川东南林滩场五峰组—龙马溪组深层页岩气储层脆性定量评价

Quantitative evaluation of brittleness of deep shale gas reservoirs of Wufeng- Longmaxi formations in Lintanchang area, southeastern Sichuan Basin

冯少柯 熊亮 尹帅 董晓霞 魏力民

FENG Shaoke XIONG Liang YIN Shuai DONG Xiaoxia WEI Limin

中国石化 西南油气分公司, 成都 610081 成都理工大学, 成都 610059 西安石油大学 地球科学与工程学院, 西安 710065

SINOPEC Southwest Oil and Gas Branch Company, Chengdu, Sichuan 610081, China Chengdu University of Technology, Chengdu, Sichuan 610059, China School of Earth Sciences and Engineering, Xi'an Shiyou University, Xi'an, Shaanxi 710065, China

随着深层页岩气储层岩石塑性的增加，其脆性特征难以通过传统评价方法进行准确表征。以川东南林滩场上奥陶统五峰组—下志留统龙马溪组一段深层页岩气储层为例，开展页岩样品的三轴岩石力学实验和断裂韧性实验，再结合深度学习对储层脆性进行综合定量评价。岩石力学实验和断裂韧性实验结果表明，随温度和压力的升高，页岩样品杨氏模量、泊松比和抗压强度均有所增加；①号层样品的脆性明显低于③号层样品；脆性较好的页岩样品应力—应变曲线波动特征明显，表现出非线性变形特征，残余应变值较小；页岩样品的断裂韧度与脆性矿物含量关系较为密切，纹层垂直于页理方向的样品Ⅰ型和Ⅱ型断裂韧度值较低。在考虑页岩物质组分特征、三轴岩石力学特征和断裂韧性特征的前提下，以脆性指数Bel和Bmine3、断裂韧性指数IKIC为数据基础，建立深度学习权重分析模型，累积风险值小于5，模型可靠性较强。根据模型建立综合脆性指数B，与岩心脆性测定值BS的相关性得到显著提高(R=0.852 7)。脆性定量评价结果对深层页岩储层纵向剖面的脆性特征进行了真实反映，研究区五峰组—龙一段③号层底部和②号层储层脆性较好，断裂韧性指数较小，为后期勘探开发的优选目的层。

With the increase in rock plasticity of deep shale gas reservoirs, their brittleness characteristics become difficult to be accurately characterized using traditional evaluation methods. Taking the deep shale gas reservoirs from the upper Ordovician Wufeng Formation to the first member of Lower Silurian Longmaxi Formation in the Lintanchang area of the southeastern Sichuan Basin as a case study, triaxial rock mechanics and fracture toughness experiments on shale samples were conducted. Based on the experimental results, a comprehensive quantitative evaluation of reservoir brittleness was carried out using deep learning. The experimental results showed that with the increasing temperature and pressure, the Young's modulus, Poisson's ratio, and compressive strength of the shale samples all increased. The brittleness of shale samples from layer ① was significantly lower than that of samples from layer ③. Shale samples with better brittleness exhibited obvious fluctuations in the stress-strain curves, showed nonlinear deformation characteristics, and had relatively small residual strain values. The fracture toughness of shale samples was closely related to the content of brittle minerals, and the fracture toughness values of type Ⅰ and type Ⅱ samples with laminations perpendicular to bedding planes were relatively lower. Based on the shale characteristics of mineral composition, triaxial rock mechanics, and fracture toughness, a deep learning weight analysis model was developed using brittleness indices Bel and Bmine3 and fracture toughness index IKIC as data inputs.The cumulative risk value was less than 5, indicating the high reliability of the model.A comprehensive brittleness index B was established based on the model, and its correlation with the measured brittleness index BS of core samples was significantly improved (R=0.852 7). The quantitative brittleness evaluation results truly reflect the vertical profile of brittleness characteristics in deep shale reservoirs. The reservoirs at layer ③ bottom and layer ② in the Wufeng-Longmaxi formations of the study area exhibit relatively better brittleness and lower fracture toughness index, making them preferred target layers for future exploration and development.

中国石化科技部项目 P21042-1;中国石化科技部项目 P23221

https://doi.org/10.11781/sysydz2025030742