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A practical workflow for model-driven seismic inversion

Xin‐Quan Ma

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Abstract

Seismic inversion transforms reflectivity data into layer property which adds valuable interpretive benefits for reservoir characterization. Although seismic inversion is routinely conducted in reservoir interpretation projects, there are still pitfalls in using this technology. If not careful, risks exist which may lead to incorrect estimation of reservoir properties and in the worst case to wrong drilling. In this paper, a model-driven inversion is used as an example to devise a practical workflow for typical post-stack inversion projects. The devised workflow consists of (1) log calibration, (2) selection of a seismic trace near a well, (3) well tie analysis, (4) wavelet estimation, (5) seismic amplitude calibration, (6) low frequency model building, (7) inversion job parameterization, (8) volume inversion and (9) interpretation. The technical background of all steps is reviewed and methods of problem solving presented. Emphasis is placed on how to quality control each stage of a multi-step process so that uncertainty is reduced to a minimum. With careful data preparation and job parameterization, model-driven inversion produces both absolute and relative impedances, useful for more accurate stratigraphic interpretation and reservoir property determination.

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What this paper is about

Seismic inversion transforms reflectivity data into layer property which adds valuable interpretive benefits for reservoir characterization. Although seismic inversion is routinely conducted in reservoir interpretation projects, there are still pitfalls in using this technology. If not careful, risks exist which may lead to incorrect estimation of reservoir properties and in the worst case to wrong drilling. In this paper, a model-driven inversion is used as an example to devise a practical workflow for typical post-stack inversion projects. The devised workflow consists of (1) log calibration, (2) selection of a seismic trace near a well, (3) well tie analysis, (4) wavelet estimation, (5) seismic amplitude calibration, (6) low frequency model building, (7) inversion job parameterization, (8) volume inversion and (9) interpretation. The technical background of all steps is reviewed and methods of problem solving presented. Emphasis is placed on how to quality control each stage of a multi-step process so that uncertainty is reduced to a minimum. With careful data preparation and job parameterization, model-driven inversion produces both absolute and relative impedances, useful for more accurate stratigraphic interpretation and reservoir property determination.

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Available abstract

Seismic inversion transforms reflectivity data into layer property which adds valuable interpretive benefits for reservoir characterization. Although seismic inversion is routinely conducted in reservoir interpretation projects, there are still pitfalls in using this technology. If not careful, risks exist which may lead to incorrect estimation of reservoir properties and in the worst case to wrong drilling. In this paper, a model-driven inversion is used as an example to devise a practical workflow for typical post-stack inversion projects. The devised workflow consists of (1) log calibration, (2) selection of a seismic trace near a well, (3) well tie analysis, (4) wavelet estimation, (5) seismic amplitude calibration, (6) low frequency model building, (7) inversion job parameterization, (8) volume inversion and (9) interpretation. The technical background of all steps is reviewed and methods of problem solving presented. Emphasis is placed on how to quality control each stage of a multi-step process so that uncertainty is reduced to a minimum. With careful data preparation and job parameterization, model-driven inversion produces both absolute and relative impedances, useful for more accurate stratigraphic interpretation and reservoir property determination.

Key concepts: Inversion (geology), Seismic inversion, Well control, Workflow, Environmental geology, Geology, Seismic to simulation, Regional geology

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