Hydrogen storage in depleted gas reservoirs: A comprehensive review

Hydrogen future depends on large-scale storage, which can be provided by geological formations (such as caverns, aquifers, and depleted oil and gas reservoirs) to handle demand and supply changes, a typical hysteresis of most renewable energy sources. Amongst them, depleted natural gas reservoirs are the most cost-effective and secure solutions due to their wide geographic distribution, proven surface facilities, and less ambiguous site evaluation. They also require less cushion gas as the native residual gases serve as a buffer for pressure maintenance during storage. However, there is a lack of thorough understanding of this technology. This work aims to provide a comprehensive insight and technical outlook into hydrogen storage in depleted gas reservoirs. It briefly discusses the operating and potential facilities, case studies, and the thermophysical and petrophysical properties of storage and withdrawal capacity, gas immobilization, and efficient gas containment. Furthermore, a comparative approach to hydrogen, methane, and carbon dioxide with respect to well integrity during gas storage has been highlighted. A summary of the key findings, challenges, and prospects has also been reported. Based on the review, hydrodynamics, geochemical, and microbial factors are the subsurface\u27s principal promoters of hydrogen losses. The injection strategy, reservoir features, quality, and operational parameters significantly impact gas storage in depleted reservoirs. Future works (experimental and simulation) were recommended to focus on the hydrodynamics and geomechanics aspects related to migration, mixing, and dispersion for improved recovery. Overall, this review provides a streamlined insight into hydrogen storage in depleted gas reservoirs

Oil and Gas Wells: Enhanced Wellbore Casing Integrity Management through Corrosion Rate Prediction Using an Augmented Intelligent Approach

Wellbore integrity management for oil and gas wells plays a vital role throughout the typical lifespan of a well. Downhole casing leaks in oil- and gas-producing wells significantly affect their shallow water horizon, the environment, and fresh water resources. Additionally, downhole casing leaks may cause seepage of toxic gases to fresh water zones and the surface, through the casing annuli. Forecasting of such leaks and proactive measures of prevention will help eliminate their consequences and, in turn, better protect the environment. The objective of this study is to formulate an effective, robust, and accurate model for predicting the corrosion rate of metal casing string using artificial intelligence (AI) techniques. The input parameters used to train AI models include casing leaks, the percentage of metal loss, casing age, and average remaining barrier ratio (ARBR). The target parameter is the corrosion rate of the metal casing string. The dataset from which the AI models were trained was comprised of 250 data points collected from 218 wells in a giant carbonate reservoir that covered a wide range of practically reasonable values. Two AI tools were used: artificial neural networks (ANNs) and adaptive network-based fuzzy inference systems (ANFISs). A prediction comparison was made between these two tools. Based on the minimum average absolute percentage error (AAPE) and the highest coefficient of determination (R2) between the measured and predicted corrosion rate values, the ANN model proposed here was determined to be best for predicting the corrosion rate. An ANN-based empirical model is also presented in this study. The proposed model is based on the associated weights and biases. After evaluating the new ANN equation using an unseen validation dataset, it was concluded that the ANN equation was able to make predictions with a significantly lower AAPE and higher R2. Use of the proposed new equation is very cost-effective in terms of reducing the number of sequential surveys and experiments conducted. The proposed equation can be utilized without an AI engine. The developed model and empirical correlation are very promising and can serve as a handy tool for corrosion engineers seeking to determine the corrosion rate without training an AI model

Gas Production from Gas Condensate Reservoirs Using Sustainable Environmentally Friendly Chemicals

Unconventional reservoirs have shown tremendous potential for energy supply for long-term applications. However, great challenges are associated with hydrocarbon production from these reservoirs. Recently, injection of thermochemical fluids has been introduced as a new environmentally friendly and cost-effective chemical for improving hydrocarbon production. This research aims to improve gas production from gas condensate reservoirs using environmentally friendly chemicals. Further, the impact of thermochemical treatment on changing the pore size distribution is studied. Several experiments were conducted, including chemical injection, routine core analysis, and nuclear magnetic resonance (NMR) measurements. The impact of thermochemical treatment in sustaining gas production from a tight gas reservoir was quantified. This study demonstrates that thermochemical treatment can create different types of fractures (single or multistaged fractures) based on the injection method. Thermochemical treatment can increase absolute permeability up to 500%, reduce capillary pressure by 57%, remove the accumulated liquids, and improve gas relative permeability by a factor of 1.2. The findings of this study can help to design a better thermochemical treatment for improving gas recovery. This study showed that thermochemical treatment is an effective method for sustaining gas production from tight gas reservoirs

Corrosion Inhibition Properties of Waterborne Polyurethane/Cerium Nitrate Coatings on Mild Steel

Waterborne polyurethane (WBPU)/cerium nitrate (Ce(NO3)3) dispersions were synthesized with different defined Ce(NO3)3 content. All pristine dispersions were stable with different poly(tetramethylene oxide) glycol (PTMG) number average molecular weights (Mn) of 650, 1000, and 2000. The interaction between the carboxyl acid salt group and Ce(NO3)3 was analyzed by Fourier-transform infrared spectroscopy (FT-IR) and X-ray photoelectron spectroscopy (XPS) techniques. Coating hydrophilicity, water swelling (%), water contact angle, leaching, and corrosion protection efficiency were all affected when using different Ce(NO3)3 content and PTMG molecular weights. The maximal corrosion protection of the WBPU coating was recorded using a higher molecular weight of PTMG with 0.016 mole Ce(NO3)3 content

Theoretical and Experimental Studies of Hydrogen Bonded Dihydroxybenzene Isomers Polyurethane Adhesive Material

Hydrogen bonding in polyurethane (PU) is imposed by molecular parameters. In this study, the effect of structural isomerism of certain monomers on hydrogen bonding of waterborne polyurethane (WBPU) was studied theoretically and experimentally. Two dihydroxybenzene (DHB)-based structural isomers such as catechol (CC) and hydroquinone (HQ), with different OH positions on the inner benzene core, had been used. Two series of WBPU dispersions were prepared using CC and HQ with defined contents. The binding energies between the catechol (CC)/hydroquinone (HQ) (respective OH group) and urethane/urea were calculated theoretically. By using a density functional theory (DFT) method, it was found that the largest binding energy between the urea and CC was higher than that of urea and HQ. The FT-IR analysis of synthesized polymer was also carried out to compare the results with the theoretical values. The CC-based polymers showed a stronger hydrogen bond both theoretically and experimentally than those for HQ-based polymers. The higher level of hydrogen bond was reflected in their properties of CC-based polymers. The adhesive strength, thermal stability, and hydrophobicity were higher for CC-based materials than those for HQ-based materials. The adhesive strength was increased 25% with the addition of 2.0 wt% CC content. This adhesive strength slightly deviated at a moderately high temperature of 80 °C

Static and dynamic adsorption of a gemini surfactant on a carbonate rock in the presence of low salinity water

Abstract In chemical enhanced oil recovery (cEOR) techniques, surfactants are extensively used for enhancing oil recovery by reducing interfacial tension and/or modifying wettability. However, the effectiveness and economic feasibility of the cEOR process are compromised due to the adsorption of surfactants on rock surfaces. Therefore, surfactant adsorption must be reduced to make the cEOR process efficient and economical. Herein, the synergic application of low salinity water and a cationic gemini surfactant was investigated in a carbonate rock. Firstly, the interfacial tension (IFT) of the oil-brine interface with surfactant at various temperatures was measured. Subsequently, the rock wettability was determined under high-pressure and high-temperature conditions. Finally, the study examined the impact of low salinity water on the adsorption of the cationic gemini surfactant, both statically and dynamically. The results showed that the low salinity water condition does not cause a significant impact on the IFT reduction and wettability alteration as compared to the high salinity water conditions. However, the low salinity water condition reduced the surfactant’s static adsorption on the carbonate core by four folds as compared to seawater. The core flood results showed a significantly lower amount of dynamic adsorption (0.11 mg/g-rock) using low salinity water conditions. Employing such a method aids industrialists and researchers in developing a cost-effective and efficient cEOR process