【摘要】：致密砂巖氣藏目前是最具勘探開發(fā)意義的非常規(guī)天然氣領(lǐng)域。由于致密砂巖孔隙度低、滲透率低、含氣飽和度低，滲流機理復(fù)雜，建立高精度的儲層孔滲飽解釋模型困難；非均質(zhì)性強，低阻氣層高低阻水層并存，致使致密砂巖含氣性評價困難；生產(chǎn)中壓裂措施對地層的影響，給致密砂巖氣層的儲層壓后產(chǎn)能預(yù)測帶來一系列挑戰(zhàn)。 開展致密砂巖儲層的滲流特征分析、建立高精度解釋模型、正確評價含氣性、準(zhǔn)確預(yù)測儲層產(chǎn)能，分析研究區(qū)的產(chǎn)氣、產(chǎn)水分布有助于指導(dǎo)致密砂巖油氣田的合理開發(fā)。 本文以蘇里格地區(qū)二疊系的盒8段致密砂巖氣層為目的層，圍繞儲層評價以及壓裂產(chǎn)能預(yù)測展開研究。 從儲層的儲集性分析展開，研究蘇里格地區(qū)致密砂巖的儲集特征、巖石學(xué)特征，分析礦物含量對產(chǎn)能的影響，分析含氣測井特征。從宏觀角度分析孔隙度、滲透率、含氣飽和度、氣水相對滲透率對致密砂巖滲流的影響。 在經(jīng)驗統(tǒng)計的基礎(chǔ)上，開展神經(jīng)網(wǎng)絡(luò)法建立孔滲飽的解釋模型。使用Elman_Adaboost強預(yù)測器進行孔隙度的計算，使用SVR進行滲透率和飽和度的計算。 從常規(guī)測井曲線的圖版法出發(fā)，建立含氣性評價的定性評價指標(biāo)，利用數(shù)學(xué)手段即小波分析、GRNN網(wǎng)絡(luò)曲線重構(gòu)法對常規(guī)測井曲線進行分析建立含氣性定量評價指標(biāo)。 最后綜合分析壓裂產(chǎn)能的影響因素及并預(yù)測壓裂產(chǎn)能。從壓裂產(chǎn)能的理論出發(fā)，分析壓裂產(chǎn)能的影響因素。重點討論測井參數(shù)和壓裂施工參數(shù)對壓裂產(chǎn)能的影響，并使用R型主成分分析法進行影響因素的降維分析，選出主要的影響因素�；谥鞒煞址治鲞x出的主因子，利用GRNN網(wǎng)絡(luò)建立單層產(chǎn)能的預(yù)測模型。對合試層段產(chǎn)能劈分方法的研究，在單層產(chǎn)能預(yù)測模型的基礎(chǔ)上建立GRNN單點產(chǎn)能預(yù)測模型，利用建立的GRNN單點產(chǎn)能預(yù)測模型對蘇里格地區(qū)致密砂巖氣藏進行井中預(yù)測，并分析蘇里格地區(qū)盒8段的產(chǎn)氣量、產(chǎn)水量進行預(yù)測分析，分析蘇里格盒8段的產(chǎn)氣、產(chǎn)水的分布特征。
[Abstract]:Tight sandstone gas reservoir is currently the most important unconventional natural gas field with exploration and development significance. Due to the low porosity, low permeability, low gas saturation and complex seepage mechanism of tight sandstone, it is difficult to establish a high precision pore and permeability saturation interpretation model of reservoir. It is difficult to evaluate the gas-bearing property of tight sandstone and the influence of fracturing measures on formation in production brings a series of challenges to the prediction of reservoir productivity after pressure in tight sandstone gas reservoir. The analysis of percolation characteristics of tight sandstone reservoir, the establishment of high precision interpretation model, the correct evaluation of gas-bearing property, the accurate prediction of reservoir productivity, the analysis of gas production and distribution of water production in the study area are helpful to guide the rational development of tight sandstone oil and gas field. This paper focuses on reservoir evaluation and fracturing productivity prediction based on tight sandstone gas reservoir of Bo8 member of Permian in Sulige area. In this paper, the reservoir characteristics and petrological characteristics of tight sandstone in Sulige area are studied. The effects of mineral content on productivity and gas logging characteristics are analyzed. The effects of porosity, permeability, gas saturation and relative permeability of gas and water on the permeability of tight sandstone are analyzed from the macroscopic point of view. On the basis of empirical statistics, a neural network method was developed to establish an interpretation model of pore and osmotic saturation. Elman_Adaboost strong predictor is used to calculate porosity and SVR is used to calculate permeability and saturation. Based on the chart method of conventional logging curve, the qualitative evaluation index of gas-bearing property is established, and the quantitative evaluation index of gas-bearing property is established by means of mathematical means, I. E. wavelet analysis GRNN network curve reconstruction method. Finally, the influencing factors of fracturing productivity and the prediction of fracturing productivity are analyzed synthetically. Based on the theory of fracturing productivity, the influencing factors of fracturing productivity are analyzed. The effects of logging parameters and fracturing operation parameters on fracturing productivity are discussed emphatically. The main influencing factors are selected by using R-type principal component analysis method to reduce the dimension of the factors. Based on the principal factor selected by principal component analysis (PCA), a single layer productivity prediction model is established by using GRNN network. Based on the single-layer productivity prediction model, the GRNN single-point productivity prediction model is established, and the GRNN single-point productivity prediction model is used to predict the tight sandstone gas reservoir in Sulige area. The gas production and water production of section 8 in Sulige area were analyzed, and the distribution characteristics of gas production and water production in section 8 of Sulige box were analyzed.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TE312

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