Design Considerations to Test Sealing Capacity of Saline Aquifers
- Mehdi Zeidouni (U. of Calgary) | Mehran Pooladi-Darvish (Fekete Associates Inc.)
- Document ID
- Society of Petroleum Engineers
- Canadian Unconventional Resources and International Petroleum Conference, 19-21 October, Calgary, Alberta, Canada
- Publication Date
- Document Type
- Conference Paper
- 2010. Society of Petroleum Engineers
- 5.6.4 Drillstem/Well Testing, 4.1.2 Separation and Treating, 4.1.5 Processing Equipment
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The geological storage of carbon dioxide (CO2) provides the possibility of maintaining access to fossil energy, while reducing emissions of CO2 to the atmosphere. One of the essential concerns in geologic storage is the risk of CO2 leakage from the storage formations. The leakage occurs through possible pathways in the seal. Characterization of the CO2 leakage pathways from the storage formations into overlying formations is required. The aquifer cap-rock may be characterized before CO2 storage. This will allow for the determination of proper storage aquifers and locations for the injection wells. In a companion paper, a flow and pressure test has been suggested for characterization of leakage pathways in aquifer cap-rock. Water is injected in the target aquifer, and the pressure is observed in an overlying aquifer. The pressure data are analyzed to characterize the leakage pathways in the cap-rock. In this work, design considerations to maximize the capability of leakage characterization are presented.
A leakage pathway can be characterized by the leak transmissibility and location parameters. A successful test should be able to provide sufficient information to evaluate the leakage parameters. In this work, different strategies are evaluated in order to achieve a successful test. The strategies include increasing the sampling frequency, use of pulsing, increasing the number of monitoring/injection wells and utilization of prior information. Prior information on the leak is provided through analysis of the pressure derivative curve.
Estimation of the leakage parameters is actually an inverse problem that is generally ill-conditioned and very sensitive to noise. The information provided by different strategies is evaluated, based on their effects on well-posing the inverse problem. The effects are studied based on information and correlation matrices, as well as the confidence interval.
One of the main challenges facing development and deployment of CO2 capture and storage in deep saline aquifers is the risk of leakage. The injected buoyant CO2 may leak through the leakage pathways in an otherwise sealing cap-rock. In a companion paper (Zeidouni and Pooladi-Darvish, 2010), a pressure and flow test has been introduced to detect and characterize the leak based on pressure data measured in an overlying aquifer. The leak is characterized based on location and transmissibility parameters. In dimensionless form, these parameters are the dimensionless abscissa of the leak (xlD), the dimensionless ordinate of the leak (ylD), and the leakage coefficient a (klrl 2/(2kshshl)). For convenience, the origin of the coordinate system is considered to be at the (first) injection well, while the (first) monitoring well is considered to be at (L,0) coordinates.
Applying the inverse methodology to a base case, it is shown that, due to relatively linearly dependent sensitivity coefficients and a high correlation between the location parameters, it may be difficult to obtain the leak parameters through pressure information at a single monitoring well. The parameter estimation process may be very unstable, causing the leakage parameters inferred from pressure data to vary over a very large confidence interval. It is noted that the solution to the leakage inverse problem is non-unique. At least two and at most four leaks with the same transmissibility but different locations exist that equally fit the data. Obtaining one set of parameters the remaining possible sets can be calculated.
In this work, we investigate different strategies to maximize the information that can be obtained in order to characterize the leak. The strategies include increasing the number of data samples, use of injection pulses, considering multiple monitoring wells, considering multiple injection wells, and regularization using information extracted from derivative analysis. The information added through these procedures are investigated based on information and correlation matrices, as well as confidence intervals.
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