2010Xinjiang shiyou dizhiRequires access

Fluid-Density Inversion of Shaximiao Gas Reservoir in Western Sichuan Area

Shuguang Li, XU Tian-ji

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Abstract

The fluid-density changes from rich gas reservoir to water layer obviously, so it is a nice parameter of reservoir gas forecasting. This paper presents the method for calculating the fluid-density values of each reservoir using density logging and porosity data, according to the density-porosity least-square inversion method, calculated the fluid-density of reservoir in well. The inversed three dimensional fluiddensity results can be obtained based on the probabilistic neural network inversion method, and using the well fluid-density data and three dimensional seismic data. Application of this method to Shaximiao gas reservoir in a gas field of western Sichuan area has achieved very good results, providing important data support for reservoir prediction, gas-water identification and gas reservoir description in this area.

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What this paper is about

The fluid-density changes from rich gas reservoir to water layer obviously, so it is a nice parameter of reservoir gas forecasting. This paper presents the method for calculating the fluid-density values of each reservoir using density logging and porosity data, according to the density-porosity least-square inversion method, calculated the fluid-density of reservoir in well. The inversed three dimensional fluiddensity results can be obtained based on the probabilistic neural network inversion method, and using the well fluid-density data and three dimensional seismic data. Application of this method to Shaximiao gas reservoir in a gas field of western Sichuan area has achieved very good results, providing important data support for reservoir prediction, gas-water identification and gas reservoir description in this area.

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Available abstract

The fluid-density changes from rich gas reservoir to water layer obviously, so it is a nice parameter of reservoir gas forecasting. This paper presents the method for calculating the fluid-density values of each reservoir using density logging and porosity data, according to the density-porosity least-square inversion method, calculated the fluid-density of reservoir in well. The inversed three dimensional fluiddensity results can be obtained based on the probabilistic neural network inversion method, and using the well fluid-density data and three dimensional seismic data. Application of this method to Shaximiao gas reservoir in a gas field of western Sichuan area has achieved very good results, providing important data support for reservoir prediction, gas-water identification and gas reservoir description in this area.

Key concepts: Natural gas field, Geology, Inversion (geology), Porosity, Petroleum engineering, Well logging, Reservoir modeling, Natural gas

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