【摘要】：目前我國多數(shù)老油田已進入高含水開發(fā)階段，勘探和開發(fā)剩余油是這一階段的重點工作。隨著油田井網(wǎng)的加密，利用加密井提供的地質信息，通過儲層沉積相建模建立儲層砂體模型，能夠對分布在砂體中的剩余油的勘探和開發(fā)起到重要作用。 結合油田項目，調研了國際上比較流行的建模軟件——斯倫貝謝公司的Petrel軟件、挪威Roxar公司的RMS地質建模軟件，以及我國自主研發(fā)的建模軟件——GPTModel油藏地質建模軟件、數(shù)字油藏表征工具Direct，了解了這些建模軟件中沉積相建模的一般步驟和常用算法。最終選用Petrel軟件作為本次研究的建模工具。研究開始前首先收集了某油田區(qū)塊建模的相關數(shù)據(jù)，包括井位坐標、補心海拔、井軌跡、測井曲線、地震解釋斷層數(shù)據(jù)、地震解釋控制面數(shù)據(jù)等，，通過編程完成這些數(shù)據(jù)的格式轉換，并修正了部分錯誤數(shù)據(jù)。然后應用GPTMap軟件對測井曲線進行分層得到小層分層數(shù)據(jù)和斷點數(shù)據(jù)。接著在Petrel中根據(jù)地震解釋的斷層數(shù)據(jù)應用Fault modeling模塊建立斷層模型；按照網(wǎng)格精度要求應用Pillar gridding模塊建立三維構造模型；根據(jù)分層數(shù)據(jù)和斷點數(shù)據(jù)以及地震解釋的控制面數(shù)據(jù)應用Make horizons模塊建立地層模型。最后采用確定性建模方法將GPTMap中的沉積相圖導入Petrel中建立儲層沉積相模型，同時還采用隨機建模方法，具體是采用序貫指示模擬方法建立儲層沉積相模型。重點研究了序貫指示模擬算法，對該算法以及該算法的地質統(tǒng)計學基礎知識包括變差函數(shù)的計算、實現(xiàn)克立金估計等的數(shù)學原理進行了較為詳細的說明，并使用MATLAB工具計算了實驗變差函數(shù)，編程實現(xiàn)了普通克里金估計方法和序貫指示模擬方法。 本次研究的主要成果是建立了兩種沉積相模型。通過與確定性建模方法得到的模型進行比較，序貫指示模擬的模型與地質專家確定的沉積相模型是比較相符的。在數(shù)據(jù)量比較大的情況下，地質專家可依據(jù)序貫指示模擬的結果，手工修改沉積相圖，節(jié)約大量時間提高工作效率。
[Abstract]:At present, most of the old oil fields in China have entered the stage of high water cut development, and the exploration and development of remaining oil is the key work in this stage. With the infilling of oilfield well pattern and geological information provided by infilled well, the reservoir sand body model can be established by reservoir sedimentary facies modeling, which can play an important role in the exploration and development of remaining oil distributed in sand body. Combined with the oil field project, the international popular modeling software-Schlumberger 's Petrel software, the Norwegian Roxar's RMS geological modeling software, and the independently developed GPTModel reservoir geological modeling software are investigated. The digital reservoir characterization tool Direct, understands the general steps and common algorithms of sedimentary facies modeling in these modeling software. Finally, Petrel software is chosen as the modeling tool of this study. Prior to the beginning of the study, the relevant data of modeling in a certain oilfield block were collected, including well location coordinates, supplementary altitude, well trajectory, logging curve, seismic interpretation fault data, seismic interpretation control surface data, etc. Through programming to complete the format of these data conversion, and fixed part of the error data. Then GPTMap software is used to stratify the log curve to obtain the data of small layer stratification and fracture point. Then the fault model is established by using Fault modeling module in Petrel according to the seismic interpretation fault data, and the 3D structural model is built by using Pillar gridding module according to the requirements of grid precision. The stratigraphic model is established by using Make horizons module based on stratified data, fracture data and control surface data of seismic interpretation. In the end, the sedimentary facies diagram in GPTMap is introduced into Petrel to establish reservoir sedimentary facies model, and the stochastic modeling method is used to establish reservoir sedimentary facies model. The sequential indicator simulation algorithm is studied in detail. The basic knowledge of geostatistics of the algorithm, including the calculation of variation function, and the mathematical principle of realizing Kriging estimation, etc., are explained in detail. The experimental variation function is calculated by using MATLAB tool, and the general Kriging estimation method and sequential indicator simulation method are realized by programming. The main results of this study are the establishment of two sedimentary facies models. Compared with the model obtained by deterministic modeling method, the sequential indicative simulation model is in good agreement with the sedimentary facies model determined by geological experts. In the case of large amount of data geological experts can manually modify the sedimentary facies diagram according to the results of sequential indicator simulation and save a lot of time to improve the working efficiency.
【學位授予單位】：吉林大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：P618.13

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