Abstract

Abstract A model is presented to predict, qualify and quantify sand production in oil and gas well systems for different reservoir types. Sand production is normally caused when the shear stresses acting on the rock surrounding the perforation cavities or well bore exceed the rock strength, which leads to rock failure. The numerical model that evolves incorporates a sanding factor KDs in the fluidized solid flow and erosional model; characterizing different reservoir types under the influence of various in-situ stresses, reservoir drawdown pressures and rock failure criteria relevant to the reservoir type The rock type and field conditions; derived directly from field observations, correlated with the characteristic modeled sanding factors Kds can be used to benchmark a variety of reservoir sand producer well systems for various production and pressure profile scenarios. Using the simulated data of porosity, pressure and fluidized solid phase saturation represented as characteristic eigenvalue data points, which is derived from a characteristic deviation matrix, the solution variables can result in an efficient model to predict and quantify sand production in oil and gas reservoirs. This model representation allows the simulation of different sand reservoir producing scenarios under different production index and formation pressure profile. The numerical simulation solution strategy employed benefited from use of the Crank Nicholson finite difference as well as the Gaussian Elimination Method to solve the set of matrix of linear equations. Operators field data have being used to tuned and calibrate the model against observed production and well data logs, core and fluid property information from operator's database, which was used for the simulation program. This allows us to provisionally identify candidate sand prone wells that were considered to be most at risk from sand production as well as improve understanding of in-situ stresses, rock strength and failure processes using the sanding factors Kds as important benchmarks. The results and plots of simulation studies demonstrates that using porosity deviation eigenvalues solution data simulated over the metrics of the pressure and production profile data studied in time and depth would always produced definite sand production signatures above a predetermined value of 1, in time for a specific production index and sanding factor Kds, which would allow the evaluation of sand produced in the reservoir. Also sand signatures were indicated by computing the standard deviation of eigenvalue data points, where standard deviation (SD) points above 1 indicates sand signatures in the reservoir flow spectrum. It is also clear from our study that high pressures draw down or low productivity of the well tends to lead to higher sand production. Also fludised solids in flow and sand production decreases and increases respectively with increasing sanding factor Kds, or sandstones property in the reservoir type. It is also indicated by the plots that there exist a sanding threshold critical value, Kds<0.5, above which mark the threshold of rock failure which ultimately lead to increased sand production. From our study it has been demonstrated that sand production varies inversely with the productivity or production index of the well. These important benchmarks would offer important design tradeoff advantages for higher oil and gas production rates, effective sand control strategies and cheaper well completions for specified reservoir types.

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