Semi-analytical prediction of critical oil rate in naturally fractured reservoirs with water coning

Prasun, Samir; Wojtanowicz, Andrew K.

doi:10.1016/j.petrol.2019.05.082

Cited by 6 publications

(2 citation statements)

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“…Semianalytical models are based on simplified force interaction, but also consider the ignored physical effects by fitting the discrepancy statistically with empirical data. The processes of estimating some values of analytical model's parameters by experimental data are called statistical model calibrations [12][13][14][15][16][17] .This kind of model increases the accuracy of the prediction and reduces bias. Prasun and Wojtanowicz [17] generated a semi-analytical model to study water coning problem for a more specific scenario of naturally fractured reservoirs (NFR).…”

Section: Introductionmentioning

confidence: 99%

“…The processes of estimating some values of analytical model's parameters by experimental data are called statistical model calibrations [12][13][14][15][16][17] .This kind of model increases the accuracy of the prediction and reduces bias. Prasun and Wojtanowicz [17] generated a semi-analytical model to study water coning problem for a more specific scenario of naturally fractured reservoirs (NFR). They simplified an NFR mechanistic model and applied Chaperon's correlations in their model by replacing the permeability of matrix with an equivalent permeability of NFR.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Reservoir Analysis for A Low Recovery Factor Mature Reservoir with A Gas Cap and Large Aquifer: A Proposed Coning Correlation

Yi,

Liu

2023

J. Phys.: Conf. Ser.

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With the development of reservoir engineering and management, enhanced oil recovery (EOR) techniques are becoming increasingly sophisticated. Generally, the recovery factor (RF) for a conventional reservoir can range from around 10% to 60% after four decades of production, with an average recovery factor of around 35%. While the RF of the NGJ field with high porosity (0.25) and permeability (300 to 600 md) is 6.11% after producing for over 40 years, which is rare in such good reservoir conditions. In this work, some classic techniques and several advanced methods were utilized to investigate the reason behind the low RF for this reservoir. A dynamic reservoir simulation was constructed on the basis of a statics petrophysical model. Based on the preliminary simulation study, it was found that gas coning is a common problem in the reservoir. Therefore, a concept of coning correlation function (CCF) is proposed, and the procedures for developing the CCF are explained. The critical oil rate was estimated using the Addington correlation and modified through the proposed coning correlation that varies as a function of time. The estimated critical rate through CCF is used to control flowing bottom hole pressure (FBHP) in the prediction scenarios.

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