{"title":"Simultaneous inversion of four physical parameters of hydrate reservoir for high accuracy porosity estimation","authors":"Yuning Yan, Hongbing Li","doi":"10.1111/1365-2478.13615","DOIUrl":null,"url":null,"abstract":"<p>Estimation of the porosity of a hydrate reservoir is essential for its exploration and development. However, the estimation accuracy was usually less certain in most previous studies that simply assumed that there is a linear relationship between the porosity and single-elastic wave velocities or other rock physical parameters, thus affecting the evaluation of the reserves. In the three-phase Biot-type equations that are fundamental to model a hydrate-bearing reservoir, porosity, alongside hydrate saturation, mineral constituent proportions and hydrate–grain contact factor, is non-linearly responded by density, compressional and shear wave velocities. To improve porosity estimation, we propose to invert simultaneously four-parameter (porosity, hydrate saturation, mineral constituent proportions and hydrate–grain contact factor) using an iteratively nonlinear interior-point optimization algorithm to solve a nonlinear objective function that is a summation of the squared misfits between the well log and three-phase Biot-type equation–modelled density, compressional and shear wave velocities. A test in Mount Elbert gas hydrate research well was conducted for the case of a gas hydrate stratigraphic test well where elastic wave velocities, density, porosity and mineral composition analysis data are available. The four-parameter inversion yielded a lower root mean square error for porosity (0.0245) across the entire well-logging section compared to previous estimations from the linear relationship, post-stacked and pre-stacked seismic traces as well as the pore-filling effective medium theory model applied to other well cases. Additionally, the other three parameters demonstrated good agreement with well logs. Inversion tests conducted at three additional hydrate sites also produced accurate results. Consequently, the new method surpasses previous approaches in porosity estimation accuracy.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geophysical Prospecting","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/1365-2478.13615","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
引用次数: 0
Abstract
Estimation of the porosity of a hydrate reservoir is essential for its exploration and development. However, the estimation accuracy was usually less certain in most previous studies that simply assumed that there is a linear relationship between the porosity and single-elastic wave velocities or other rock physical parameters, thus affecting the evaluation of the reserves. In the three-phase Biot-type equations that are fundamental to model a hydrate-bearing reservoir, porosity, alongside hydrate saturation, mineral constituent proportions and hydrate–grain contact factor, is non-linearly responded by density, compressional and shear wave velocities. To improve porosity estimation, we propose to invert simultaneously four-parameter (porosity, hydrate saturation, mineral constituent proportions and hydrate–grain contact factor) using an iteratively nonlinear interior-point optimization algorithm to solve a nonlinear objective function that is a summation of the squared misfits between the well log and three-phase Biot-type equation–modelled density, compressional and shear wave velocities. A test in Mount Elbert gas hydrate research well was conducted for the case of a gas hydrate stratigraphic test well where elastic wave velocities, density, porosity and mineral composition analysis data are available. The four-parameter inversion yielded a lower root mean square error for porosity (0.0245) across the entire well-logging section compared to previous estimations from the linear relationship, post-stacked and pre-stacked seismic traces as well as the pore-filling effective medium theory model applied to other well cases. Additionally, the other three parameters demonstrated good agreement with well logs. Inversion tests conducted at three additional hydrate sites also produced accurate results. Consequently, the new method surpasses previous approaches in porosity estimation accuracy.
期刊介绍:
Geophysical Prospecting publishes the best in primary research on the science of geophysics as it applies to the exploration, evaluation and extraction of earth resources. Drawing heavily on contributions from researchers in the oil and mineral exploration industries, the journal has a very practical slant. Although the journal provides a valuable forum for communication among workers in these fields, it is also ideally suited to researchers in academic geophysics.