珠江河口盆地北部西江24-3油田某油藏面控模型研究

xinmeng

珠江河口盆地北部西江24-3油田某油藏面控模型研究

Ager,2018, 2(3): 282-291

原文网址：http://www.astp-agr.com/index.php/Index/Index/detail?id=72

  随机建模技术是对储层进行描述及表征的一种方法，直到上世纪90年代，随机建模逐渐发展为国际上储层量化研究的核心技术。由于储层沉积相中的有效物性参数在分布上存在一定差异，且统计特征也不相同，使得相控属性随机建模技术得到发展。相控属性建模是通过沉积微相来约束并控制储层的物性参数分布，然后根据不同的微相类型进行井间插值或随机模拟，最后建立有效的储层属性模型。同时在建模过程中也面临着两大难题：建立合理的微相模型与使用合适的算法建立属性模型。

本文以西江24-3油田H3A油藏为研究对象进行储层属性建模研究。在岩心、测井等资料的基础上，对储层沉积微相进行了精细划分，并应用多点模拟方法建立了储层沉积微相模型；然后以沉积微相为约束条件应用序贯高斯算法建立了储层属性模型。通过建立非相控属性模型与相控属性模型进行对比，证明了相控属性模型与储层沉积微相的对应性较好，模型变化趋势与井上的分布特征吻合率较高。故而相控属性模型能较好地反映地下储层物性的空间分布特征，适合该地区的储层描述。最后对模型进行检验，统计井点刻画参数和随机模拟参数，证明了模拟结果的可靠性。

Study on facies-controlled model of a reservoir in Xijiang 24-3 oilfield in the Northern Pearl River Mouth Basin

Liao Zheng, Cheng Chen, Cheng Lu, Minhua Cheng

(Published: 2018-07-05)

CorrespondingAuthor and Email:Liao Zheng, zhengliao93@sina.com

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Citation: Zheng, L., Chen, C., Lu, C., Cheng, M. Study on facies-controlled model of a reservoir in Xijiang 24-3 oilfield in the Northern Pearl River Mouth Basin. Advances in Geo-Energy Research, 2018, 2(3): 282-291, doi: 10.26804/ager.2018.03.06.

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ArticleType: Original article

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Abstract：

    To better understand the internal structure of the Xijiang 24-3 Oilfield in the Northern Pearl River Mouth Basin, a reasonable and effective three-dimensional quantitative geological model is needed to characterize the distribution characteristics of the reservoir. Xijiang 24-3 Oilfield is a braided river delta deposition, which contains many sedimentary microfacies in three subfacies zones. The reservoir structure is complex and heterogeneous. The reservoir modeling research was conducted on the Xijiang 24-3 oilfield H3A reservoir. Analysis of the oilfield core, the well-logging, and seismic data, establish a regional structural model. The regional sedimentary microfacies model is simulated by multi-point geostatistics. The reservoir property model is established by using facies-controlled modeling technology with sedimentary microfacies as a constraint condition. A facies-controlled property model and a non-facies-controlled property model are established respectively. The facies-controlled model corresponds well with the sedimentary microfacies of the reservoir, and the variation trend of the model shows a higher coincidence rate with the distribution characteristics of the well. The facies-controlled model reflects the spatial distribution characteristics of the physical properties of the underground reservoir and is in accord with the actual geological understanding of the reservoir. This model also provides a reliable basis for the next stage of reservoir description and a basis for further exploration and development work.

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Keywords: Sedimentary facies, geological model, multi-point geostatistics, facies-controlled modeling, model verification.