Applications of statistical physics to the oil industry: Predicting oil recovery using percolation theory

P. R. King; S. V. Buldyrev; N. V. Dokholyan; S. Havlin; Y. Lee; G. Paul; H. E. Stanley; N. Vandesteeg

doi:10.1016/S0378-4371(99)00327-1

Applications of statistical physics to the oil industry: Predicting oil recovery using percolation theory

P. R. King
, S. V. Buldyrev
, N. V. Dokholyan
, S. Havlin
, Y. Lee
, G. Paul
, H. E. Stanley
, N. Vandesteeg

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

In this paper we apply scaling laws from percolation theory to the problem of estimating the time for a fluid injected into an oil field to breakthrough into a production well. The main contribution is to show that, when these previously published results are used on realistic data, they are in good agreement with results calculated in a more conventional way but they can be obtained significantly more quickly. As a result they may be used in practical engineering circumstances and aid decision-making for real field problems.

Original language	English (US)
Pages (from-to)	S105-S117
Journal	Petroleum Geoscience
Volume	7
DOIs	https://doi.org/10.1016/S0378-4371(99)00327-1
State	Published - 2001

All Science Journal Classification (ASJC) codes

Fuel Technology
Geology
Geochemistry and Petrology
Economic Geology
Earth and Planetary Sciences (miscellaneous)

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10.1016/S0378-4371(99)00327-1

Cite this

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title = "Applications of statistical physics to the oil industry: Predicting oil recovery using percolation theory",

abstract = "In this paper we apply scaling laws from percolation theory to the problem of estimating the time for a fluid injected into an oil field to breakthrough into a production well. The main contribution is to show that, when these previously published results are used on realistic data, they are in good agreement with results calculated in a more conventional way but they can be obtained significantly more quickly. As a result they may be used in practical engineering circumstances and aid decision-making for real field problems.",

author = "King, \{P. R.\} and Buldyrev, \{S. V.\} and Dokholyan, \{N. V.\} and S. Havlin and Y. Lee and G. Paul and Stanley, \{H. E.\} and N. Vandesteeg",

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language = "English (US)",

volume = "7",

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T1 - Applications of statistical physics to the oil industry

T2 - Predicting oil recovery using percolation theory

AU - King, P. R.

AU - Buldyrev, S. V.

AU - Dokholyan, N. V.

AU - Havlin, S.

AU - Lee, Y.

AU - Paul, G.

AU - Stanley, H. E.

AU - Vandesteeg, N.

PY - 2001

Y1 - 2001

N2 - In this paper we apply scaling laws from percolation theory to the problem of estimating the time for a fluid injected into an oil field to breakthrough into a production well. The main contribution is to show that, when these previously published results are used on realistic data, they are in good agreement with results calculated in a more conventional way but they can be obtained significantly more quickly. As a result they may be used in practical engineering circumstances and aid decision-making for real field problems.

AB - In this paper we apply scaling laws from percolation theory to the problem of estimating the time for a fluid injected into an oil field to breakthrough into a production well. The main contribution is to show that, when these previously published results are used on realistic data, they are in good agreement with results calculated in a more conventional way but they can be obtained significantly more quickly. As a result they may be used in practical engineering circumstances and aid decision-making for real field problems.

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UR - https://www.scopus.com/pages/publications/85008343482#tab=citedBy

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DO - 10.1016/S0378-4371(99)00327-1

M3 - Article

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VL - 7

SP - S105-S117

JO - Petroleum Geoscience

JF - Petroleum Geoscience

ER -

Applications of statistical physics to the oil industry: Predicting oil recovery using percolation theory

Abstract

All Science Journal Classification (ASJC) codes

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