的提取。3.本文結(jié)合實(shí)際的工區(qū)情況,將上述提出的不同地質(zhì)曲面的重建方案應(yīng)用到真實(shí)地質(zhì)曲面中進(jìn)行了仿真,得到了重建后的曲面形狀,發(fā)現(xiàn)重建后的效果滿足實(shí)際需求。
[Abstract]:Geological data interpretation is widely used in the field of geological research and geological petroleum research, including geological tectonics, geological stratigraphy, etc., and the reconstruction of 3D geological surfaces is a very important link in the process of interpretation of geological data within the scope of the work area. The image is presented to the geological analyst to better understand the geological form below the surface in order to make accurate analysis and judgment. At the present stage, there are two solutions to 3D point cloud surface reconstruction. The first method is to use the 3D visualization modeling software Petrel to use the scalar function value of each point on the point cloud surface. The second method is to reconstruct the 3D point cloud surface by using the normal vector of each point in the point cloud. For example, the surface of the sample is recovered by dividing the triangulation surface by the moving cube algorithm to recover the surface of the sampled object. A large number of large noise points and redundant points are preprocessed before the point cloud surface is reconstructed. However, the existing solution is to consider each part of the point cloud as a non thickness and uniform distribution, and do not combine the information that can reflect the topological features of the point cloud data, so the effect of the surface recovery is often and actually needed. There is a certain gap. According to the actual geological surface, this paper puts forward the corresponding method of point cloud preprocessing and surface reconstruction based on multi grid, and uses the information of geological surface in the actual work area to verify the proposed scheme. The main work done in this paper is as follows: 1. the common three dimensions in geology are as follows. For this case, a Poisson equation based on the thought of multi grid and the idea of the mapping between the points in the point cloud and the meshes in the point cloud is proposed. The method of surface reconstruction. First, a certain reduction is made for the closed surface cloud with thickness, including building a cube grid in three-dimensional space, mapping the points in the point cloud to the cell grid, constructing a grid with two times the length of the edge and a series of simplification of the point cloud. After that, the covariance method is used to find the normal vector and direction of the points in the point cloud. Then the divergence of the adjusted normal vector is brought into the three-dimensional Poisson equation to solve the multigrid iteration. Finally, the moving cube algorithm is used to extract the equivalent surface of the.2. in the sampling process of the common surface of the geological exploration. The surface of the open surface point cloud is very unsmooth. In order to get a satisfactory result after the surface reconstruction, it is necessary to smooth the open surface point cloud. The concrete steps include: the mesh generation on the surface of the geological surface in the work area, the curvature information of each point in the point cloud, and the construction of two The dimensional Poisson equation is used to iterate the multi grid of point cloud coordinates. After getting the smooth point cloud, the covariance method is used to obtain the normal vector information of the points in the point cloud and make the uniform adjustment. Then the divergence of the adjusted normal vector is brought into the three-dimensional Poisson equation to solve the multi grid iteratively. Finally, the moving cube algorithm is used to do so. .3. in this paper, based on the actual work area, the reconstruction scheme of different geological surfaces proposed above is applied to the real geological surface to simulate the surface. The shape of the reconstructed surface is obtained, and the results after the reconstruction are found to meet the actual needs.

【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：P628

【參考文獻(xiàn)】

相關(guān)期刊論文 前9條

1 Bo Xu;Ancheng Xiao;Lei Wu;Liguang Mao;Youpu Dong;Lijun Zhou;;3D Seismic Attributes for Structural Analysis in Compressional Context: A Case Study from Western Sichuan Basin[J];Journal of Earth Science;2014年06期

2 許洪才;張德生;姚寶剛;張藝馨;;淺談地質(zhì)體層與塊的劃分[J];地層學(xué)雜志;2013年04期

3 張曉峰;呂良海;白永強(qiáng);白光;;城市地下空間模糊綜合評(píng)價(jià)方法研究[J];地下空間與工程學(xué)報(bào);2012年01期

4 ;3D visualization model and key techniques for digital mine[J];Transactions of Nonferrous Metals Society of China;2011年S3期

5 胡鋼;劉哲;徐小平;高瑞;;像素級(jí)圖像融合技術(shù)的研究與進(jìn)展[J];計(jì)算機(jī)應(yīng)用研究;2008年03期

6 張延玲;楊長(zhǎng)春;賈曙光;;地震屬性技術(shù)的研究和應(yīng)用[J];地球物理學(xué)進(jìn)展;2005年04期

7 崔宇紅,倪國(guó)強(qiáng),范宏深;基于模糊推理的紋理圖像融合方法研究[J];光學(xué)技術(shù);2005年01期

8 張曉丹,趙海,王剛,魏守智;不確定信息的模糊決策融合算法[J];東北大學(xué)學(xué)報(bào);2004年07期

9 范凱,陶然,周思永;模糊數(shù)據(jù)融合在目標(biāo)跟蹤中的應(yīng)用[J];北京理工大學(xué)學(xué)報(bào);2000年03期

相關(guān)博士學(xué)位論文 前3條

1 姚為;像素級(jí)和特征級(jí)遙感圖像融合方法研究與應(yīng)用[D];大連理工大學(xué);2011年

2 王大偉;基于特征級(jí)圖像融合的目標(biāo)識(shí)別技術(shù)研究[D];中國(guó)科學(xué)院研究生院（長(zhǎng)春光學(xué)精密機(jī)械與物理研究所）;2010年

3 李立新;散亂點(diǎn)集曲面重建的理論、方法及應(yīng)用研究[D];浙江大學(xué);2001年

相關(guān)碩士學(xué)位論文 前3條

1 連濤;二維/三維地震圖像的融合顯示技術(shù)研究[D];電子科技大學(xué);2013年

2 秦玉飛;多地震屬性數(shù)據(jù)融合體繪制技術(shù)研究[D];電子科技大學(xué);2013年

3 白永強(qiáng);基于模糊邏輯及神經(jīng)網(wǎng)絡(luò)的醫(yī)學(xué)圖像融合研究[D];西安電子科技大學(xué);2010年

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