Permeability (earth sciences)

About: Permeability (earth sciences) is a research topic. Over the lifetime, 15424 publications have been published within this topic receiving 288535 citations.

Modelling Water Flow in Unsaturated Porous Media: Accounting for Nonlinear Permeability and Material Heterogeneity

Abstract: Introduction.- Mathematical Models of Flow in Porous Media.- Numerical Solution of Flow Equations.- Computation of Inter-Nodal Permeabilities for Richards Equation.- Upscaling from Darcy Scale to Field Scale.- Flow in Binary Media with Heterogenous Hydraulic Diffusivity.- Flow in Binary Media with Heterogenous Air-Entry Pressure.

Optimization of Multiple Hydraulically Fractured Horizontal Wells in Unconventional Gas Reservoirs

Abstract: Accurate placement of multiple horizontal wells drilled from the same well pad plays a critical role in the successful economical production from unconventional gas reservoirs. However, there are high cost and uncertainty due to many inestimable and uncertain parameters such as reservoir permeability, porosity, fracture spacing, fracture half-length, fracture conductivity, gas desorption, and well spacing. In this paper, we employ response surface methodology to optimize multiple horizontal well placement to maximize Net Present Value (NPV) with numerically modeling multistage hydraulic fractures in combination with economic analysis. This paper demonstrates the accuracy of numerical modeling of multistage hydraulic fractures for actual Barnett Shale production data by considering the gas desorption effect. Six uncertain parameters, such as permeability, porosity, fracture spacing, fracture half-length, fracture conductivity, and distance between two neighboring wells with a reasonable range based on Barnett Shale information, are used to fit a response surface of NPV as the objective function and to finally identify the optimum design under conditions of different gas prices based on NPV maximization. This integrated approach can contribute to obtaining the optimal drainage area around the wells by optimizing well placement and hydraulic fracturing treatment design and provide insight into hydraulic fracture interference between single well and neighboring wells.

Correlations for predicting air permeabilities and 222Rn diffusion coefficients of soils.

Abstract: The rate of 222Rn gas transport through earthen materials controls 222Rn releases to the atmosphere and to indoor environments. The key soil-related parameters characterizing 222Rn transport in earthen materials are the 222Rn diffusion coefficient and the soil air permeability. Simple correlations have been developed for predicting the 222Rn diffusion coefficient and the air permeability of soils based on fraction of water saturation, total porosity, and arithmetic mean particle diameter. Correlations are based on 1,073 diffusion coefficient measurements and 137 soil air permeability measurements. The geometric standard deviations between the correlation predictions and the measurements are 1.98 for the diffusion coefficients and 2.31 for the soil air permeabilities.

A fuzzy logic approach for estimation of permeability and rock type from conventional well log data: an example from the Kangan reservoir in the Iran Offshore Gas Field

Abstract: Permeability and rock type are the most important rock properties which can be used as input parameters to build 3D petrophysical models of hydrocarbon reservoirs. These parameters are derived from core samples which may not be available for all boreholes, whereas, almost all boreholes have well log data. In this study, the importance of the fuzzy logic approach for prediction of rock type from well log responses was shown by using an example of the Vp to Vs ratio for lithology determination from crisp and fuzzy logic approaches. A fuzzy c-means clustering technique was used for rock type classification using porosity and permeability data. Then, based on the fuzzy possibility concept, an algorithm was prepared to estimate clustering derived rock types from well log data. Permeability was modelled and predicted using a Takagi-Sugeno fuzzy inference system. Then a back propagation neural network was applied to verify fuzzy results for permeability modelling. For this purpose, three wells of the Iran offshore gas field were chosen for the construction of intelligent models of the reservoir, and a forth well was used as a test well to evaluate the reliability of the models. The results of this study show that fuzzy logic approach was successful for the prediction of permeability and rock types in the Iran offshore gas field.