Gas Well Pressure Drop Predictions Under Foam Flow Conditions

One of the most important challenges the operators of tight gas reservoirs face is maintaining sustained production from these wells.  One of the characteristics of tight gas wells is the significant drop in production rate over a short period of time.  Since most of these wells produce some water, without some type of artificial lift method, it is difficult to sustain production from these wells.  One of the most common techniques used for lifting the water is foam lift; this involves injecting surfactant in the well so that in-situ foam between gas and water is created, and the foam is produced to the surface which includes water and gas.  For deep gas wells with small amounts of water production, foam lift is the most economical method.  Unfortunately, no correlation exists to calculate the pressure drop under foam flow. Therefore, operators are unable to correctly predict the performance of the well under foam flow conditions.  In addition, since we cannot predict the time of abandonment, we cannot determine the reserves for the wells which are on foam lift. This project addressed the issue of pressure drop calculation under foam flow condition.  By using available data from vendors and field measurements, as well as collecting data from new experimental facility, we developed suitable correlations to calculate the pressure drop in vertical gas wells. The project was sponsored by Research Partnership to Secure Energy for America (RPSEA), Chevron Energy Technology Compay, ConocoPhillips, Marathon Oil Company, Multi-Chem Group, Nalco Energy Services, Shell Exploration and Production Company, and The University of Tulsa.

Final Report (December, 2015) (.pdf - 14.9MB)

Haynesville Shale Simulation Project

Sponsored by QEP Energy Company and The University of Tulsa, the overall objective of this project was to determine the performance of Haynesville gas wells as a function of spacing. Many papers have been published on Haynesville shale well simulations. These papers concentrate on single well flow simulation. The history matching involves adjusting many unknown parameters (fracture permeability and damage, formation permeability, fracture length, etc.) so that performance can be matched. These history matches, although helpful in understanding important input parameters that can affect the production data, did not provide any information on how the wells interfere with each other and how the spacing of these wells impacts the performance. Our goal was to extend the current understanding of the flow simulation of these wells and provide a pathway by which the interference between adjacent wells is understood so that the impact of well spacing on the performance of the reservoir is better understood. Although the project’s main emphasis was on simulation, we incorporated all of the information about the reservoir in improving our understanding of the reservoir performance. This included decline curve analysis, incorporation of core and other petrophysical data, fracturing data and any build up tests conducted on the wells.

Privately Sponsored (March 2013)

Haynesville Shale Simulation Project

Sponsored by Samson Contour Energy Exploration & Production, LLC and The University of Tulsa. The overall objective of this project was to understand the behavior of Haynesville shale gas wells by simulating the performance of the wells.   Many papers have been published on Haynesville shale well simulations.  These papers concentrated on single well flow simulation.  The history matching involved adjusting many unknown parameters (fracture permeability and damage, formation permeability, fracture length, etc.) so that performance could be matched.  However, these history matches, although helpful in understanding important input parameters that can affect the production data, did not provide any information on how the wells interfered with each other and how the optimal spacing of these wells could be defined.  Our goal was to extend the current understanding of the flow simulation of these wells and provide a pathway by which the interference between adjacent wells is understood so that the impact of well spacing on the performance of the reservoir is better understood.

Privately Sponsored (January 2013)

Woodford Simulation Project

The overall objective of this project, which was fully funded by Range Resources, Inc., was to understand the behavior of Woodford shale oil wells by simulating the performance of the wells. Many papers have been published on shale well simulations. These papers concentrated on single well flow simulation. The history matching involved adjusting many unknown parameters (fracture permeability and damage, formation permeability, fracture length, etc.) so that performance could be matched. However, these history matches, although helpful in understanding important input parameters that can affect production data, did not provide any information on how the wells interfered with each other and how the optimal spacing of these wells could be defined. Our goal was to extend the current understanding of the flow simulation of these wells and provide a pathway by which the interference between adjacent wells is understood so that the impact of well spacing on the performance of the reservoir is better understood. The ultimate goal was to quantify the production profiles from multiple wells drilled in a single section. Sponsored by Range Production Company and The University of Tulsa.

Privately Sponsored (November 2012)

Optimization of Infill Well Locations in Wamsutter Field

One of the most important challenges the operators of tight gas reservoirs face is optimizing infill well locations. Unlike conventional reservoirs, optimization of infill well locations in tight gas reservoirs is significantly difficult. This project addresses specific issues in the Wamsutter gas field, one of the largest gas fields in the Rocky Mountain region. The proposed solutions can be used in other similar tight gas reservoirs. The project was funded through a cooperative agreement issued by the Research Partnership to Secure Energy for America (RPSEA) and was directed by Dr. Mohan Kelkar of The University of Tulsa (Offeror), and Kent Perry, RPSEA Program Manager. Industry partners include Devon Energy Corporation and Texas A & M University, with Devon Energy Corporation paying for more than 80% of the total cost of the project.

Final Report (August, 2011) (.pdf - 6.95MB)

Exploitation and Optimization of Reservoir Performance in Hunton Formation, Oklahoma

The goal of this project goal was to understand the mechanism under which oil is produced from the Hunton Formation and to propose techniques to optimize the performance of these reservoirs using various technologies. The project was funded through a Cooperative Agreement issued by the Department of Energy under their Gas/Oil - Oil Field Demonstrations Class Revisit Program. The project was directed by Mohan Kelkar of The University of Tulsa. Paul West and Purna Halder were our U. S. Department of Energy Program Managers. Industry partners included Marjo Operating Company, Inc., The University of Houston, and James R. Derby and Associates. Consultants to the project included independent geologists Joe Podpechan and Ron Snyder.

Final Report (August, 2007) (.pdf - 3.28MB)

Application of Integrated Reservoir Management and Reservoir Characterization

This project involved the application of reservoir characterizationtools and techniques, advanced reservoir management techniques and advanced recovery technologies aimed at resolving specific producibility problems, which result in a significant increase in oil production from a mature water flood located in a shallow shelf carbonate environment. The project was jointly funded by Fina Oil and Chemical Company, the U.S. Department of Energy, Texas A&M University, The University of Tulsa and David K. Davies & Associates. 

Final Report (March, 2000) (.pdf -1.59MB)

Integrated Approach Towards the Application of Horizontal Wells to Improve Waterflooding

This project involved the application of horizontal well technology to improve the performance of a mature oil field located in a fluvially dominated deltaic sandstone reservoir. The project was jointly funded by the U.S. Department of Energy, Amoco Production Company, Uplands Resources, Inc. and The University of Tulsa.

Final Report (August 1999) (.pdf - 3.62MB)

Application of Artificial Intelligence to Reservoir Characterization:  An Interdisciplinary Approach

This project involved the development of a user-friendly computer program to integrate geological and engineering information using artificial intelligence (AI) methodology. The project was restricted to fluvially dominated deltaic environments. The project was jointly funded by the U.S. Department of Energy, and The University of Tulsa.

Final Report (August, 1997) (.pdf - 776KB)