New techniques for estimating properties of saturated reservoirs, using readily-available rate decline data

Mosobalaje, O. O.; Orodu, O. D.; Tiab, Djebbar

doi:10.1016/j.petrol.2014.06.023

Cited by 4 publications

(1 citation statement)

References 9 publications

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“…The work presented by Mosobalaje et al (2014) requires two techniques for estimating permeability and well drainage radius, for solution-gas driven reservoirs. However, data requirement has placed a limitation on the application of the techniques.…”

Section: (Iii) Net Pay Determination -Oil or Gas Recoverymentioning

confidence: 99%

Neural network applications to reservoirs: Physics-based models and data models

Aı̈fa

2014

Journal of Petroleum Science and Engineering

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Section: (Iii) Net Pay Determination -Oil or Gas Recoverymentioning

confidence: 99%

Neural network applications to reservoirs: Physics-based models and data models

Aı̈fa

2014

Journal of Petroleum Science and Engineering

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A New Methodology of Production Performance Prediction for Strong Edge-Water Reservoir

Zhang

Fan

Zhao

et al. 2020

Journal of Energy Resources Technology

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Material balance is a basic principle in reservoir engineering, which is still used as a quick and easy analytical tool for reservoir evaluation. In this paper, a new methodology of production performance prediction for water-flooding reservoir was proposed based on material balance principle, which considers the water saturation change caused by water injection and natural water influx, and its effect on instantaneous gas-oil ratio. Among them, the cumulative water production was calculated based on Tong's water-driver performance curve; the cumulative water influx was obtained by the Fetkovitch method; the instantaneous gas-oil ratio can be acquired by Darcy's law and Bakers relative-permeability model. Comparisons have been made between the new methodology and commercial reservoir simulator for a specific water-flooding reservoir. The results show that there is good similarity between these two tools, which verifies the correctness of the new methodology.

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Theories of Arps' Decline Curve Exponent and Loss Ratio, for Saturated Reservoirs

Mosobalaje

Tiab

2014

Abu Dhabi International Petroleum Exhibition and Conference

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Rate decline curve analysis is an essential tool in predicting reservoir performance and in estimating reservoir properties. In its most basic form, decline curve analysis is to a large extent based on Arps' empirical models that have little theoretical basis. The use of historical production data to predict future performance is the focus of the empirical approach of decline analysis while the theoretical approach focuses on the derivation of relationships between the empirical model parameters and reservoir rock/fluid properties; thereby establishing a theoretical basis for the empirical models. Such relationships are useful in formulating techniques for reservoir properties estimation using production data.Many previous attempts at establishing relationships between the empirical parameters and the rock/fluid properties have been concerned primarily with the exponential decline of single phase oil reservoirs. A previous attempt to establish the theories of hyperbolic decline of saturated reservoirs (multiphase) have yielded an expression relating the Arps' decline exponent, b, to rock/fluid properties. However, the values of exponent computed from the expression are not constant through time, whereas, the empirically-determined exponent b is a constant value.This work utilizes basic concepts of compressibility and mobility to justify the dynamic behaviour of the values obtained from the existing theoretical expression of the previous theory; to prove that the expression, though rigorously derived, is not the theoretical equivalence of the empirical Arps' b-exponent; and finally, to properly to offer a new logical perspective to the previous theory relating b-exponent to rock and fluid property. Ultimately, this work presents, for the first time, a new consistent theoretical expression for the Arps' exponent, b. The derivation of the new expression is still founded on the concept of Loss Ratio, as in previous attempts; however, this latest attempt utilizes the cumulative derivative of the Loss Ratio, instead of the instantaneous derivative implied in the previous attempt.The new expression derived in this work have been applied to a number of saturated reservoir models and found to yield values of b-exponent that are constant through time and are equivalent to the empirically-determined b-exponent.

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New techniques for estimating properties of saturated reservoirs, using readily-available rate decline data

Cited by 4 publications

References 9 publications

Neural network applications to reservoirs: Physics-based models and data models

Neural network applications to reservoirs: Physics-based models and data models

A New Methodology of Production Performance Prediction for Strong Edge-Water Reservoir

Theories of Arps' Decline Curve Exponent and Loss Ratio, for Saturated Reservoirs

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