Dispersion and Dispersivity from Core Scale to Reservoir Scale

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Harvard

Pechorskaya, E 2019, 'Dispersion and Dispersivity from Core Scale to Reservoir Scale', Dipl.-Ing., Montanuniversitaet Leoben (000).

APA

Pechorskaya, E. (2019). Dispersion and Dispersivity from Core Scale to Reservoir Scale. [Master's Thesis, Montanuniversitaet Leoben (000)].

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@mastersthesis{716963e922e8489993875c1cbcba594e,
title = "Dispersion and Dispersivity from Core Scale to Reservoir Scale",
abstract = "Upstream companies nowadays are widely using chemical floods to achieve incremental oil production. However, before the company makes the decision of implementing the flood on the field, a number of simulation forecasts are done to estimate the possible oil recovery. The reliability of the forecasts is studied in this work with the focus on the influence of dispersion on the forecast results. Influence of dispersion on the fluid flow in porous media is a well-known fact, it should therefore also be introduced in the flow simulation. This is possible by mimicking the actual, physical dispersion by numerical dispersion. Numerical dispersion, or “truncation error”, is an artifact of the current simulation techniques that may lead to severe distortions along with an occurrence of rapid saturation changes. The role of gridding and the size of calculation time-steps for different types of models (1D/2D domain with single/two-phase flow) is studied. These models were created with Petrel and simulation runs done in Eclipse – both Schlumberger Ltd. software. Dispersion was calculated by analyzing tracer-concertation and production-rate curves. While time-step size had a significant impact on all the homogeneous models, gridding was the important issue in terms of tracer production for both types of models: homogeneous and heterogeneous. The influence of gridding on dispersion led to underestimation of incremental oil-recovery after the alkali-polymer flood, even though the influence of gridding on the water-cut was insignificant. An alternative technique of influencing numerical dispersion is introduction of relative-permeability pseudo-function to match the water-cut (the volumetric ratio of water production to total liquid). However, the increase of the gridding by a factor of 20 still resulted in a very good water-cut match, and that left very little room for improvement. The only one relative-permeability pseudo-function that maintained the quality of the match, did not bring any improvements on the tracer curve match. Another technique available in Eclipse to control numerical dispersion is the “diffusion control” option. The usage of that option led to maintaining the water-cut match quality while improving the tracer production-curve match. The improvement of the tracer production curves match might lead to the improvement of forecasts of incremental oil-recovery after the alkali-polymer flood.",
keywords = "Dispersion, Dispersivity, Numerical dispersion, Production forecast, Simulation, Gridding, Time-step, Alkali-Polymer, Tracer-test, Dispersion, Dispersivit{\"a}t, Simulation, Polymer- und Tensidfluten, Numerische Dispersion, Tracer-Test",
author = "Eleonora Pechorskaya",
note = "no embargo",
year = "2019",
language = "English",
school = "Montanuniversitaet Leoben (000)",

}

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TY - THES

T1 - Dispersion and Dispersivity from Core Scale to Reservoir Scale

AU - Pechorskaya, Eleonora

N1 - no embargo

PY - 2019

Y1 - 2019

N2 - Upstream companies nowadays are widely using chemical floods to achieve incremental oil production. However, before the company makes the decision of implementing the flood on the field, a number of simulation forecasts are done to estimate the possible oil recovery. The reliability of the forecasts is studied in this work with the focus on the influence of dispersion on the forecast results. Influence of dispersion on the fluid flow in porous media is a well-known fact, it should therefore also be introduced in the flow simulation. This is possible by mimicking the actual, physical dispersion by numerical dispersion. Numerical dispersion, or “truncation error”, is an artifact of the current simulation techniques that may lead to severe distortions along with an occurrence of rapid saturation changes. The role of gridding and the size of calculation time-steps for different types of models (1D/2D domain with single/two-phase flow) is studied. These models were created with Petrel and simulation runs done in Eclipse – both Schlumberger Ltd. software. Dispersion was calculated by analyzing tracer-concertation and production-rate curves. While time-step size had a significant impact on all the homogeneous models, gridding was the important issue in terms of tracer production for both types of models: homogeneous and heterogeneous. The influence of gridding on dispersion led to underestimation of incremental oil-recovery after the alkali-polymer flood, even though the influence of gridding on the water-cut was insignificant. An alternative technique of influencing numerical dispersion is introduction of relative-permeability pseudo-function to match the water-cut (the volumetric ratio of water production to total liquid). However, the increase of the gridding by a factor of 20 still resulted in a very good water-cut match, and that left very little room for improvement. The only one relative-permeability pseudo-function that maintained the quality of the match, did not bring any improvements on the tracer curve match. Another technique available in Eclipse to control numerical dispersion is the “diffusion control” option. The usage of that option led to maintaining the water-cut match quality while improving the tracer production-curve match. The improvement of the tracer production curves match might lead to the improvement of forecasts of incremental oil-recovery after the alkali-polymer flood.

AB - Upstream companies nowadays are widely using chemical floods to achieve incremental oil production. However, before the company makes the decision of implementing the flood on the field, a number of simulation forecasts are done to estimate the possible oil recovery. The reliability of the forecasts is studied in this work with the focus on the influence of dispersion on the forecast results. Influence of dispersion on the fluid flow in porous media is a well-known fact, it should therefore also be introduced in the flow simulation. This is possible by mimicking the actual, physical dispersion by numerical dispersion. Numerical dispersion, or “truncation error”, is an artifact of the current simulation techniques that may lead to severe distortions along with an occurrence of rapid saturation changes. The role of gridding and the size of calculation time-steps for different types of models (1D/2D domain with single/two-phase flow) is studied. These models were created with Petrel and simulation runs done in Eclipse – both Schlumberger Ltd. software. Dispersion was calculated by analyzing tracer-concertation and production-rate curves. While time-step size had a significant impact on all the homogeneous models, gridding was the important issue in terms of tracer production for both types of models: homogeneous and heterogeneous. The influence of gridding on dispersion led to underestimation of incremental oil-recovery after the alkali-polymer flood, even though the influence of gridding on the water-cut was insignificant. An alternative technique of influencing numerical dispersion is introduction of relative-permeability pseudo-function to match the water-cut (the volumetric ratio of water production to total liquid). However, the increase of the gridding by a factor of 20 still resulted in a very good water-cut match, and that left very little room for improvement. The only one relative-permeability pseudo-function that maintained the quality of the match, did not bring any improvements on the tracer curve match. Another technique available in Eclipse to control numerical dispersion is the “diffusion control” option. The usage of that option led to maintaining the water-cut match quality while improving the tracer production-curve match. The improvement of the tracer production curves match might lead to the improvement of forecasts of incremental oil-recovery after the alkali-polymer flood.

KW - Dispersion

KW - Dispersivity

KW - Numerical dispersion

KW - Production forecast

KW - Simulation

KW - Gridding

KW - Time-step

KW - Alkali-Polymer

KW - Tracer-test

KW - Dispersion

KW - Dispersivität

KW - Simulation

KW - Polymer- und Tensidfluten

KW - Numerische Dispersion

KW - Tracer-Test

M3 - Master's Thesis

ER -