High-resolution geostatistical modeling of an intensively drilled heavy oil reservoir, the BQ 10 block, Biyang Sag, Nanxiang Basin, China. (June 2019)

• Record Type: Journal Article
• Authors: Ren, Shuangpo; Yao, Guangqing; Zhang, Ye
• Is Part Of: Marine and petroleum geology. Volume 104(2019)
• Page Start: 404
• Page End: 422
• Publication Date: 2019-06
• Subjects: BQ 10 block -- Reservoir characterization -- Geostatistical modeling -- SIS -- SGS; Submarine geology -- Periodicals; Petroleum -- Geology -- Periodicals; Géologie sous-marine -- Périodiques; Pétrole -- Géologie -- Périodiques; Petroleum -- Geology; Submarine geology; Periodicals; Electronic journals; 551.468
• DOI: 10.1016/j.marpetgeo.2019.03.026
• Languages: English
• ISSNs: 0264-8172

Abstract

Abstract: Establishing a high-resolution subsurface model is the ultimate goal of reservoir characterization. The "BQ 10 Block", in Biyang Sag of Nanxiang Basin in China, is a data-rich mature field with heavy oil deposits penetrated by over two hundred wells with an average well spacing of 75m. The aim of this study is to establish a three-dimensional high-resolution model of the BQ 10 reservoir and to accurately and efficiently derive its geological and geometrical properties. A geostatistical modeling study was carried out in combination with stratigraphic correlation, core observations, log interpretation, lithology estimation, and sedimentary facies analysis. Based on core and wireline log data, lithology and conventional well logs (i.e. resistivity, gamma ray, and spontaneous potential) were correlated first. Lithofacies data at cored well locations were grouped into petrofacies units based on reservoir quality data. Using a neural network method, petrofacies at uncored wells was predicted based on correlation with conventional well logs. For different petrofacies, statistical analyses revealed correlation between laboratory porosity and permeability with acoustic well logs. A petrofacies model was built alternatively with indicator kriging, truncated Gaussian simulation (TGS), and sequential indicator simulation (SIS). SIS with a 3D trend model was identified to give the most reasonable petrofacies distribution. Using this model, facies-controlled petrophysical property modeling was performed using sequential Gaussian simulation (SGS). A validation procedure based on "minimum acceptance criteria" was employed to ensure that the SIS/SGS realizations are consistent. For this data-rich reservoir, this study demonstrates an effective application of the standard geostatistical modeling techniques on constructing high-resolution reservoir models of a heavy oil reservoir. The final suite of models reveal a likely range of reservoir facies and petrophysical property distributions for BQ 10, which can be useful for designing heavy oil recovery operations. Highlights: High-resolution geostatistical modeling of an intensively drilled heavy oil reservoir. Hierarchical modeling framework integrating well facies with facies-controlled petrophysical measurements. Facies and petrophysical geostatistical parameters are useful for production optimization and analog studies.