本文選題：致密砂礫巖 + 四性關系��； 參考：《長江大學》2017年碩士論文

【摘要】：隨著油氣資源需求持續(xù)增長,常規(guī)儲層油氣的勘探開發(fā)到達一個瓶頸期,世界關注的焦點逐步投入到非常規(guī)儲層,其中非常規(guī)儲層的致密砂礫巖儲層受到越來越多的關注。致密砂礫巖儲層流體性質識別遇到儲層巖性、物性復雜、非均質性強、孔隙結構復雜及儲層控制因素復雜等難題。本文針對致密砂礫巖儲層流體性質識別方法進行研究,不僅有重要的理論意義,還可以為致密砂礫巖儲層的勘探開發(fā)提供方法補充。本文以某油田低孔、低滲致密砂礫巖儲層為主要研究對象,以研究區(qū)提供的巖心數據、物性分析資料、試油數據、測井資料以及地質錄井信息為基礎,主要針對研究區(qū)內30多口井對儲層進行研究,形成了一套相對系統(tǒng)的致密砂礫巖儲層流體性質識別的測井資料解釋方法,建立了符合S區(qū)塊流體識別的評價標準。儲層的物理性質方面,研究區(qū)“四性”關系研究。發(fā)現研究區(qū)整體巖性復雜,較常規(guī)儲層砂礫巖含量較高,孔滲關系復雜,且層控作用強于巖性,因此,后面建立儲層參數解釋模型應考慮分層位進行研究,并進一步建立儲層“四性”關系圖版。儲層的典型儲層的測井響應特征及影響因素:從測井響應角度出發(fā),判斷儲層流體識別方法的基礎就在于不同流體的巖石物理特征對測井響應的貢獻大小。研究區(qū)最明顯的影響因素是巖性,尤其是礫石含量較高的電阻率曲線呈異常高值。建立儲層參數精細解釋模型:利用自然伽馬、聲波、密度和粒度中值等參數建立了孔隙度、滲透率和飽和度的模型。其中,對傳統(tǒng)的阿爾奇公式計算飽和度的模型進行改進,利用變巖電參數和等效巖石組分理論建立了EREM模型,提高了飽和度的計算精度。儲層流體性質識別方法研究:利用試油資料及測井資料,分別采用三孔隙度差、比值法、電阻率差、比值法、中子-密度相關系數法、等效巖石彈性模型法及電阻率-孔隙度交會圖版法判別S地區(qū)目標層組的氣、水層,并給出了各種方法的判別標準。在實際應用中,對目的層段的流體性質進行識別,建議結合試油資料,選用多種方法進行綜合流體性質判別,以期達到最為準確、可靠的識別效果。
[Abstract]:With the continuous increase of oil and gas resource demand, the exploration and development of conventional reservoir oil and gas reach a bottleneck period, and the focus of world attention is gradually put into unconventional reservoir, among which the dense sand and gravel reservoir of unconventional reservoir is paid more and more attention. The identification of fluid properties of tight sandstone and gravel reservoir is confronted with the problems of reservoir lithology, complex physical properties, strong heterogeneity, complex pore structure and complex reservoir control factors. In this paper, the method of identifying the fluid properties of dense gravel reservoir is studied, which is not only of great theoretical significance, but also can be used as a supplement to the exploration and development of dense sandstone and gravel reservoir. In this paper, the core data, physical property analysis data, oil test data, logging data and geological logging information provided by the study area are taken as the main research object of a low porosity and low permeability sand gravel reservoir in an oil field, which is based on the core data, physical property analysis data, oil test data, logging data and geological logging information provided by the study area. In this paper, more than 30 wells in the study area are studied, and a set of relatively systematic logging data interpretation method for identifying the fluid properties of dense sandy gravel reservoir is formed, and the evaluation criteria for fluid identification in S block are established. In terms of the physical properties of the reservoir, the relationship between the "four properties" of the study area is studied. It is found that the whole lithology of the study area is complex, the content of sandy gravel is higher than that of the conventional reservoir, the relationship between pore and permeability is complex, and the formation control action is stronger than that of lithology. Therefore, the stratification location should be considered in the later reservoir parameter interpretation model. And further establish the reservoir "four properties" relationship chart. Logging response characteristics and influencing factors of typical reservoirs: from the point of view of log response, the basis of identifying reservoir fluid is the contribution of petrophysical characteristics of different fluids to log response. The most obvious influencing factor in the study area is lithology, especially the abnormal high value of resistivity curve with high gravel content. The fine interpretation model of reservoir parameters is established: the porosity, permeability and saturation model are established by using natural gamma ray, acoustic wave, density and particle size median. Among them, the traditional Archie formula model for saturation calculation is improved, and the EREM model is established by using the variable rock electrical parameters and the equivalent rock component theory, which improves the accuracy of saturation calculation. Research on the identification method of reservoir fluid properties: using oil test data and logging data, adopting three porosity difference, ratio method, resistivity difference, ratio method, neutron-density correlation coefficient method, respectively. The equivalent rock elastic model method and the resistivity-porosity cross chart method are used to judge the gas and water layers of the target formation in S area and the criteria of these methods are given. In the practical application, the fluid properties of the target layer are identified, and it is suggested that combined with the oil test data, various methods should be used to judge the comprehensive fluid properties in order to achieve the most accurate and reliable recognition effect.
【學位授予單位】：長江大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：P618.13

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