Comparison of permeability models using mercury injection capillary pressure data on carbonate rock samples

Hasan A. Nooruddin; M. Enamul Hossain; Hasan Al-Yousef; Taha Okasha

doi:10.1016/j.petrol.2014.06.032

Comparison of permeability models using mercury injection capillary pressure data on carbonate rock samples

Hasan A. Nooruddin, M. Enamul Hossain^*, Hasan Al-Yousef, Taha Okasha

^*Corresponding author for this work

King Fahd University of Petroleum & Minerals

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

96 Scopus citations

Abstract

With the latest advances in carbonate reservoir characterization, new workflows have been proposed for consistent and accurate reservoir modeling where mercury injection capillary pressure (MICP) data is used primarily to determine petophysical properties. A dataset - obtained from carbonate formations from the Middle East region - containing 206 rock samples are used to evaluate the performance of nine permeability models. Numerical pressure derivative plots are proposed as a new approach to visually validate the accuracy of the mercury capillary pressure curves. As the order of the derivative increases, the data spreading increases as well proving an indication of the accuracy of the lab measurements. The compared permeability models are Purcell, Thomeer, Winland, Swanson, Pittman, Huet, Dastidar and Buiting-Clerke (two forms) permeability models. An accuracy index (ACI) is introduced to rank the permeability models along with a detailed statistical and graphical analysis. The ACI is computed by taking the arithmetic average of four different error measures after normalizing them. The error measures are the mean relative percent error (MRPE), the mean absolute relative percent error (MAPE), the coefficient of determination (R²), and the root mean squares (RMS). In general, the comparative study shows that the permeability models can be grouped into three categories with respect to their performance using our dataset. The first group contains Swanson and Winland permeability models as the top-ranking permeability models with an average ACI of 0.91. The second category contains Buiting-Clerke, Thomeer, Dastidar and Pittman permeability models with an average ACI of 0.37. The last category has a single permeability model - Huet permeability model - with an ACI value of 0.02. This study provides a very thorough assessment of the performance and predictive capabilities of the compared permeability models in carbonate reservoirs using MICP data.

Original language	English
Pages (from-to)	9-22
Number of pages	14
Journal	Journal of Petroleum Science and Engineering
Volume	121
DOIs	https://doi.org/10.1016/j.petrol.2014.06.032
State	Published - Sep 2014

Bibliographical note

Funding Information:
The authors would like to thank King Fahd University of Petroleum and Minerals (KFUPM) for funding this work under internal grant number RG1215 – 1 and RG1215 – 2 and for the support received from KFUPM׳s Deanship of Scientific Research. The authors would like to thank management of Saudi Aramco for support and permission to publish this paper. We also thank the petroleum engineering department at KFUPM for the continuous support and the provided knowledge. Sincere thanks go to Dr. Jan Buiting and Dr. Edward Clerke for their support.

Keywords

Carbonate rocks
Mercury injection capillary pressure
Permeability-capillary pressure model

ASJC Scopus subject areas

Fuel Technology
Geotechnical Engineering and Engineering Geology

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10.1016/j.petrol.2014.06.032

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title = "Comparison of permeability models using mercury injection capillary pressure data on carbonate rock samples",

abstract = "With the latest advances in carbonate reservoir characterization, new workflows have been proposed for consistent and accurate reservoir modeling where mercury injection capillary pressure (MICP) data is used primarily to determine petophysical properties. A dataset - obtained from carbonate formations from the Middle East region - containing 206 rock samples are used to evaluate the performance of nine permeability models. Numerical pressure derivative plots are proposed as a new approach to visually validate the accuracy of the mercury capillary pressure curves. As the order of the derivative increases, the data spreading increases as well proving an indication of the accuracy of the lab measurements. The compared permeability models are Purcell, Thomeer, Winland, Swanson, Pittman, Huet, Dastidar and Buiting-Clerke (two forms) permeability models. An accuracy index (ACI) is introduced to rank the permeability models along with a detailed statistical and graphical analysis. The ACI is computed by taking the arithmetic average of four different error measures after normalizing them. The error measures are the mean relative percent error (MRPE), the mean absolute relative percent error (MAPE), the coefficient of determination (R2), and the root mean squares (RMS). In general, the comparative study shows that the permeability models can be grouped into three categories with respect to their performance using our dataset. The first group contains Swanson and Winland permeability models as the top-ranking permeability models with an average ACI of 0.91. The second category contains Buiting-Clerke, Thomeer, Dastidar and Pittman permeability models with an average ACI of 0.37. The last category has a single permeability model - Huet permeability model - with an ACI value of 0.02. This study provides a very thorough assessment of the performance and predictive capabilities of the compared permeability models in carbonate reservoirs using MICP data.",

keywords = "Carbonate rocks, Mercury injection capillary pressure, Permeability-capillary pressure model",

author = "Nooruddin, \{Hasan A.\} and Hossain, \{M. Enamul\} and Hasan Al-Yousef and Taha Okasha",

note = "Funding Information: The authors would like to thank King Fahd University of Petroleum and Minerals (KFUPM) for funding this work under internal grant number RG1215 – 1 and RG1215 – 2 and for the support received from KFUPM׳s Deanship of Scientific Research. The authors would like to thank management of Saudi Aramco for support and permission to publish this paper. We also thank the petroleum engineering department at KFUPM for the continuous support and the provided knowledge. Sincere thanks go to Dr. Jan Buiting and Dr. Edward Clerke for their support. ",

year = "2014",

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doi = "10.1016/j.petrol.2014.06.032",

language = "English",

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AU - Nooruddin, Hasan A.

AU - Hossain, M. Enamul

AU - Al-Yousef, Hasan

AU - Okasha, Taha

N1 - Funding Information: The authors would like to thank King Fahd University of Petroleum and Minerals (KFUPM) for funding this work under internal grant number RG1215 – 1 and RG1215 – 2 and for the support received from KFUPM׳s Deanship of Scientific Research. The authors would like to thank management of Saudi Aramco for support and permission to publish this paper. We also thank the petroleum engineering department at KFUPM for the continuous support and the provided knowledge. Sincere thanks go to Dr. Jan Buiting and Dr. Edward Clerke for their support.

PY - 2014/9

Y1 - 2014/9

N2 - With the latest advances in carbonate reservoir characterization, new workflows have been proposed for consistent and accurate reservoir modeling where mercury injection capillary pressure (MICP) data is used primarily to determine petophysical properties. A dataset - obtained from carbonate formations from the Middle East region - containing 206 rock samples are used to evaluate the performance of nine permeability models. Numerical pressure derivative plots are proposed as a new approach to visually validate the accuracy of the mercury capillary pressure curves. As the order of the derivative increases, the data spreading increases as well proving an indication of the accuracy of the lab measurements. The compared permeability models are Purcell, Thomeer, Winland, Swanson, Pittman, Huet, Dastidar and Buiting-Clerke (two forms) permeability models. An accuracy index (ACI) is introduced to rank the permeability models along with a detailed statistical and graphical analysis. The ACI is computed by taking the arithmetic average of four different error measures after normalizing them. The error measures are the mean relative percent error (MRPE), the mean absolute relative percent error (MAPE), the coefficient of determination (R2), and the root mean squares (RMS). In general, the comparative study shows that the permeability models can be grouped into three categories with respect to their performance using our dataset. The first group contains Swanson and Winland permeability models as the top-ranking permeability models with an average ACI of 0.91. The second category contains Buiting-Clerke, Thomeer, Dastidar and Pittman permeability models with an average ACI of 0.37. The last category has a single permeability model - Huet permeability model - with an ACI value of 0.02. This study provides a very thorough assessment of the performance and predictive capabilities of the compared permeability models in carbonate reservoirs using MICP data.

AB - With the latest advances in carbonate reservoir characterization, new workflows have been proposed for consistent and accurate reservoir modeling where mercury injection capillary pressure (MICP) data is used primarily to determine petophysical properties. A dataset - obtained from carbonate formations from the Middle East region - containing 206 rock samples are used to evaluate the performance of nine permeability models. Numerical pressure derivative plots are proposed as a new approach to visually validate the accuracy of the mercury capillary pressure curves. As the order of the derivative increases, the data spreading increases as well proving an indication of the accuracy of the lab measurements. The compared permeability models are Purcell, Thomeer, Winland, Swanson, Pittman, Huet, Dastidar and Buiting-Clerke (two forms) permeability models. An accuracy index (ACI) is introduced to rank the permeability models along with a detailed statistical and graphical analysis. The ACI is computed by taking the arithmetic average of four different error measures after normalizing them. The error measures are the mean relative percent error (MRPE), the mean absolute relative percent error (MAPE), the coefficient of determination (R2), and the root mean squares (RMS). In general, the comparative study shows that the permeability models can be grouped into three categories with respect to their performance using our dataset. The first group contains Swanson and Winland permeability models as the top-ranking permeability models with an average ACI of 0.91. The second category contains Buiting-Clerke, Thomeer, Dastidar and Pittman permeability models with an average ACI of 0.37. The last category has a single permeability model - Huet permeability model - with an ACI value of 0.02. This study provides a very thorough assessment of the performance and predictive capabilities of the compared permeability models in carbonate reservoirs using MICP data.

KW - Carbonate rocks

KW - Mercury injection capillary pressure

KW - Permeability-capillary pressure model

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DO - 10.1016/j.petrol.2014.06.032

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JF - Journal of Petroleum Science and Engineering

ER -

Comparison of permeability models using mercury injection capillary pressure data on carbonate rock samples

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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