發(fā)布時(shí)間：2018-06-24 20:22

  本文選題：隨機(jī)模擬 + 孔隙度��； 參考：《吉林大學(xué)》2015年碩士論文

【摘要】：天然氣水合物的研究逐漸成為了世界上能源科學(xué)研究的熱點(diǎn)，它廣泛分布于極地凍土帶及海底，其資源量相當(dāng)巨大，有專家大膽估測(cè)天然氣水合物的含碳量是所有煤、石油和天然氣中碳含量的2倍，我國(guó)海域遼闊，天然氣水合物富集區(qū)域多。本文的研究目的和意義為利用對(duì)單井資料的分析和處理明確天然氣水合物礦體的層位并得到符合天然氣水合物儲(chǔ)集層的評(píng)價(jià)模型和方法；利用多井資料進(jìn)行隨機(jī)模擬研究以得到除井孔以外區(qū)域的孔隙度、含水合物飽和度分布情況，為研究區(qū)域水合物進(jìn)一步勘探和研究提供必要的參數(shù)和依據(jù)。 本文在分析天然氣水合物的物理性質(zhì)及研究區(qū)地層的物理性質(zhì)基礎(chǔ)上，明確了研究區(qū)域天然氣水合物的層位，在前人工作研究的基礎(chǔ)上建立了符合研究區(qū)域的孔隙度計(jì)算方法（校正后的密度孔隙度法）、飽和度計(jì)算方法（優(yōu)選阿爾奇公式及雙水模型）。同時(shí)本文提出了利用主成分分析法結(jié)合層內(nèi)差異法及聚類分析法對(duì)研究區(qū)井進(jìn)行自動(dòng)分層處理，利用主成分分析法是為了綜合各條高分辨率測(cè)井曲線的特征及減少用于分層的曲線條數(shù)方便計(jì)算，在利用層內(nèi)差異法處理之后做聚類分析可以避免一些尖刺造成的分層過(guò)細(xì)。在單井分層的基礎(chǔ)上，對(duì)分層數(shù)據(jù)做橫向?qū)Ρ确治龅玫接糜陔S機(jī)模擬研究的研究區(qū)的層面數(shù)據(jù)。 此次在Petrel軟件上利用隨機(jī)模擬的方法對(duì)井孔以外的屬性數(shù)據(jù)進(jìn)行模擬研究。綜合各隨機(jī)模擬方法的優(yōu)缺點(diǎn)及適用性選擇序貫高斯模擬作為模擬方法。隨機(jī)模擬一般分為數(shù)據(jù)準(zhǔn)備、模型建立及模擬三步。以井?dāng)?shù)據(jù)為主的數(shù)據(jù)主要包括井的基本信息數(shù)據(jù)、測(cè)井?dāng)?shù)據(jù)、測(cè)井解釋數(shù)據(jù)及分層數(shù)據(jù)等；利用處理得到層面數(shù)據(jù)建立模型，并在此基礎(chǔ)上對(duì)模型進(jìn)行網(wǎng)格劃分，每個(gè)網(wǎng)格平面上代表100m*100m、厚度上根據(jù)層厚等比例劃分精度一般在1m左右；在模擬之前，需對(duì)屬性數(shù)據(jù)做統(tǒng)計(jì)分析及空間相關(guān)性分析，統(tǒng)計(jì)分析包括均值、最值、方差、協(xié)方差及相關(guān)性系數(shù)等；空間相關(guān)性分析是為了得到滿足區(qū)域的變差函數(shù)模型。最終，在通過(guò)統(tǒng)計(jì)對(duì)比和抽樣法的檢驗(yàn)之后得到了反映全研究區(qū)的三維的屬性數(shù)據(jù)（孔隙度、含天然氣水合物飽和度）的分布。 在現(xiàn)有的資料的基礎(chǔ)上，本文處理得到的屬性分布基本反映了研究區(qū)的分布特征，孔隙度的分布較為準(zhǔn)確，，含天然氣水合物飽和度的分布在趨勢(shì)上基本符合，具體精度沒(méi)有孔隙度高，下一步需搜集更多的地質(zhì)、地震資料，完善儲(chǔ)層數(shù)據(jù)庫(kù)，這樣模擬的精度會(huì)更高。
[Abstract]:The research of natural gas hydrate has gradually become the hot spot of energy science research in the world. It is widely distributed in the polar frozen soil zone and seabed, and its resources are very large. Some experts boldly estimate that the carbon content of natural gas hydrate is all coal. The carbon content in oil and natural gas is twice as large as that in China, and there are many gas hydrate enrichment areas in China. The purpose and significance of this paper is to use the single well data analysis and processing to determine the horizon of the gas hydrate ore body and to obtain the evaluation model and method that accord with the gas hydrate reservoir. In order to obtain the distribution of porosity and hydrate saturation in the area other than the well hole, the random simulation of multi-well data provides necessary parameters and basis for further exploration and study of hydrate in the studied area. Based on the analysis of the physical properties of natural gas hydrate and the physical properties of strata in the study area, the layer of natural gas hydrate in the study area is determined in this paper. On the basis of previous studies, the methods of porosity calculation (density porosity method after correction) and saturation calculation method (optimal selection of Archie formula and two-water model) were established in accordance with the study area. At the same time, this paper puts forward to use principal component analysis method combined with intra-layer difference method and cluster analysis to deal with the automatic stratification of wells in the study area. The principal component analysis (PCA) is used to synthesize the characteristics of each high resolution logging curve and to reduce the number of curves used for stratification. Cluster analysis can be used to avoid the delamination caused by some spikes. On the basis of single well stratification, the stratified data are analyzed horizontally to obtain the stratified data of the study area used in the random simulation study. The method of random simulation is used to simulate the attribute data outside the well hole in Petrel software. Considering the advantages and disadvantages and applicability of each stochastic simulation method, Sequential Gao Si simulation is chosen as the simulation method. Random simulation is generally divided into three steps: data preparation, modeling and simulation. The data based on well data mainly include well basic information data, log interpretation data and stratified data. Each mesh plane represents 100mb, and the accuracy of dividing the thickness according to the scale of layer thickness is generally about 1m. Before the simulation, statistical analysis and spatial correlation analysis of attribute data are needed. The statistical analysis includes mean value, maximum value, variance, and so on. Covariance and correlation coefficient, etc. The spatial correlation analysis is to obtain the variation function model of satisfying region. Finally, the distribution of 3D attribute data (porosity, gas hydrate saturation) reflecting the whole study area is obtained by statistical comparison and sampling. On the basis of the existing data, the attribute distribution obtained in this paper basically reflects the distribution characteristics of the study area, the distribution of porosity is more accurate, and the distribution of gas hydrate saturation is basically consistent with the trend. The accuracy is not as high as porosity, the next step is to collect more geological, seismic data and improve reservoir database, so the accuracy of simulation will be higher.
【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】：2015
【分類號(hào)】：P618.13

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