A Review of Well Integrity Based on Field Experience at Carbon Utilization and Storage Sites

Iyer, Jaisree; Lackey, Greg; Edvardsen, Laura; Bean, Andrew; Carroll, Susan; Huerta, Nicolas; Smith, Megan M.; Torsæter, Malin; Dilmore, Robert; Cerasi, Pierre

doi:10.1016/j.ijggc.2021.103533

Cited by 21 publications

(10 citation statements)

References 75 publications

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Section: Wells and Borehole Integritymentioning

confidence: 99%

“…Salt precipitation and scale formation have been found to have an insignificant impact on CO 2 storage [329]. Formation of ice-like crystalline compounds caused by trapping CO 2 in cages created by H 2 -bonded molecules posed signifi-cant hazards like rapid pressurization and loss of injectivity [330,329]. The role of contaminants (depends on the concentration) in the stream of CO 2 can change the rate of dissolution and precipitation rates which can react with cement and further degrade it [328].…”

Section: Wells and Borehole Integritymentioning

confidence: 99%

See 1 more Smart Citation

Comprehensive review of geomechanics of underground hydrogen storage in depleted reservoirs and salt caverns

Ramesh Kumar,

Honorio,

Chandra

et al. 2023

Preprint

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Hydrogen is a promising energy carrier for a low-carbon future energy system, as it can be stored on a megaton scale (equivalent to TWh of energy) in subsurface reservoirs. However, safe and eﬀicient underground hydrogen storage requires a thorough understanding of the geomechanics of the host rock under fluid pressure fluctuations. In this context, we summarize the current state of knowledge regarding geomechanics relevant to carbon dioxide and natural gas storage in salt caverns and depleted reservoirs. We further elaborate on how this knowledge can be applied to underground hydrogen storage. The primary focus lies on the mechanical response of rocks under cyclic hydrogen injection and production, fault reactivation, the impact of hydrogen on rock properties, and other associated risks and challenges. In addition, we discuss wellbore integrity from the perspective of underground hydrogen storage. The paper provides insights into the history of energy storage, laboratory scale experiments, and analytical and simulation studies at the field scale. We also emphasize the current knowledge gaps and the necessity to enhance our understanding of the geomechanical aspects of hydrogen storage. This involves developing predictive models coupled with laboratory scale and field-scale testing, along with benchmarking methodologies.

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Section: Wells and Borehole Integritymentioning

confidence: 99%

Section: Wells and Borehole Integritymentioning

confidence: 99%

Comprehensive review of geomechanics of underground hydrogen storage in depleted reservoirs and salt caverns

Ramesh Kumar,

Honorio,

Chandra

et al. 2023

Preprint

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“…The model simulated the change of a rock-cement casing combination in the abandoned well of the carbon storage bank [15][16][17]. The possible geomechanical risks in the CCS process were outlined [18][19][20]. Gao et al [21] provided theoretical guidance and analysis methods for evaluating the integrity of wellbore cement and optimizing injection parameters under CO 2 and injection conditions and described the research status of the integrity of a cement sheath with defects.…”

Section: Introductionmentioning

confidence: 99%

The Influence of CO2 Physical Properties on Casing and Its Prediction Method

Cai,

Li,

et al. 2024

Processes

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In order to reveal the physical properties of CO2 under actual formation conditions, this paper establishes a mathematical model of the temperature field and pressure field in the wellbore under CO2 injection conditions, optimizes the state equation of CO2 physical-property parameters, calculates the change trend of CO2 density, viscosity, and compression factor along the wellbore, and obtains the influence law of CO2 corrosion on the casing and interface. The viscosity showed a downward trend along the well depth; the compression factor showed an upward trend. The surfaces of the three casings were smooth and flat without obvious defects, the cement structure was dense, and there was no obvious pore structure. After corrosion, with the increase of Cr content, the change of interfacial corrosion decreases. The morphology of the Q125 and 3Cr interface is loose after corrosion, while there is no obvious change in the 13Cr interface. With the prolongation of corrosion time, low wellbore internal pressure easily causes casing yield, and high wellbore internal pressure easily causes cement-sheath compression failure. The circumferential stress of the casing increases with the corrosion time extension, and the radial stress of the casing and cement sheath decreases first and then increases with the corrosion time. The compressive strength of the cement sheath does not exceed the compressive strength.

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“…Sandl et al (2021) utilized a basic predictive method to investigate the linkages between various well features and reported instances of GM in BC. There were other database analysis studies to identify wellbore leakage based on a wide range of factors (Fleming et al, 2021; Cahill and Samano, 2022; Iyer et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Machine learning approaches for the prediction of serious fluid leakage from hydrocarbon wells

Rezvandehy

Mayer

2023

DCE

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The exploitation of hydrocarbon reservoirs may potentially lead to contamination of soils, shallow water resources, and greenhouse gas emissions. Fluids such as methane or CO2 may in some cases migrate toward the groundwater zone and atmosphere through and along imperfectly sealed hydrocarbon wells. Field tests in hydrocarbon-producing regions are routinely conducted for detecting serious leakage to prevent environmental pollution. The challenge is that testing is costly, time-consuming, and sometimes labor-intensive. In this study, machine learning approaches were applied to predict serious leakage with uncertainty quantification for wells that have not been field tested in Alberta, Canada. An improved imputation technique was developed by Cholesky factorization of the covariance matrix between features, where missing data are imputed via conditioning of available values. The uncertainty in imputed values was quantified and incorporated into the final prediction to improve decision-making. Next, a wide range of predictive algorithms and various performance metrics were considered to achieve the most reliable classifier. However, a highly skewed distribution of field tests toward the negative class (nonserious leakage) forces predictive models to unrealistically underestimate the minority class (serious leakage). To address this issue, a combination of oversampling, undersampling, and ensemble learning was applied. By investigating all the models on never-before-seen data, an optimum classifier with minimal false negative prediction was determined. The developed methodology can be applied to identify the wells with the highest likelihood for serious fluid leakage within producing fields. This information is of key importance for optimizing field test operations to achieve economic and environmental benefits.

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A Review of Well Integrity Based on Field Experience at Carbon Utilization and Storage Sites

Cited by 21 publications

References 75 publications

Comprehensive review of geomechanics of underground hydrogen storage in depleted reservoirs and salt caverns

Comprehensive review of geomechanics of underground hydrogen storage in depleted reservoirs and salt caverns

The Influence of CO2 Physical Properties on Casing and Its Prediction Method

Machine learning approaches for the prediction of serious fluid leakage from hydrocarbon wells

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