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The integration of seismic anisotropy and reservoir performance data for characterization of naturally fractured reservoirs using discrete feature network models

機譯：使用離散特征網(wǎng)絡(luò)模型整合地震各向異性和儲層性能數(shù)據(jù)表征天然裂縫性儲層

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This dissertation presents the development of a method for quantitative integration of seismic (elastic) anisotropy attributes with reservoir performance data as an aid in characterization of systems of natural fractures in hydrocarbon reservoirs. This new method incorporates stochastic Discrete Feature Network (DFN) fracture modeling techniques, DFN model based fracture system hydraulic property and elastic anisotropy modeling, and non-linear inversion techniques, to achieve numerical integration of production data and seismic attributes for iterative refinement of initial trend and fracture intensity estimates. Although DFN modeling, flow simulation, and elastic anisotropy modeling are in themselves not new technologies, this dissertation represents the first known attempt to integrate advanced models for production performance and elastic anisotropy in fractured reservoirs using a rigorous mathematical inversion. The following new developments are presented: .? Forward modeling and sensitivity analysis of the upscaled hydraulic properties of realistic DFN fracture models through use of effective permeability modeling techniques. .? Forward modeling and sensitivity analysis of azimuthally variant seismic attributes based on the same DFN models. .? Development of a combined production and seismic data objective function and computation of sensitivity coefficients. .? Iterative model-based non-linear inversion of DFN fracture model trend and intensity through minimization of the combined objective function. This new technique is demonstrated on synthetic models with single and multiple fracture sets as well as differing background (host) reservoir hydraulic and elastic properties. Results on these synthetic control models show that, given a well conditioned initial DFN model and good quality field production and seismic observations, the integration procedure results in convergence of both fracture trend and intensity in models with both single and multiple fracture sets. Tests show that for a single fracture set convergence is accelerated when the combined objective function is used as compared to a similar technique using only production data in the objective function. Tests performed on multiple fracture sets show that, without the addition of seismic anisotropy, the model fails to converge. These tests validate the importance of the new process for use in more realistic reservoir models.
機譯：本文提出了一種將地震（彈性）各向異性屬性與儲層性能數(shù)據(jù)進(jìn)行定量整合的方法的開發(fā)，以幫助表征油氣藏天然裂縫系統(tǒng)。該新方法結(jié)合了隨機離散特征網(wǎng)絡(luò)（DFN）裂縫建模技術(shù)，基于DFN模型的裂縫系統(tǒng)水力特性和彈性各向異性建模以及非線性反演技術(shù)，從而實現(xiàn)了生產(chǎn)數(shù)據(jù)和地震屬性的數(shù)值集成，從而可以迭代地細(xì)化初始趨勢。和斷裂強度估算。盡管DFN建模，流動模擬和彈性各向異性建模本身并不是新技術(shù)，但本文代表了首次嘗試使用嚴(yán)格的數(shù)學(xué)反演方法將裂縫性油藏的生產(chǎn)性能和彈性各向異性先進(jìn)模型進(jìn)行集成的嘗試。提出了以下新發(fā)展： ？通過使用有效的滲透率建模技術(shù)，對實際DFN裂縫模型的高檔水力特性進(jìn)行正向建模和敏感性分析。 。 ？基于相同DFN模型的方位變化地震屬性的正向建模和敏感性分析。 。 ？開發(fā)生產(chǎn)和地震數(shù)據(jù)相結(jié)合的目標(biāo)函數(shù)并計算靈敏度系數(shù)。 。 ？通過最小化組合目標(biāo)函數(shù)，DFN斷裂模型趨勢和強度的基于迭代模型的非線性反演。這項新技術(shù)在具有單個和多個裂縫集以及不同背景（宿主）儲層的水力和彈性特性的合成模型中得到了證明。這些綜合控制模型的結(jié)果表明，給定條件良好的初始DFN模型以及良好的現(xiàn)場生產(chǎn)和地震觀測結(jié)果，積分過程會導(dǎo)致具有單個和多個裂縫集的模型的裂縫趨勢和強度都趨于一致。測試表明，與僅在目標(biāo)函數(shù)中使用生產(chǎn)數(shù)據(jù)的類似技術(shù)相比，使用組合目標(biāo)函數(shù)可加快單個裂縫的收斂速度。對多個裂縫集進(jìn)行的測試表明，如果不添加地震各向異性，模型將無法收斂。這些測試驗證了在更實際的油藏模型中使用新工藝的重要性。

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  • 作者

    Will Robert A.;

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  • 年度 2004
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  • 正文語種 en_US
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