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物探与化探  2025, Vol. 49 Issue (1): 138-147    DOI: 10.11720/wtyht.2025.2425
  方法研究信息处理仪器研制 本期目录 | 过刊浏览 | 高级检索 |
基于孔隙结构和多相渗流能力的鄂尔多斯盆地致密砂岩储层品质分类方法研究
徐风1(), 司兆伟1(), 梁忠奎1, 田超国1, 罗兰1, 郭宇航2
1.中国石油冀东油田公司勘探开发研究院,河北 唐山 063000
2.吉林大学 地球探测科学与技术学院,吉林 长春 130026
A method for quality classification of tight sandstone reservoirs in the Ordos Basin based on pore structures and multiphase seepage capacity
XU Feng1(), SI Zhao-Wei1(), LIANG Zhong-Kui1, TIAN Chao-Guo1, LUO Lan1, GUO Yu-Hang2
1. Exploration and Development Research Institute, Jidong Oilfield Company, PetroChina, Tangshan 063000, China
2. College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China
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摘要 

随着社会经济和科技的进步,在日常生活和工业领域,人们对于油气资源的需求不断增长,致密砂岩储层一直是勘探开发的重点。然而,致密砂岩储层参数和品质评价等问题仍然存在许多难点。本文通过对鄂尔多斯盆地神木气田太原组地层的岩石样品进行物性、孔隙结构、电性等实验测试,建立了孔渗关系模型、毛管压力预测模型和分类饱和度评价模型。此外,还基于I-Kr模型在井中获得了逐点变化的气水两相相对渗透率。提出了储层品质评价因子,综合考虑物性、孔隙结构和多相渗流能力,对目标研究区井段进行实际处理获得了较好的效果,该方法为致密砂岩储层品质测井评价提供了可靠的依据。

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徐风
司兆伟
梁忠奎
田超国
罗兰
郭宇航
关键词 致密砂岩毛管压力曲线储层品质相对渗透率    
Abstract

With the advancement of social economy and science and technology, the demand for oil and gas resources has been increasing in daily life and industry. Tight sandstone reservoirs have been the priority targets for the exploration and production of oil and gas resources. However, there still exist many challenges in assessing the parameters and quality of tight sandstone reservoirs. This study conducted experiments on the physical properties, pore structures, and electrical properties of rock samples from the Taiyuan Formation in the Shenmu gas field of the Ordos Basin. Based on this, it established a porosity-permeability relationship model, a capillary pressure prediction model, and a classification saturation assessment model. Besides, it obtained the relative permeability of gas and water phases, which varied point by point, from wells based on the I-Kr model. This study proposed the factors for assessing reservoir quality, which were applied to the target interval in the study area considering the physical properties, pore structures, and multiphase seepage capacity, yielding satisfactory assessment results. Therefore, the method of this study provides a reliable basis for the log-based assessment of the quality of tight sandstone reservoirs.

Key wordstight sandstone    capillary pressure curve    reservoir quality    relative permeability
收稿日期: 2023-10-13      修回日期: 2024-05-06      出版日期: 2025-02-20
ZTFLH:  P631  
基金资助:国家自然科学基金项目(42204122)
通讯作者: 司兆伟(1974-),男,高级工程师,研究方向为测井解释。Email:74521545@qq.com
作者简介: 徐风(1980-),男,高级工程师,研究方向为测井解释。Email:45468542@qq.com
引用本文:   
徐风, 司兆伟, 梁忠奎, 田超国, 罗兰, 郭宇航. 基于孔隙结构和多相渗流能力的鄂尔多斯盆地致密砂岩储层品质分类方法研究[J]. 物探与化探, 2025, 49(1): 138-147.
XU Feng, SI Zhao-Wei, LIANG Zhong-Kui, TIAN Chao-Guo, LUO Lan, GUO Yu-Hang. A method for quality classification of tight sandstone reservoirs in the Ordos Basin based on pore structures and multiphase seepage capacity. Geophysical and Geochemical Exploration, 2025, 49(1): 138-147.
链接本文:  
https://www.wutanyuhuatan.com/CN/10.11720/wtyht.2025.2425      或      https://www.wutanyuhuatan.com/CN/Y2025/V49/I1/138
标号 岩性 层组 长度/mm 直径/mm 孔隙度/% 渗透率/mD RQI 束缚水饱和度
X37-1 砂岩 太原组 45.12 25.25 5.21 0.1328 0.1597 0.7000
X37-2 砂岩 太原组 43.79 25.23 8.09 0.3935 0.2205 0.5693
X37-3 砂岩 太原组 42.21 25.22 10.39 0.5527 0.2306 0.4709
X37-4 砂岩 太原组 41.85 25.21 9.65 0.4676 0.2201 0.4101
X37-5 砂岩 太原组 45.12 25.22 9.76 0.6157 0.2512 0.4333
X37-6 砂岩 太原组 44.45 25.24 9.75 0.5235 0.2317 0.4601
X37-7 砂岩 太原组 41.79 25.19 10.08 0.4847 0.2193 0.4030
X37-8 砂岩 太原组 43.83 25.22 11.89 1.4168 0.3452 0.5264
X37-9 砂岩 太原组 41.06 25.22 11.12 0.7265 0.2556 0.3559
X37-10 砂岩 太原组 44.11 25.27 9.26 0.5261 0.2384 0.4198
X37-11 砂岩 太原组 47.12 25.25 10.88 1.1125 0.3198 0.4162
X37-12 砂岩 太原组 45.23 25.30 10.44 1.0861 0.3225 0.4399
X37-13 砂岩 太原组 42.50 25.29 8.58 0.6948 0.2846 0.4029
X37-14 砂岩 太原组 45.90 25.26 11.26 1.0869 0.3107 0.3425
X37-15 砂岩 太原组 43.58 25.28 10.34 1.2611 0.3492 0.3831
Table 1  太原组X37-2c1井岩石样品基本信息
Fig.1  太原组15块样品孔隙度和渗透率关系
Fig.2  太原组15块样品地层因素和孔隙度关系
Fig.3  太原组15块样品电阻率系数和含水饱和度关系
Fig.4  太原组15块样品毛管压力曲线分类
Fig.5  太原组15块样品地层因素与孔喉半径中值交会图
标号 AC/
(μs·m-1)
CNL/
%
DEN/
(g·cm-3)
GR/
API
RT/
(Ω·m)
RXO/
(Ω·m)
Shg60/
MPa
Shg40/
MPa
Shg30/
MPa
Shg20/
MPa
Shg10/
MPa
Shg5/
MPa
Shg1/
MPa
X37-1 208.2 9.25 2.57 111.85 52.83 39.77 175.11 24.24 7.54 2.79 1.20 0.75 0.01
X37-2 217.3 8.35 2.5 84.04 44.02 31.92 52.50 5.77 2.24 0.97 0.45 0.26 0.01
X37-3 218.02 8.1 2.51 67.95 39.54 28.42 19.42 2.26 1.19 0.85 0.62 0.51 0.01
X37-4 216.3 8.0 2.53 63.66 39.13 28.05 8.40 1.76 1.01 0.83 0.64 0.50 0.01
X37-5 208.53 10.24 2.59 83.86 54.8 37.21 10.74 1.94 1.08 0.70 0.53 0.41 0.01
X37-6 217.03 7.91 2.5 80.54 40.99 27.54 17.26 2.01 1.14 0.80 0.54 0.38 0.01
X37-7 218.55 7.54 2.48 65.38 39.03 25.7 7.86 1.51 0.95 0.71 0.52 0.39 0.01
X37-8 219.66 6.91 2.47 55.85 42.87 27.96 57.15 3.23 1.33 0.70 0.42 0.25 0.01
X37-9 214.09 7.5 2.52 56.29 41.97 26.64 4.81 1.16 0.83 0.63 0.48 0.33 0.01
X37-10 214.51 6.62 2.49 63.31 44.59 28.04 9.50 1.62 0.96 0.74 0.55 0.34 0.01
X37-11 215.51 6.74 2.48 63.22 44.87 28.27 9.31 1.45 0.82 0.52 0.35 0.21 0.01
X37-12 215.32 6.51 2.49 61.31 44.62 28.58 11.63 1.85 0.96 0.61 0.39 0.22 0.01
X37-13 215.13 6.63 2.49 59.68 44.59 28.78 7.83 1.47 0.85 0.54 0.35 0.21 0.01
X37-14 215.69 7.22 2.46 57.4 44.6 30.52 4.10 1.01 0.65 0.47 0.36 0.22 0.01
X37-15 208.11 9.38 2.54 70.68 54.42 38.48 6.22 1.27 0.70 0.42 0.25 0.15 0.01
Table 2  太原组毛管压力曲线预测样本
Fig.6  毛管压力曲线预测效果
Fig.7  毛管压力曲线预测应用实例X37-2C1井
Fig.8  基于I-Kr模型的连续气水相对渗透率计算实例
分类 物性 孔隙结构 渗流性能
一类 RQI>0.3 毛管压力一类 Krg/Krw>10
二类 0.3>RQI>0.2 毛管压力二类 10>Krg/Krw>0.01
三类 RQI<0.2 毛管压力三类 Krg/Krw<0.01
Table 3  太原组物性、孔隙结构和渗流性能分类阈值
因子 ωpc ωQ ωKS
权重 0.35 0.4 0.25
Table 4  因子权重设置
Fig.9  基于孔隙结构和渗流能力的综合储层品质分类计算实例
[1] 何庆, 韩学彬, 吴建东, 等. 低孔低渗储层参数解释模型的建立[J]. 西部探矿工程, 2009, 21(10):99-104.
[1] He Q, Han X B, Wu J D, et al. Establishment of parameter interpretation model for low porosity and low permeability reservoirs[J]. West-China Exploration Engineering, 2009, 21(10):99-104.
[2] 石玉江. 低渗透岩性油藏含油性与富集区测井评价研究——以鄂尔多斯盆地姬塬地区长8油层组为例[D]. 西安: 西北大学, 2011.
[2] Shi Y J. Study on oil-bearing property and logging evaluation of enriched areas in low permeability lithologic reservoirs—Taking Chang-8 reservoir group in Jiyuan area of Ordos Basin as an example[D]. Xi’an: Northwest University, 2011.
[3] 丁圣, 钟思瑛, 周方喜, 等. 高邮凹陷成岩相约束下的低渗透储层物性参数测井解释模型[J]. 石油学报, 2012, 33(6):1012-1017.
[3] Ding S, Zhong S Y, Zhou F X, et al. A logging interpretation model of physical property parameters confined by diagenetic facies of low-permeability reservoirs in Gaoyou sag[J]. Acta Petrolei Sinica, 2012, 33(6):1012-1017.
doi: 10.7623/syxb201206012
[4] 杜元凯, 吴寒, 马强, 等. 鄂尔多斯东部低渗砂岩储层饱和度解释方法[J]. 石油化工应用, 2017, 36(1):93-96.
[4] Du Y K, Wu H, Ma Q, et al. Reservoir saturation interpretation method of low permeability sandstone reservoir in eastern Ordos[J]. Petrochemical Industry Application, 2017, 36(1):93-96.
[5] Guo Y H, Pan B Z, Liu W B. A research on the relationship between resistivity index and relative permeability at different measurement conditions based on the pore structure[J]. Environmental Fluid Mechanics, 2016, 16(6):1129-1141.
[6] 王振阳. CX坳陷DY地区须家河组致密砂岩气储层测井评价方法研究[D]. 荆州: 长江大学, 2023.
[6] Wang Z Y. Study on logging evaluation method of tight sandstone gas reservoir in Xujiahe Formation in DY area of CX depression[D]. Jingzhou: Yangtze University, 2023.
[7] 刘瑞林, 朱广生. 用神经网络建立孔隙度预测模型[J]. 江汉石油学院学报, 1993(1):28-31.
[7] Liu R L, Zhu G S. An application of neural network to reservoir evaluating from seismic data:Express porosity prediction model[J]. Journal of Jianghan Petroleum Institute, 1993(1):28-31.
[8] 赵仕俊, 任荣亭, 马绍国. 基于线性拟合方法测量岩心孔隙度研究[J]. 石油仪器, 1997(4):10-11,62.
[8] Zhao S J, Ren R T, Ma S G. Study on measurement of core porosity based on linear fitting[J]. Petroleum Instruments, 1997(4):10-11,62.
[9] 张松扬, 严建文. 非线性声波孔隙率模型及其应用[J]. 石油地球物理勘探, 1998, 33(5):671-678,690-706.
[9] Zhang S Y, Yan J W. Non-linear acoustic porosity model and its application[J]. Oil Geophysical Prospecting, 1998, 33(5):671-678,690-706.
[10] 肖亮, 毛志强, 孙中春, 等. 最优化方法在复杂岩性储集层测井评价中的应用[J]. 断块油气田, 2011, 18(3):342-345.
[10] Xiao L, Mao Z Q, Sun Z C, et al. Application of optimization method in log evaluation of complex lithologic reservoir[J]. Fault-Block Oil & Gas Field, 2011, 18(3):342-345.
[11] 童强. 鄂尔多斯盆地史家湾—堡子湾地区长82-长9砂体构型及多因素耦合储层综合评价[D]. 西安: 西北大学, 2021.
[11] Tong Q. Sand body configuration of Chang 82-Chang 9 in Shijiawan-Baoziwan area of Ordos Basin and comprehensive evaluation of multi-factor coupling reservoir[D]. Xi’an: Northwest University, 2021.
[12] 张雁, 柳成志, 秦秋寒, 等. 利用人工神经网络预测砂岩储层渗透率[J]. 大庆石油学院学报, 2005, 29(4):10-11,32-137.
[12] Zhang Y, Liu C Z, Qin Q H, et al. Predicting reservoir permeability of sandstone by means of artificial neural network[J]. Journal of Daqing Petroleum Institute, 2005, 29(4):10-11,32-137.
[13] 石萍, 唐俊. 遗传算法在致密砂岩储层渗透率计算公式优化中的应用—以鄂尔多斯盆地环县地区延长组长8段为例[J]. 内蒙古大学学报:自然科学版, 2014, 45(4):365-371.
[13] Shi P, Tang J. Application of genetic algorithm to the optimization of the calculation formula for permeability of tight sandstone reservoir:Taking the number 8 of the Yanchang formation of Huan County oilfield in Ordos Basin as an example[J]. Journal of Inner Mongolia University:Natural Science Edition, 2014, 45(4):365-371.
[14] 成志刚, 宋子齐, 景成, 等. 苏里格东区致密气储层成岩储集相分类及特征[J]. 断块油气田, 2012, 19(5):577-582.
[14] Cheng Z G, Song Z Q, Jing C, et al. Classfication and characteristics of reservoir diagenetic facies for tight gas reservoir in eastern area of Sulige[J]. Fault-Block Oil & Gas Field, 2012, 19(5):577-582.
[15] 尹帅, 丁文龙, 单钰铭, 等. 利用致密砂岩储层电导率参数求取渗透率[J]. 岩性油气藏, 2016, 28(6):117-124.
[15] Yin S, Ding W L, Shan Y M, et al. Permeability calculation of tight sandstone reservoir by conductivity parameters[J]. Lithologic Reservoirs, 2016, 28(6):117-124.
[16] 萧高健. 鄂尔多斯盆地红河油田长8段致密裂缝砂岩储层表征及“甜点油层” 综合评价研究[D]. 武汉: 中国地质大学(武汉), 2022.
[16] Xiao G J. Study on reservoir characterization of tight fractured sandstone in Chang 8 member of Honghe Oilfield in Ordos Basin and comprehensive evaluation of “dessert reservoir”[D]. Wuhan: China University of Geosciences(Wuhan), 2022.
[17] Purcell W R. Capillary pressures-their measurement using mercury and the calculation of permeability therefrom[J]. Journal of Petroleum Technology, 1949, 1(2):39-48.
[18] Burdine N T. Relative permeability calculations from pore size distribution data[J]. Journal of Petroleum Technology, 1953, 5(3):71-78.
[19] 杨博. 致密油储层微观结构及甜点评价——以鄂尔多斯盆地定边东南部三叠系延长组长7油层组为例[D]. 西安: 西北大学, 2022.
[19] Yang B. Evaluation of reservoir microstructure and dessert in tight oil—A case study of Chang 7 oil formation in Yanchang Formation of Triassic in southeastern Dingbian,Ordos Basin[D]. Xi’an: Northwest University, 2022.
[20] 钟新宇. 河套盆地临河坳陷西部白垩系固阳组砂砾岩储层不同模态孔喉结构及渗流特征响应[D]. 西安: 西北大学, 2021.
[20] Zhong X Y. Pore throat structure and seepage characteristics response of glutenite reservoir of Cretaceous Guyang Formation in the west of Linhe Depression,Hetao Basin[D]. Xi’an: Northwest University, 2021.
[21] 邹佳儒, 霍守东. 基于测井数据驱动的相渗曲线预测方法研究[C]// 2021年中国地球科学联合学术年会, 2021.
[21] Zou J R, Huo S D. Research on phase permeability curve prediction based on logging data[C]// China Earth Science Joint Annual Conference, 2021.
[22] 白新庄. 神木气田新增探明储量区地震预测技术及应用效果[D]. 西安: 西安石油大学, 2015.
[22] Bai X Z. Seismic prediction technology and its application effect in the newly proven reserves area of Shenmu gas field[D]. Xi’an: Xi’an Shiyou University, 2015.
[23] 习丽英. 神木气田储层评价及井位优化部署[D]. 西安: 西安石油大学, 2015.
[23] Xi L Y. Reservoir evaluation and well location optimization in Shenmu gas field[D]. Xi’an: Xi’an Shiyou University, 2015.
[24] Li K, Williams W. Deter mination of capillary pressure fuction form resistivity data[J]. Transport in Porous Media, 2007, 67(1):1-15.
[25] Bian H Y, Li K W, Yang J H, et al. A modified method and experimental verification for estimating relative permeability from resistivity logging data[C]// Kuala Lumpur, 2014.
[26] 郭宇航. 基于渗流与导电特性的致密砂岩储层测井解释与产能预测[D]. 长春: 吉林大学, 2017.
[26] Guo Y H. Logging interpretation and productivity prediction of tight sandstone reservoir based on seepage and conductivity characteristics[D]. Changchun: Jilin University, 2017.
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