{"title":"案例教程,介绍如何结合地球物理、岩石物理和地质制约因素,生成安大略省马西森研究区的现实地质模型","authors":"F. Della Justina, Richard S. Smith, R. Vayavur","doi":"10.1190/geo2023-0522.1","DOIUrl":null,"url":null,"abstract":"The model that is used to explain potential-field data is highly dependent on the constraints applied in the modelling process. Many studies demonstrate the necessity of constraining gravity and magnetic models. However, typically they do not demonstrate the individual enhancements that come as a consequence of integrating each constraint into the geophysical model. In this paper, we show that when there are no constraints, it is possible to find an inverse model that is consistent with gravity data, but the model is unrealistic, as one sedimentary basin is too deep. Adding a depth weighting constraint can ensure the depth is correct, but all other features have the same depth, which is unrealistic. Including densities from a density compilation makes the densities at surface realistic, but the dips are all close to vertical and the thicknesses are similar, which is unrealistic. In this case, the inversion is believed to have found a local minimum close to the starting model. Reflection seismic data was used to constrain a two-dimensional (2D) modeling exercise (on multiple profiles) to determine the geometry of one sedimentary sub-basin. These 2D models were then combined to build a realistic three-dimensional (3D) starting model. An inversion from this model fixed the densities of each lithology, but allowed the thicknesses of the layers to vary. The resulting model was realistic, with the dips and thicknesses away from the seismic constraints being consistent with geological expectations. Although the fit to the data was much better than the previous model, it was poorer than hoped. If the densities were then allowed to vary within a realistic range of values, the fit could be improved so that both the fit to the data and the geologic model are realistic.","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":"62 16","pages":""},"PeriodicalIF":4.7000,"publicationDate":"2024-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A case-history tutorial describing the incorporation of geophysical, petrophysical and geological constraints to generate realistic geological models of the Matheson Study Area, Ontario\",\"authors\":\"F. Della Justina, Richard S. Smith, R. Vayavur\",\"doi\":\"10.1190/geo2023-0522.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The model that is used to explain potential-field data is highly dependent on the constraints applied in the modelling process. Many studies demonstrate the necessity of constraining gravity and magnetic models. However, typically they do not demonstrate the individual enhancements that come as a consequence of integrating each constraint into the geophysical model. In this paper, we show that when there are no constraints, it is possible to find an inverse model that is consistent with gravity data, but the model is unrealistic, as one sedimentary basin is too deep. Adding a depth weighting constraint can ensure the depth is correct, but all other features have the same depth, which is unrealistic. Including densities from a density compilation makes the densities at surface realistic, but the dips are all close to vertical and the thicknesses are similar, which is unrealistic. In this case, the inversion is believed to have found a local minimum close to the starting model. Reflection seismic data was used to constrain a two-dimensional (2D) modeling exercise (on multiple profiles) to determine the geometry of one sedimentary sub-basin. These 2D models were then combined to build a realistic three-dimensional (3D) starting model. An inversion from this model fixed the densities of each lithology, but allowed the thicknesses of the layers to vary. The resulting model was realistic, with the dips and thicknesses away from the seismic constraints being consistent with geological expectations. Although the fit to the data was much better than the previous model, it was poorer than hoped. If the densities were then allowed to vary within a realistic range of values, the fit could be improved so that both the fit to the data and the geologic model are realistic.\",\"PeriodicalId\":3,\"journal\":{\"name\":\"ACS Applied Electronic Materials\",\"volume\":\"62 16\",\"pages\":\"\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2024-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Electronic Materials\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1190/geo2023-0522.1\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1190/geo2023-0522.1","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
A case-history tutorial describing the incorporation of geophysical, petrophysical and geological constraints to generate realistic geological models of the Matheson Study Area, Ontario
The model that is used to explain potential-field data is highly dependent on the constraints applied in the modelling process. Many studies demonstrate the necessity of constraining gravity and magnetic models. However, typically they do not demonstrate the individual enhancements that come as a consequence of integrating each constraint into the geophysical model. In this paper, we show that when there are no constraints, it is possible to find an inverse model that is consistent with gravity data, but the model is unrealistic, as one sedimentary basin is too deep. Adding a depth weighting constraint can ensure the depth is correct, but all other features have the same depth, which is unrealistic. Including densities from a density compilation makes the densities at surface realistic, but the dips are all close to vertical and the thicknesses are similar, which is unrealistic. In this case, the inversion is believed to have found a local minimum close to the starting model. Reflection seismic data was used to constrain a two-dimensional (2D) modeling exercise (on multiple profiles) to determine the geometry of one sedimentary sub-basin. These 2D models were then combined to build a realistic three-dimensional (3D) starting model. An inversion from this model fixed the densities of each lithology, but allowed the thicknesses of the layers to vary. The resulting model was realistic, with the dips and thicknesses away from the seismic constraints being consistent with geological expectations. Although the fit to the data was much better than the previous model, it was poorer than hoped. If the densities were then allowed to vary within a realistic range of values, the fit could be improved so that both the fit to the data and the geologic model are realistic.
期刊介绍:
ACS Applied Electronic Materials is an interdisciplinary journal publishing original research covering all aspects of electronic materials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials science, engineering, optics, physics, and chemistry into important applications of electronic materials. Sample research topics that span the journal's scope are inorganic, organic, ionic and polymeric materials with properties that include conducting, semiconducting, superconducting, insulating, dielectric, magnetic, optoelectronic, piezoelectric, ferroelectric and thermoelectric.
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