Abstract
Abstract The proportion of different lithofacies is essential to determine the net-gross ratio, which directly affects the calculation of oil and gas reserves. Under the condition of few wells, the reliability of different lithofacies proportions obtained using well data is poor because it is difficult to estimate the uncertainty variation range of different lithofacies proportions. The present study overcomes this problem using an uncertainty evaluation method for reservoir lithofacies proportion. First, different lithofacies proportions of the reservoir are determined using the well and seismic data and are considered as the most likely estimated. Based on the lithofacies proportion, the lithofacies models of the study area are developed. Second, uniform and random methods are applied to sample the lithofacies models, and then, the probability distribution functions of different lithofacies proportions are derived. Third, the three levels of lithofacies proportions in the study area are calculated using the method of quantile and discretization of the probability distribution. Finally, we take M gas field as a sample and compare the test results of the fixed and random well structures. The results show that the sampling results of the fixed well structure model significantly deviate under the influence of the extension direction of the channel and well pattern distribution. Therefore, it is suggested to use random well structure to determine the uncertainty distribution range of lithofacies proportion.
Highlights
Stochastic reservoir modeling technology has been extensively applied in oil and gas exploration and development
In the Association of American Petroleum Geologists Annual Meeting in 2005, many papers reported that the risks in the development of oil and gas fields largely came from the uncertainty of underground reservoir since it is usually underestimated [15]
Jin et al reported that the multiple solutions of stratigraphic correlation, uncertainty of reservoir physical parameters, and limitation of reservoir heterogeneity description are the main geological factors affecting the accuracy of reservoir modeling [18]
Summary
Stochastic reservoir modeling technology has been extensively applied in oil and gas exploration and development. In the early stage of oil and gas exploration and development, the uncertainties are more prominent when less drilling data are available [1,2,3] To reduce these risks, it is necessary to investigate and reduce the uncertainty of geological models [4,5,6]. Huo et al selected six geological variables that are the depth of oil–water interface, volume percentage of microfacies, width of the channel, influence coefficient of seismic data, range of physical parameters, and lower limit of effective reservoir permeability of an oil field in Bohai Bay for reservoir modeling [7]. Xue et al applied the technology proposed by Huo to the modeling of offshore oil and gas fields and selected the variables, such as the variogram, correlation between reservoir and seismic attributes, lower limit of porosity, oil saturation, volume coefficient, and oil–water interface [23, 24]. It is expected that this method can be more objective to estimate the proportion of the lithofacies even though only few wells are available
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