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Experimental and Computational Complex for Determination of the Effectiveness of Cyclic Carbon Dioxide Injection for Tight Oil Reservoirs
Popov E., Myasnkov A., Cheremisin A., Miftakov R., Stukachev V., Mukhametdinova A.
AbstractThe problems of numerical and experimental modeling of cyclic carbon dioxide injection in a supercritical state for low-permeability reservoirs were considered in this study. Sensitivity analysis of the cumulative oil production from a number of physical - chemical parameters of the reservoir was performed. The experimental and numerical simulation of cyclic injection of carbon dioxide (huff-n-puff) on core samples of low permeability reservoirs was carried out. Calculations of phase equilibrium pumping supercritical fluid were conducted. Two-dimensional model was proposed for huff-n-puff technology of cyclic injection of CO2, which is a periodic pumping in and pumping out of the solvent into the formation.
Scale Deposition Prediction for Pump Design in Oil Wells
Elichev V.A., Voloshin A.I., Latypov O.A., Topolnikov A.S., Gotvig K.L., Khabibullin R.A.
Abstract
The paper presents the description of an integrated approach, which is implemented in a program module and allows predicting scale deposition in well based on distributions of specific multiphase flow parameters (temperature, pressure, and gas content). Parameters are obtained from calculated pump operation regimes. The method's apparent advantages are presented, namely: -automatic input of reservoir water/gas chemical content data,-numerical estimation of scale deposition risk in different well sections by means of the saturation index,-built-in tips on selecting the optimal scale prevention technology specifying the inhibitor type and amount,-prediction of pump life cycle buildup,-estimation of the expected economic benefit caused by scale prevention.
The prediction method of scale deposition and the algorithm of selection of the scale prevention technology can be successfully used during analysis of scale deposition risk and planning the activities for scale prevention for a group of oil wells or oilfield. The proposed algorithmic module has been tested in a number of active oil fields of Western Siberia, and has already garnered positive references from production professionals. This module is planned to serve as a basis for similar modules for forecasting risks of mechanical dashes, corrosion and paraffin buildup.
