Well Test Analysis of Data Dominated by Storage and Skin: Non-Newtonian Power-Law Fluids

1987 ◽  
Vol 2 (04) ◽  
pp. 618-628 ◽  
Author(s):  
S. Vongvuthipornchai ◽  
Rajagopal Raghavan
Keyword(s):  
Power Law ◽  
Well Test ◽  
Well Test Analysis ◽  
Test Analysis ◽  
Power Law Fluids

Pressure Transient Behavior of Non-Newtonian/Newtonian Fluid Composite Reservoirs

1981 ◽  
Vol 21 (02) ◽  
pp. 271-280 ◽  
Author(s):  
O. Lund ◽  
Chi U. Ikoku
Keyword(s):  
Differential Equation ◽  
Partial Differential Equation ◽  
Porous Media ◽  
Newtonian Fluid ◽  
Power Law ◽  
Well Test ◽  
Well Test Analysis ◽  
Partial Differential ◽  
Test Analysis ◽  
Power Law Fluids

Abstract Pressure transient theory of flow of non-Newtonian power-law fluids in porous media is extended to non-Newtonian/Newtonian fluid composite reservoirs. This paper examines application of non-Newtonian and conventional (Newtonian) well test analysis techniques to injectivity and falloff tests in wells where different amounts of non-Newtonian fluids have been injected into the reservoir to displace the in-situ Newtonian fluid (oil and/or water). Early time pressure data can be analyzed by non-Newtonian well test analysis methods. Conventional semilog methods may be used to analyze late time falloff data. The location of the non-Newtonian fluid front can be estimated from well tests using the radius of investigation equation for power-law fluids. An equation for calculating shear rates and apparent viscosities for power-law fluids in reservoirs is presented. An example problem is used to illustrate observations and solution techniques. Introduction Recent studies have proposed new well test analysis techniques for interpreting pressure data obtained during injectivity and falloff testing in reservoirs containing slightly compressible non-Newtonian, power-law fluids. The first papers proposing well test analysis methods for non-Newtonian fluid injection wells were published in 1979. Odeh and Yang1 derived a partial differential equation for flow of power-law fluids through porous media. They used a power-law function relating the viscosity to the shear rate. The power-law viscosity function was coupled with the variable viscosity diffusivity equation and a shear rate relationship proposed by Savins2 to give the new partial differential equation. An approximate analytical solution was obtained. The solution provided new plotting techniques for analyzing injection and falloff test data. The utility of the new methods was demonstrated on field tests. They also derived the steady-state flow equation and an expression for the radius of investigation. Isochronal testing was discussed. McDonald3 presented a numerical study using the power-law flow equation of Odeh and Yang. He presented different numerical techniques of solving the equation and compared results with the analytical results of Odeh and Yang. He found that a finer grid was required for finite difference simulation of power-law fluids than for black-oil fluids. A partial differential equation for radial flow of non-Newtonian power-law fluids through porous media was published by Ikoku and Ramey4,5 in 1979. Coupling the non-Newtonian Darcy's law with the continuity equation, the rigorous partial differential equation was derived:Equation 1

Well Test Analysis for Two-Phase Flow of Non-Newtonian Power-Law and Newtonian Fluids

1984 ◽  
Vol 106 (2) ◽  
pp. 295-305 ◽  
Author(s):  
C. S. Gencer ◽  
C. U. Ikoku
Keyword(s):  
Power Law ◽  
Two Phase Flow ◽  
Newtonian Fluids ◽  
Phase Flow ◽  
Well Test ◽  
Finite Radius ◽  
Well Test Analysis ◽  
Two Phase ◽  
Power Law Fluids ◽  
Rock Compressibility

Analysis of injectivity and falloff test data is considered during two-phase flow of non-Newtonian and Newtonian fluids. The non-Newtonian fluids considered are power-law fluids. Two sets of relative permeability data representing preferentially water wet and oil wet systems are considered. The conditions under which saturation gradients develop are thoroughly investigated. The effects of finite radius skin region and rock compressibility on pressure response are also investigated. During two-phase flow of power-law and Newtonian fluids, saturation gradients do not develop under most practical conditions. Injectivity and falloff data can be analyzed using available techniques with appropriate definitions of dimensionless variables for two-phase flow. When saturation gradients exist, the response of this transition region is not interpretable by available methods.

scholarly journals Determination of well-drainage area for power-law fluids by transient pressure analysis

2012 ◽  
Vol 5 (1) ◽  
pp. 45-56 ◽  
Author(s):  
Freddy-Humberto Escobar ◽  
Laura-Jimena Vega ◽  
Luis-Fernando Bonilla
Keyword(s):  
Power Law ◽  
Oil Recovery ◽  
Heavy Oil ◽  
Drainage Area ◽  
Well Test ◽  
Transient Pressure ◽  
Well Test Analysis ◽  
Pressure Derivative ◽  
Oil Companies ◽  
Power Law Fluids

Since conventional oil is almost depleted, oil companies are focusing their efforts on exploiting heavy oil reserves. A modern and practical technique using the pressure and pressure derivative, log-log plot for estimating the well-drainage area in closed and constant-pressure reservoirs, drained by a vertical well is presented by considering a non-Newtonian flow model for describing the fluid behavior. Several synthetic examples were presented for demonstration and verification purposes.Such fluids as heavy oil, fracturing fluids, some fluids used for Enhanced Oil Recovery (EOR) and drilling muds can behave as either Power-law or Bingham, usually referred to as the non-Newtonian fluids. Currently, there is no way to estimate the well-drainage area from conventional well test analysis when a non-Newtonian fluid is dealt with; therefore, none of the commercial well test interpretation package can estimate this parameter (drainage area).

Connecting Data, Model and Process to Streamline and Enhance Single-Point Production Well Test Validation

2021 ◽  
Author(s):  
Mohamad Mustaqim Mokhlis ◽  
Nurdini Alya Hazali ◽  
Muhammad Firdaus Hassan ◽  
Mohd Hafiz Hashim ◽  
Afzan Nizam Jamaludin ◽  
...  
Keyword(s):  
Test Data ◽  
Single Point ◽  
Database Systems ◽  
Test Validation ◽  
Well Test ◽  
Production Well ◽  
Well Test Analysis ◽  
Test Analysis ◽  
Digital Ecosystem ◽  
Well Model

Abstract In this paper we will present a process streamlined for well-test validation that involves data integration between different database systems, incorporated with well models, and how the process can leverage real-time data to present a full scope of well-test analysis to enhance the capability for assessing well-test performance. The workflow process demonstrates an intuitive and effective way for analyzing and validating a production well test via an interactive digital visualization. This approach has elevated the quality and integrity of the well-test data, as well as improved the process cycle efficiency that complements the field surveillance engineers to keep track of well-test compliance guidelines through efficient well-test tracking in the digital interface. The workflow process involves five primary steps, which all are conducted via a digital platform: Well Test Compliance: Planning and executing the well test Data management and integration Well Test Analysis and Validation: Verification of the well test through historical trending, stability period checks, and well model analysis Model validation: Correcting the well test and calibrating the well model before finalizing the validity of the well test Well Test Re-testing: Submitting the rejected well test for retesting and final step Integrating with corporate database system for production allocation This business process brings improvement to the quality of the well test, which subsequently lifts the petroleum engineers’ confidence level to analyze well performance and deliver accurate well-production forecasting. A well-test validation workflow in a digital ecosystem helps to streamline the flow of data and system integration, as well as the way engineers assess and validate well-test data, which results in minimizing errors and increases overall work efficiency.

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