玛湖凹陷风城组复杂岩性组合横波预测方法探索

doi:10.11720/wtyht.2024.1179

Abstract
Figure/Table
References
Related Citation (4)

Download: PDF (9611 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract

Research on shear-wave prediction for complex lithologic assemblages of the Permian Fengcheng Formation in the Mahu sag is critical but challenging for accurately identifying hydrocarbon accumulation zones in the sag.The key to the prediction is to make breakthroughs in petrophysical modeling based on different lithologies.Given various lithologic types and intricate mineral compositions,this study delved into petrophysical modeling based on different lithologies.Consequently,this study developed an interval-,lithology-,and model-specific shear-wave prediction technique for complex lithologies.Furthermore,it established a technique for building a dry rock matrix for alkali lake-type dolomitized tight reservoirs by highlighting the major rock mineral compositions and merging the same types of rock mineral compositions.Additionally,the self-consistent model was selected for shear-wave calculation in the petrophysical modeling of dolomitized sandstone reservoirs.These techniques have been applied in the Fengcheng Formation of the Mahu Sag,achieving encouraging application results in both the shear-wave prediction of complex lithologic assemblages and the prediction of sweet spots.This study will provide a basis for well deployment and reserves determination in the area and offer valuable experience for oil and gas exploration in similar areas.

Key words： petrophysical modeling shear-wave prediction alkali lake type tight reservoir complex mineral Mahu sag

Received: 05 May 2023 Published: 27 June 2024

ZTFLH:

P631.4

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Hou-Cai ZHONG
	Zhen-Yu LIU
	Zhe ZHU
	Lin QU
	Shan ZHANG
	Yan-Fei YAO
	Rong-Rong FAN

Cite this article:

Hou-Cai ZHONG,Zhen-Yu LIU,Zhe ZHU, et al. Exploring the shear-wave prediction method for complex lithologic assemblages of the Fengcheng Formation in the Mahu sag[J]. Geophysical and Geochemical Exploration, 2024, 48(3): 736-746.

URL:

https://www.wutanyuhuatan.com/EN/10.11720/wtyht.2024.1179 OR https://www.wutanyuhuatan.com/EN/Y2024/V48/I3/736

Complex lithology combination transverse wave prediction process

Core and thin section photos of typical well P₁f Formation volcanic rocks in Mahu Depression

S-wave prediction results of MH025 well volcanic section

Core and thin section photos of typical well P₁f Formation glutenite rocks in Mahu Depression

Shear wave estimation results of MH025 well sandstone model

Core and thin section photos of typical well P₁f Formation dolomitized sandstone in Mahu Depression

Simplified analysis of multiple minerals in dolomite reservoir

Shear wave estimation results of MH025 well dolomite sandstone section

Shear wave estimation results of MH025 well full well section

Cross plot of predicted shear wave and measured shear wave of P₁f on Manan slope

Inversion profile of P-wave and S-wave velocity ratio on Manan slope

Inversion plan of P-wave and S-wave velocity ratio on Manan slope
a—glutenite reservoir ;b—volcanic reservoir;c—dolomite reservoir

[1]	支东明, 曹剑, 向宝力, 等. 玛湖凹陷风城组碱湖烃源岩生烃机理及资源量新认识[J]. 新疆石油地质, 2016, 37(5):499-506.
[1]	Zhi D M, Cao J, Xiang B L, et al. Fengcheng alkaline lacustrine source rocks of Lower Permian in Mahu Sag in Junggar Basin:Hydrocarbon generation mechanism and petroleum resources reestimation[J]. Xinjiang Petroleum Geology, 2016, 37(5):499-506.
[2]	白雨, 汪飞, 牛志杰, 等. 准噶尔盆地玛湖凹陷二叠系风城组烃源岩生烃动力学特征[J]. 岩性油气藏, 2022, 34(4):116-127.
[2]	Bai Y, Wang F, Niu Z J, et al. Hydrocarbon generation kinetics of source rocks of Permian Fengcheng Formation in Mahu Sag,Junggar Basin[J]. Lithologic Reservoirs, 2022, 34(4):116-127.
[3]	谢月芳, 张纪. 岩石物理模型在横波速度估算中的应用[J]. 石油物探, 2012, 51(1):65-70.
[3]	Xie Y F, Zhang J. Application of petrophysical model in shear wave velocity estimation[J]. Geophysical Prospecting for Petroleum, 2012, 51(1):65-70.
[4]	马淑芳, 韩大匡, 甘利灯, 等. 地震岩石物理模型综述[J]. 地球物理学进展, 2010, 25(2):460-471.
[4]	Ma S F, Han D K, Gan L D, et al. A review of seismic rock physics models[J]. Progress in Geophysics, 2010, 25(2):460-471.
[5]	Han D H, Nur A, Morgan D. Effects of porosity and clay content on wave velocities in sandstones[J]. Geophysics, 1986, 51(11):2093-2107.
[6]	Castagna J P. Relationships between compressional-wave and shear-wave velocities in clastic silicate rocks[J]. Geophysics, 1985, 50(4):571.
[7]	Krief M, Garat J, Stellingwerff J, et al. A petrophysical interpretation using the velocities of P and S waves (full-waveform sonic)[J]. Log Analyst, 1990,31:355-369.
[8]	陈小根, 武立岐. 基于多元回归方法的岩石物理性质预测模型研究[J]. 现代矿业, 2018, 34(8):64-68.
[8]	Chen X G, Wu L Q. Study on the prediction model of rock physical property based on multiple regression method[J]. Modern Mining, 2018, 34(8):64-68.
[9]	李春鹏. 基于贝叶斯判定的反演域岩石物理交会[J]. 物探化探计算技术, 2018, 40(5):594-600.
[9]	Li C P. Rock physics crossplot in inversion domain based on Bayesian decision[J]. Computing Techniques for Geophysical and Geochemical Exploration, 2018, 40(5):594-600.
[10]	Pride S R. Relationships between seismic and hydrological properties[M]//Water Science and TechnologyLibrary. Dordrecht: Springer Netherlands,2005:253-290.
[11]	Lee M W. A simple method of predicting S-wave velocity[J]. Geophysics, 2006, 71(6):F161.
[12]	Xu S Y, White R E. A new velocity model for clay-sand mixtures1[J]. Geophysical Prospecting, 1995, 43(1):91-118.
[13]	郭栋, 印兴耀, 吴国忱. 横波速度计算方法与应用[J]. 石油地球物理勘探, 2007, 42(5):535-538.
[13]	Guo D, Yin X Y, Wu G C. Computational approach of S-wave velocity and application[J]. Oil Geophysical Prospecting, 2007, 42(5):535-538.
[14]	邵才瑞, 印兴耀, 张福明, 等. 利用常规测井资料基于岩石物理和多矿物分析反演横波速度[J]. 地球科学:中国地质大学学报, 2009, 34(4):699-707.
[14]	Shao C R, Yin X Y, Zhang F M, et al. Shear wave velocity inversion with routine well logs based on rock physics and multi-minerals analysis[J]. Earth Science-Journal of China University of Geosciences, 2009, 34(4):699-707.
[15]	Kazatchenko E, Markov M, Mousatov A, et al. Joint inversion of conventional well logs for evaluation of double-porosity carbonate formations[J]. Journal of Petroleum Science and Engineering, 2007, 56(4):252-266.
[16]	Kumar M, Han D H. Pore shape effect on elastic properties of carbonate rocks[C]// SEG Technical Program Expanded Abstracts 2005.Society of Exploration Geophysicists,2005:1477-1480.
[17]	吴志华, 印兴耀. 碳酸盐岩储层横波速度估算[C]// 深圳: SPG/SEG国际地球物理会议论文集,勘探地球物理学家学会,2011:56-59.
[17]	Wu Z H, Yin X Y. S-wave velocity prediction for carbonate reservoirs[C]// Expanded Abstracts of SPG/SEG International Geophysical Conference.Shenzhen, China: Society of Exploration Geophysicists,2011:56-59.
[18]	Sharma R, Prasad M, Surve G, et al. On the applicability of Gassmann model in carbonates[C]// SEG Technical Program Expanded Abstracts 2006.Society of Exploration Geophysicists,2006:1866-1870.
[19]	Eugenia R. Elastic rock properties of tight gas sandstones for reservoir characterization at Rulison Filed,Colorado[D]. Colorado: Colorado School of Mines, 2005.
[20]	印兴耀, 刘倩. 致密储层各向异性地震岩石物理建模及应用[J]. 中国石油大学学报:自然科学版, 2016, 40(2):52-58.
[20]	Yin X Y, Liu Q. Anisotropic rock physics modeling of tight sandstone and applications[J]. Journal of China University of Petroleum:Edition of Natural Science, 2016, 40(2):52-58.
[21]	李龙. 碎屑岩致密储层岩石物理模量定量表征[D]. 青岛: 中国石油大学(华东), 2014.
[21]	Li L. Quantitative characterization for rock physics modulus of tight clastic reservoir[J]. Qingdao:China University of Petroleum, 2014.
[22]	吕正祥, 廖哲渊, 李岳峰, 等. 玛湖凹陷二叠系风城组碱湖云质岩储层成岩作用[J]. 岩性油气藏, 2022, 34(5):26-37.
[22]	Lyu Z X, Liao Z Y, Li Y F, et al. Diagenesis of alkaline lacustrine dolomitic reservoirs of Permian Fengcheng Formation in Mahu Sag[J]. Lithologic Reservoirs, 2022, 34(5):26-37.
[23]	刘文彬. 准噶尔盆地西北缘风城组沉积环境探讨[J]. 沉积学报, 1989, 7(1):61-70.
[23]	Liu W B. Study on sedimentary environment of Fengcheng Formation at Northwest margin of Junggar Basin[J]. Acta Sedimentologica Sinica, 1989, 7(1):61-70.
[24]	雷海艳, 郭佩, 孟颖, 等. 玛湖凹陷二叠系风城组页岩油储层孔隙结构及分类评价[J]. 岩性油气藏, 2022, 34(3):142-153.
[24]	Lei H Y, Guo P, Meng Y, et al. Pore structure and classification evaluation of shale oil reservoirs of Permian Fengcheng Formation in Mahu Sag[J]. Lithologic Reservoirs, 2022, 34(3):142-153.
[25]	徐苗苗. 火山岩储层岩石物理建模与叠前地震反演方法研究[D]. 东营: 中国石油大学(华东), 2019.
[25]	Xu M M. Study on petrophysical modeling and prestack seismic inversion method of volcanic reservoir[D]. Dongying: China University of Petroleum(Huadong), 2019.
[26]	陈树民, 李来林, 赵海波. 松辽盆地白垩系火山岩储层岩石物理声学特性分析[J]. 岩石学报, 2010, 26(1):14-20.
[26]	Chen S M, Li L L, Zhao H B. Physical analysis of acoustic characteristics of Cretaceous volcanic rocks in the Songliao Basin[J]. Acta Petrologica Sinica, 2010, 26(1):14-20.
[27]	李福祥, 王雪, 张驰, 等. 基于边界点的支持向量机分类算法[J]. 陕西理工大学学报:自然科学版, 2022, 38(3):30-38.
[27]	Li F X, Wang X, Zhang C, et al. Support vector machine classification algorithm based on boundary points[J]. Journal of Shaanxi University of Technology:Natural Science Edition, 2022, 38(3):30-38.
[28]	于宝利, 赵小辉, 瞿建华, 等. 岩石物理建模技术在玛湖西斜坡储集层预测中的应用[J]. 新疆石油地质, 2016, 37(6):720-725.
[28]	Yu B L, Zhao X H, Qu J H, et al. Application of petrophysical modeling technique in favorable reservoir prediction in western slope of Mahu Sag,Junggar Basin[J]. Xinjiang Petroleum Geology, 2016, 37(6):720-725.
[29]	王贤, 郑伟, 党志敏, 等. 玛南地区中下二叠统有利储层预测[J]. 新疆石油天然气, 2021, 17(2):1-6.
[29]	Wang X, Zheng W, Dang Z M, et al. Prediction of favorable reservoirs of Middle and Lower Permian in Manan area[J]. Xinjiang Oil & Gas, 2021, 17(2):1-6.
[30]	冯有良, 张义杰, 王瑞菊, 等. 准噶尔盆地西北缘风城组白云岩成因及油气富集因素[J]. 石油勘探与开发, 2011, 38(6):685-692.
[30]	Feng Y L, Zhang Y J, Wang R J, et al. Dolomites genesis and hydrocarbon enrichment of the Fengcheng Formation in the northwestern margin of Junggar Basin[J]. Petroleum Exploration and Development, 2011, 38(6):685-692.
[31]	周琦杰. 基于岩石物理理论的致密砂岩等效模型构建及应用[D]. 东营: 中国石油大学(华东), 2017.
[31]	Zhou Q J. Construction and application of equivalent model of tight sandstone based on petrophysical theory[D]. Dongying: China University of Petroleum(Huadong), 2017.
[32]	李宏兵, 张佳佳. 多重孔岩石微分等效介质模型及其干燥情形下的解析近似式[J]. 地球物理学报, 2014, 57(10):3422-3430.
[32]	Li H B, Zhang J J. A differential effective medium model of multiple-porosity rock and its analytical approximations for dry rock[J]. Chinese Journal of Geophysics, 2014, 57(10):3422-3430.