摘要
现行的热储行业评价标准是基于有水优储(中高孔中高渗)制定的,按此标准我国大多数盆地的热储属于有水差储(中低孔低渗),故现行热储行业评价标准存在不适应性。另外,在地热资源预可行性勘查阶段,常用的评价方法需要大量的参数和数据,而这一阶段能获取的资料往往较少,因此,探索少参数的快速评价方法很有必要。松辽盆地重点油区的水热型砂岩热储具有中薄层中低孔低渗的特点,属于有水差储,本研究以此为例,探索研究有水差储的评价标准及少参数条件下热储的快速评价方法。首先,在了解了目的层热储的厚度、孔隙度和渗透率等基本特征的基础上,对其进行统计分析,应用黄金分割法划分等级,确定这些参数的评价标准。由于其属于低温热储,单井日产水量对热储的评价更为重要,选取开发区的砂体厚度、孔隙度、渗透率和单井日产水量数据,利用多元线性回归对其进行分析后构建热储评价公式,计算各评价单元的得分,并按照黄金分割法划分等级。将此方法的得分排名与现有2种评价方法的两两对比表明,纳入砂体厚度而弃用温度是合理的,且此方法的得分标准差较大,能够更好地反映各评价单元之间的差异,因此,此方法较为可行,针对有水差储制定的评价标准较为合理。本研究所确定的有水差储评价标准对其他盆地的热储评价有一定的参考意义,考虑到各盆地之间的差异,本研究确定的少参数快速评价方法对其他盆地不一定适用,但是确定评价公式的过程有借鉴意义。
Current industry criteria for geothermal-reservoir classification were established for high-quality hydrothermal systems(medium–high porosity and permeability).Consequently,most Chinese basinal reservoirs exhibit medium to low porosity and low permeability are misclassified as"poor,"rendering the standards inapplicable.Moreover,the multi-parameter methods commonly used in pre-feasibility assessments require extensive data sets that are seldom,available during early exploration phases.Rapid,low-parameter evaluation protocols are therefore urgently needed.[Objective]Hydrothermal sandstone reservoirs in the Songliao Basin's key oil-producing area are typified by medium–thin beds,medium–low porosity,and low permeability.These characteristics are traditionally labelled as"poor."Using these reservoirs as a case study,we recalibrate the classification criteria for low-quality hydrothermal systems and develop parsimonious,rapid-assessment protocols that minimize data requirements.[Methods]First,the fundamental reservoir characteristics(thickness,porosity,and permeability)were statistically analyzed.The Golden Section Method was applied to classify parameter levels and establish evaluation criteria.Second,given the limited temperature variation among the studied low-temperature geothermal reservoirs,single-well daily production rate emerged as a critical evaluation metric.Consequently,sand body thickness,porosity,permeability,and single-well daily production rate within the study area were selected as input variables.Multivariate linear regression analysis was employed to derive a geothermal reservoir evaluation formula.This formula was then used to calculate evaluation unit scores,with final grading established using the Golden Section Method.[Results]Pairwise comparison of the score rankings from this method against those of two established evaluation methods demonstrated the validity of incorporating sand body thickness while excluding temperature.Furthermore,the relatively high standard deviation of the scores obtained by this method enhances its ability to delineate variations among the evaluation units.Consequently,this approach demonstrates greater feasibility,and the formulated evaluation criteria are particularly well-suited for hydrothermal reservoirs with limited storage capacity.[Conclusion]The evaluation criteria for low-storage hydrothermal systems developed in this study provide a valuable reference for geothermal-reservoir assessment in other basins.While basin-specific heterogeneity limits the direct transferability of the concise,few-parameter rapid-assessment model,the methodological framework used to derive the evaluation equation offers a robust,replicable template for analogous studies.
作者
刘先录
胡光明
肖红平
周玉钦
张庭瑀
饶松
LIU Xianlu;HU Guangming;XIAO Hongping;ZHOU Yuqin;ZHANG Tingyu;RAO Song(School of Geosciences,Wuhan 430100,China;Hubei Engineering Research Center of Unconventional Petroleum Geology and Engineering,Wuhan 430100,China;Hubei Key Laboratory of Complex Shale Oil and Gas Geology and Development in Southern China,Wuhan 430100,China;PetroChina Research Institute of Petroleum Exploration and Development,Beijing 100083,China)
出处
《地质科技通报》
北大核心
2025年第4期185-200,共16页
Bulletin of Geological Science and Technology
基金
国家自然科学基金项目(41472097)
中国石油天然气股份有限公司油气与新能源板块2022—2023年度科技课题(2022KT2601)。
关键词
松辽盆地
水热型砂岩
有水差储
地热储层评价标准
地热储层评价方法
Songliao Basin
hydrothermal sandstone
poor-storage aquifer
geothermal-reservoir evaluation criterion
geothermal-reservoir assessment methodology
