A New General Flow Model for Well Test Analysis for Fluids Used in Enhanced Oil Recovery Projects - (SPE-164886)

Author(s):  
A.R. Valdes-Perez ◽  
H. Cinco-Ley ◽  
H. Pulido-Bello ◽  
F. Hveding ◽  
F. Samaniego
2013 ◽  
Author(s):  
Alex R. Valdes-Perez ◽  
Heber Cinco-Ley ◽  
Hector Pulido-Bello ◽  
Frode Hveding ◽  
Fernando Samaniego

1982 ◽  
Vol 104 (2) ◽  
pp. 142-148 ◽  
Author(s):  
Chi U. Ikoku

Recent studies on the transient flow of non-Newtonian fluid in porous media have proposed new well test analysis techniques for non-Newtonian injection wells. This paper extends these new techniques to non-Newtonian injection well falloff testing. The practical use of this well test analysis method is demonstrated. The limitations of the techniques are also addressed. Exmaples of field data are used to demonstrate how this analysis can aid in well test interpretation and provide data and insight for the design and operation of enhanced oil recovery projects.


Energies ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 34
Author(s):  
Zhixue Sun ◽  
Xugang Yang ◽  
Yanxin Jin ◽  
Shubin Shi ◽  
Minglu Wu

The mathematical model of composite reservoir has been widely used in well test analysis. In the process of oil recovery, due to the injection or replacement of the displacement agent, the model boundary can be moved. At present, the mathematical model of a composite reservoir with a moving boundary is less frequently studied and cannot meet industrial demand. In this paper, a mathematical model of a composite reservoir with a moving boundary is developed, with consideration of wellbore storage and skin effects. The characteristics of pressure transient in moving boundary composite reservoir are studied, and the influences of parameters, such as initial boundary radius, moving boundary velocity, skin factor, wellbore storage coefficient, diffusion coefficient ratio, and mobility ratio on pressure and production, are analyzed. The moving boundary effects are noticeable mainly in the middle and late production stages. The proposed model provides a novel theoretical basis for well test analysis in these types of reservoirs.


2021 ◽  
Author(s):  
Mohamad Mustaqim Mokhlis ◽  
Nurdini Alya Hazali ◽  
Muhammad Firdaus Hassan ◽  
Mohd Hafiz Hashim ◽  
Afzan Nizam Jamaludin ◽  
...  

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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