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Evaluation Of Engineering Sweet Spots In Chang-7 Tight Oil Reservoir Of Dongrengou Block Of Dingbian Oilfield,Ordos Basin:Research And Application

Posted on:2019-01-27Degree:DoctorType:Dissertation
Country:ChinaCandidate:X H ZhouFull Text:PDF
GTID:1481305408999749Subject:Oil and Natural Gas Engineering
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Tight hydrocarbon,with tremendous development potential,is one of the most important unconventional resources in China.Accurate evaluation and matching of geologic sweet spots and engineering sweet spots are critical guarantees for economically-effective development of tight hydrocarbons by horizontal-well volume fracturing technology.In this paper,a series of studies were conducted on the Chang 7 tight oil reservoir in Dongrengou Block of Dingbian Oilfield,the Ordos Basin,such as rock mechanics parameters analysis and brittleness characterization of reservoir,simulation of present in-situ stress field,identification of natural fractures,and prediction of natural fracture distribution between wells.Based on the geologic sweet spots delineated,as well as the fluid and sand volumes in horizontal well fracturing treatment,the parameters used for evaluating the engineering sweet spots of tight oil reservoir in the study area were determined,and the evaluation criteria were established.Moreover,the favorable zones were predicted.The research results can provide crucial basis for deployment of horizontal well pattern in Dingbian Oilfield and also guide the evaluation of engineering sweet spots of tight oil reservoir in sandstone-mudstone formations in continental lake basins.The research results mainly involve five aspects.First,the Chang 7 tight oil reservoir was subdivided into layers for purpose of fine lithologic identification and prediction of sandstone distribution.Thus,several methods were combined to determine the lower limit of effective thickness of tight oil reservoir in the study area and the oil-bearing scope of each layer,so as to lay a geologic foundation for the evaluation of engineering sweet spots of tight reservoir.Second,the triaxial rock mechanical experiment was conducted to analyze the anisotropy of tight sandstone reservoir,and the volume density calculation method of fractures was used to quantitatively characterize the complexity of rock ruptures.A new index to evaluate rock brittleness,BEC,was introduced based on the energy evolution process,and it is correlated with the characterization results of complexity of rock ruptures.Accordingly,the calculation method of brittleness index suitable for tight sandstone reservoir was selected.Third,the predicted distribution of present in-situ stress field shows that the horizontal principal stress difference in the study area ranges between 2.0 MPa and 8.4 MPa,and it is generally high in the east part and low in the west part.Vertically,the in-situ stress presents a layered distribution.Fourth,based on outcrop data and core observations,the development of regional fractures in the study area was depicted in detail.A new fracture identification method combining log extreme value and R/S variable metric algorithm was proposed.This method can facilitate the accurate identification of vertical fracture distribution in tight sandstone reservoir.According to the data of outcrops,cores and conventional logging in dense well-pattern,the discrete fracture network(DFN)model was built by stochastic modeling,thus enabling the prediction of fractures between wells with conventional logging data.Fifth,reasonable indexes for predicting engineering sweet spots were selected on the basis of fluid volume and sand volume in horizontal well fracturing.Besides,the intervals of such indexes were determined according to the average monthly fluid production of horizontal well,the evaluation criteria for engineering sweet spots of tight oil reservoir in the study area were established,and the engineering sweet spots were predicted on the basis of geologic sweet spots.
Keywords/Search Tags:engineering sweet spots of tight oil reservoir, brittleness, in-situ stress field, regional fractures, discrete fracture network(DFN) model
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