| 基于高斯过程回归和高压压汞测定致密砂岩渗透率:以鄂尔多斯盆地长7段致密砂岩为例 |
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| 引用本文： | 王伟,许兆林,李维振,侯涛,李亚辉,白云云,朱玉双.基于高斯过程回归和高压压汞测定致密砂岩渗透率:以鄂尔多斯盆地长7段致密砂岩为例[J].地质科技通报,2022,41(4):30-37. |
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| 作者姓名： | 王伟 许兆林 李维振 侯涛 李亚辉 白云云 朱玉双 |
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| 作者单位： | 1.榆林学院化学与化工学院, 陕西 榆林 719000 |
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| 基金项目： | 榆林学院高层次人才科研启动基金项目18GK22国家自然科学基金41904128国家自然科学基金42062011陕西省科技厅项目2021SF-495 |
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| 摘 要： | 致密砂岩由于滑脱效应的存在, 其气测渗透率存在一定误差, 测定绝对渗透率对明确致密砂岩渗流特征有重要意义。高斯过程回归方法是目前最先进的机器学习算法, 在处理石油领域非线性和多维数复杂问题具有优势。以鄂尔多斯盆地姬塬地区长7段致密砂岩为研究对象, 将平方指数(SE)和马特恩(Matern)函数作为高斯过程回归模型中两个协方差函数, 通过高压压汞测试的孔隙度、未饱和汞体积比、门槛压力和分形维数来预测致密砂岩的绝对渗透率, 并结合误差分析来研究不同协方差模型预测渗透率的效果。结果表明, 马特恩协方差(Matern)模型的相对误差均值(MMRE)、均方根误差(RMSE)、标准偏差(STD)分别为32%, 0.16和0.57, 准确度较高, 尤其当渗透率小于0.1×10-3 μm2时, 马特恩协方差(Matern)模型精度明显好于平方指数协方差(SE)模型和Winland经验公式。致密砂岩用马特恩模型预测渗透率精度更高。此外, 敏感性分析表明孔隙度对渗透率正影响最大, 门槛压力对渗透率负影响最大; 杠杆值和标准化残差证明高斯过程回归模型预测渗透率的有效性。综上, 马特恩协方差(Matern)模型对渗透率小于0.1×10-3 μm2致密砂岩适用性好, 对微纳米级孔喉发育的致密砂岩勘探评价有重要意义。
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| 关 键 词： | 渗透率测定 致密砂岩 高斯过程回归 高压压汞 分形维数 鄂尔多斯盆地 |
| 收稿时间： | 2021-01-08 |
Determination of permeability in tight sandstone reservoirs using Gaussian process regression and high-pressure porosimetry: A case study of the Member-7 of Yanchang Formation in the Jiyuan area of the Ordos Basin |
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| Affiliation: | 1.School of Chemistry and Chemical Engineering, Yulin University, Yulin Shaanxi 719000, China2.Oil Production Plant No.1 of Changqing Oilfield Company, PetroChina, Yan'an Shaanxi 716000, China3.Department of Geology, Northwest University, Xi'an 710069, China |
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| Abstract: | Because of the Klinkenberge effect in tight sandstones, errors exist forusing air permeability to reflect its reality, and it is thus important to determine the absolute permeability of tight sandstone.The Gaussian process regression (GPR), a state-of-the-art machine learning algorithm, has advantages in dealing with nonlinear and multidimensional complex problems in the petroleum industry. In this paper, the tight sandstone of the Member-7 of Yanchang Formation in the Jiyuan area of the Ordos Basin was taken as a sample to adopt the GPR model. In the model, the squared exponential and Matern covariance functions were taken as two covariance functions. The absolute permeability of tight sandstone was predicted by parameters including the porosity, volume ratio of unsaturated mercury, displacement pressure and fractal dimension measured by high-pressure porosimetry experiments, and the precision of different GPR models in predicting permeability were studied in combination with error analysis. The results indicate that GPR with Matern gives high precision with a mean magnitude relative error (MMRE), root mean square error (RMSE) and standard deviation (STD) equal to 32%, 0.16 and 0.57, respectively. Particularly, if the permeability is less than 0.1×10-3 μm2, the precision of the Matern model is obviously better than that of the squared exponential model and Winland model, so the Matern model has higher precision for permeability prediction of tight sandstones. In addition, sensitivity analysis reveals that porosity and displacement pressure have the highest and lowest absolute impact values on permeability estimation. The applicability and effectiveness of the GPR model are also demonstrated by means of leverage values and standardized residuals. Therefore, the Matern model can better predict tight sandstone reservoirs with permeabilities less than 0.1×10-3 μm2, and this model plays an important role in the exploration and evaluation for tight sandstone reservoirs. |
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