Storage Site Selection Research Articles

The role of structural compartmentalization in carbon storage site selection in Permian (Rotliegend Group) reservoirs in the Southern North Sea

The Southern North Sea (SNS) gas basin is a key area for CO 2 storage projects in the UK. Many of the now-depleted Permian (Rotliegend) Leman Sandstone Formation fields are being re-evaluated as carbon stores. However, the reservoir is known to be highly faulted, often leading to field compartmentalization. This has historically impacted field development and production, and will challenge suitability for CO 2 storage by limiting site capacity, requiring a high number of injector wells, and increasing capital costs. It is necessary to understand the nature of these pressure compartments - and whether any individual culmination can house sufficient capacity - before devising a carbon storage development programme. The highly compartmentalized Indefatigable (Inde) Field was evaluated as a case study. A static model of the field was constructed using 3D seismic and well log data, and subsequently used to calculate the CO 2 capacity of each of the 12 compartments. Five compartments were found to have capacities larger than 10 Mt, with the large Main Horst found to host 51% of total CO 2 capacity. A sequential filling-and-sealing storage site development plan is suggested based on the evaluation and ranking of these compartments.

Evaluation and monitoring of offshore CO2 storage using marine electromagnetic sounding

Abstract The storage of offshore carbon dioxide (CO2) is seen as an effective way to reduce greenhouse gas emissions. Submarine sediments offer a large volume and adequate permeability for the long-term injection of CO2 at high pressure and low temperature. The selection and monitoring of offshore CO2 storage sites have a significant impact on their stability and safety. Therefore, accurately identifying the distribution of offshore CO2 storage is crucial for monitoring. This study utilizes marine controllable source electromagnetic sounding (CSEM) to investigate the sensitivity of identifying plume transport distributions in offshore CO2 storage monitoring. The results show that CSEM is effective in monitoring the distribution of CO2 plumes during offshore storage processes. The changes in electromagnetic field response can reflect the distribution of CO2 plumes, providing important basis for the stability and safety of offshore CO2 storage site selection and monitoring.

Evolution of the Caprock Sealing Capacity Induced by CO2 Intrusion: A Simulation of the Dezhou Dongying Formation

CO2–water–rock interactions have an important impact on the stability and integrity of the caprock in CO2 geological storage projects. The injected CO2 in the reservoir enters the caprock via different mechanisms, leading to either the dissolution or precipitation of minerals. The mineral alterations change the porosity, permeability, and mechanical properties of the caprock, affecting its sealing capability. To evaluate the sealing effectiveness of overlying caprock and identify the influencing factors, numerical simulations and experiments were carried out on the mudstone Dongying Formation in Dezhou, China. Based on high-temperature and high-pressure autoclave experiments, batch reaction simulations were performed to obtain some key kinetic parameters for mineral dissolution/precipitation. Then, they were applied to the following simulation. The simulation results indicate that gaseous CO2 has migrated 7 m in the caprock, while dissolved CO2 migrated to the top of the caprock. Calcite is the dominant mineral within 1 m of the bottom of the caprock. The dissolution of calcite increases the porosity from 0.0625 to 0.4, but the overall porosity of the caprock decreases, with a minimum of 0.054, mainly due to the precipitation of montmorillonite and K-feldspar. A sensitivity analysis of the factors affecting the sealing performance of the caprock considered the changes in sealing performance under different reservoir sealing conditions. Sensitivity analysis of the factors affecting the sealing performance of the caprock indicates that the difference in pressure between reservoir and caprock affects the range of CO2 transport and the degree of mineral reaction, and the sealing of the caprock increases with the difference in pressure. Increasing the initial reservoir gas saturation can weaken the caprock’s self-sealing behavior but shorten the migration distance of CO2 within the caprock. When the content is lower than 2%, the presence of chlorite improves the sealing performance of the caprock and does not increase with further chlorite content. This study elucidates the factors that affect the sealing ability of the caprock, providing a theoretical basis for the selection and safety evaluation of CO2 geological storage sites.

Sub-surface geospatial intelligence in carbon capture, utilization and storage: A machine learning approach for offshore storage site selection

This study introduces an innovative data-driven and machine-learning framework designed to accurately predict site scores in the site screening study for specific offshore CO2 storage sites. The framework seamlessly integrates diverse sub-surface geospatial data sources with human aided expert-weighted criteria, thereby providing a high-resolution screening tool. Tailored to accommodate varying data accessibility and the significance of criteria, this approach considers both technical and non-technical factors. Its purpose is to facilitate the identification of priority locations for projects associated with Carbon Capture, Utilization, and Storage (CCUS). Through aggregating and analyzing geospatial datasets, the study employs machine learning algorithms and an expert-weighted model to identify suitable geologic CCUS regions. This process adheres to stringent safety, risk control, and environmental guidelines, addressing situations where human analysis may fail to recognize patterns and provide detailed insights in suitable site screening techniques. The primary emphasis of this research is to bridge the gap between scientific inquiry and practical application, facilitating informed decision-making in the implementation of CCUS projects. Rigorous assessments encompassing geological, oceanographic, and eco-sensitivity metrics contribute valuable insights for policymakers and industry leaders. To ensure the accuracy, efficiency, and scalability of the established offshore CO2 storage facilities, the proposed machine learning approach undergoes benchmarking. This comprehensive evaluation includes the utilization of machine learning algorithms such as Extreme Gradient Boosting (XGBoost), Random Forest (RF), Multilayer Extreme Learning Machine (MLELM), and Deep Neural Network (DNN) for predicting more suitable site scores. Among these algorithms, the DNN algorithm emerges as the most effective in site score prediction. The strengths of the DNN algorithm encompass nonlinear modeling, feature learning, scale invariance, handling high-dimensional data, end-to-end learning, transfer learning, representation learning, and parallel processing. The evaluation results of the DNN algorithm demonstrate high accuracy in the testing subset, with values of AAPD (Average Absolute Percentage Difference) = 1.486 %, WAAPD (Weighted Average Absolute Percentage Difference) = 0.0149 %, VAF (Variance Accounted For) = 0.9937, RMSE (Root Mean Square Error) = 0.9279, RSR (Root Sum of Squares Residuals) = 0.0068, and R2 (Coefficient of Determination) = 0.9937.

Assessment of the potential of salt mines for renewable energy peaking in China

Renewable energy sources, such as wind and solar, can reduce environmental pollution and promote the transformation of the energy structure. However, the intermittency and uncertainty of new energy sources such as wind and photovoltaics pose challenges to large-scale grid integration. Effective utilization of intermittent energy sources requires large-scale energy storage facilities. Salt rock is recognized as an excellent medium for underground large-scale energy storage with a wide range of applications. This paper identifies the potential of salt caverns to be used for large-scale energy storage by analyzing the distribution of wind and solar energy resources in China, taking into account the grid-connected infrastructure of the Chinese power grid and the geographic location of salt mines. The overlapping areas are identified for utilization in compressed air energy storage and hydrogen storage. Through meticulous categorization and analysis of the factors influencing salt cavern underground storage site selection, the AHP-EWM method is introduced to establish an objective hierarchy model for a comprehensive evaluation system of salt cavern underground storage site selection. The comprehensive planning of China's 20 major salt mines is conducted, and the research findings hold significant reference value for facilitating the low-carbon energy transition in China.

Multi-criteria site selection workflow for geological storage of hydrogen in depleted gas fields: A case for the UK

Underground hydrogen storage (UHS) plays a critical role in ensuring the stability and security of the future clean energy supply. However, the efficiency and reliability of UHS technology depend heavily on the careful and criteria-driven selection of suitable storage sites. This study presents a hybrid multi-criteria decision-making framework integrating the Analytical Hierarchy Process (AHP) and Preference Ranking Organisation Method for Enrichment of Evaluations (PROMETHEE) to identify and select the best hydrogen storage sites among depleted gas reservoirs in the UK. To achieve this, a new set of site selection criteria is proposed in light of the technical and economic aspects of UHS, including location, reservoir rock quality and tectonic characteristics, maximum achievable hydrogen well deliverability rate, working gas capacity, cushion gas volume requirement, distance to future potential hydrogen clusters, and access to intermittent renewable energy sources (RESs). The framework is implemented to rank 71 reservoirs based on their potential and suitability for UHS. Firstly, the reservoirs are thoroughly evaluated for each proposed criterion and then the AHP-PROMETHEE technique is employed to prioritise the criteria and rank the storage sites. The study reveals that the total calculated working gas capacity based on single-well plateau withdrawal rates is around 881 TWh across all evaluated reservoirs. The maximum well deliverability rates for hydrogen withdrawal are found to vary considerably among the sites; however, 22 % are estimated to have deliverability rates exceeding 100 sm3/d, and 63 % are located within a distance of 100 km from a major hydrogen cluster. Moreover, 70 % have access to nearby RESs developments, with an estimated cumulative RESs capacity of approximately 181 GW. The results highlight the efficacy of the proposed multi-criteria site selection framework. The top five highest-ranked sites for UHS based on the evaluated criteria are the Cygnus, Hamilton, Saltfleetby, Corvette, and Hatfield Moors gas fields. The insights provided by this study can contribute to informed decision-making, sustainable development, and the overall progress of future UHS projects within the UK and globally.

Origin of CO2 in Upper Devonian Duperow Formation and the Bakken Petroleum System at Kevin Dome, Northwest Montana

Carbon capture and storage (CCS) is a key mitigation strategy in achieving global net-zero emissions. It is therefore essential to identify and characterize potential subsurface storage repositories. Natural CO2 accumulations provide an opportunity to understand the behavior of CO2 in the subsurface. Here, we investigate the source(s), migration, and storage of CO2 in the Upper Devonian Duperow Formation at Kevin Dome, northwest Montana, USA within the Bakken Petroleum System. We report, major gas, stable and noble gas isotopic compositions in bulk gas samples (n = 19) produced from nearby hydrocarbon-bearing reservoirs at Kevin Dome and compare with CO2 bearing fluid inclusions (n = 24) from the Duperow Formation. Using the same methods, bulk gas samples (n = 9) from the adjacent Ferguson Field, (Exshaw/Bakken Petroleum System) in southern Alberta, Canada, and fluid inclusions from the Sweetgrass Hills igneous complex (n = 2) were analyzed to understand CO2 generation and the subsequent processes affecting CO2 regionally. We find that CO2 in the Upper Devonian Duperow Formation is magmatic in origin, likely related to the nearby Sweetgrass Hills igneous complex intrusion (∼52 Ma), whereas CH4 and N2 gases are generated predominantly by thermogenic processes associated with hydrocarbon generation during burial. Since emplacement, most CO2 in the hydrocarbon-bearing reservoirs of the Bakken petroleum system at Kevin Dome (∼98%) and the Ferguson Field (∼82%) has subsequently been dissolved into the groundwater. We employ a solubility model to calculate minimum gas/water ratios in Kevin Dome and the Ferguson Field, which are consistent with more groundwater interaction and more dissolution at Kevin Dome. Understanding the subsurface processes affecting CO2 is critical for future CO2 storage site selection.

Integrated GIS-AHP-based approach for off-river pumped hydro energy storage site selection

Pumped hydro energy storage (PHES) solutions enable greater diffusion of renewable energy into the electricity grid. However, accelerated development of PHES is complex due to the numerous spatially relevant technical, environmental, social, and economic criteria that must be assessed to determine a pumped hydro sites feasibility. With the goal to rapidly narrow down feasible sites from a large land area, this study developed a Geographic Information System (GIS) and Analytic Hierarchy Process (AHP) based technique to autonomously identify PHES sites based on a range of environmental and technical criteria. Following GIS-AHP analysis, Levelized Cost of Energy (LCOE) scenario analysis was conducted with a limited number of feasible sites, as well as their carbon abatement potential. The developed approach was demonstrated for the case of Northern Queensland (NrQLD), Australia. The developed GIS-AHP PHES site selection approach identified 14 potentially feasible sites. For the base case scenario, these sites could generate 366.94 TWh over their lifetime while abating 300 ktCO2eq. The LCOE of these 14 PHES sites ranged between 0.04 AU$/kWh and 0.27 AU$/kWh for the base case scenario. The developed approach has implications for energy planning managers seeking to efficiently narrow down feasible PHES sites, which are essential storage enablers for transitioning to a zero-emissions economy.

MULTIMOORA Method-Based Schweizer–Sklar Operations for CO2 Geological Storage Site Selection Under Pythagorean Fuzzy Environment

The site selection of CO2 geological storage facilities is essential for the development of safe and efficient carbon capture, utilization, and storage (CCUS) projects. Normally, CO2 geological storage site selection can be regarded as a complex multi-criteria decision-making (MCDM) problem. The aim of this paper is to present an integrated decision-making method for solving the site selection problem for CO2 geological storage. To achieve this goal, this method is based on multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA) method and prioritized aggregation operators in Pythagorean fuzzy environment. The academic contributions of this study include: first, some Pythagorean fuzzy Schweizer–Sklar prioritized aggregation (PFSSPA) operators are proposed, which take into account the priority levels of criteria and the risk preferences of decision makers. The excellent properties of these operators are given. Then this study extends the classical MULTIMOORA method based on the developed aggregation operators (named PFSSPA-MULTIMOORA), and the calculation process of this method is described in detail. Subsequently, on the basis of the constructed criteria system, the PFSSPA-MULTIMOORA method is applied to rank the alternatives. Finally, we successfully utilized the PFSSPA-MULTIMOORA method to solve the site selection problem of CO2 geological storage in China. A comparative analysis of existing methods verifies the effectiveness and robustness of the proposed method. This work can provide advanced decision support for researchers and practitioners.

Sustainable carbon-dioxide storage assessment in geological media using modified Pythagorean fuzzy VIKOR and DEMATEL approach

In a developing country like India, the primary source of power generation is fossil fuels. The lion's share of India's electricity production is from fossil fuels leading to massive greenhouse gas emissions (GHG) like CO2, which causes global warming. To deal with climate change and control global warming, the carbon capture utilization and storage (CCUS) project in geological formation is a practical, comparatively secure, inevitable and emergent method to be materialized. However, CO2 storage in deep geological structures in the sedimentary basin has a risk of leakage due to the geological formation of different seams, which might harm human beings, including different underground, terrestrial, and aquatic species. It could affect the energy sources of our environment also. Therefore the selection of CO2 storage site in geological media is based on some criteria, and therefore it is a multi-criteria decision-making (MCDM) problem. The multi-criteria group decision-making (MCGDM) method is proposed to get a more impartial result, using the soft computing methodology Pythagorean fuzzy VIKOR (“VIekriterijumsko KOmpromisno Rangiranje”, a Serbian term for “multi-criteria optimization and compromise solution”) modified with a novel divergence called Pythagorean fuzzy Jensen-Shannon Song (PJSS). The fuzzy DEMATEL (DEcision MAking Trial and Evaluation Laboratory) method is introduced to evaluate the criteria weights. A Comparative Study and Sensitivity analysis are also presented in this article. Finally, the outcomes of the work show that the proposed methodology is feasible.

Research on the scheduling scheme of resource storage locations in deep-sea oil and gas exploitation

Crucial components of the exploration and exploitation of deep-sea oil and gas resources include the identification of pre-disaster emergency resource storage locations and the appropriate scheduling of emergency resources. Frequently, integer linear programming or integer nonlinear programming is used to investigate them. Both techniques may result in optimization, but it is difficult to determine the global optimal solution. Consequently, this study presents a two-stage optimization model of emergency resource storage location-scheduling that not only surpasses the limitations of independent research but also applies an intelligent optimization algorithm to discover the global optimal solution. In the first phase of the model, the objective of optimization is to decrease the emergency response time. Uncertainty and unpredictability are incorporated as marine environmental components in the goal function. Using the analytic hierarchy method, the effect of resource storage and location is evaluated, and the genetic algorithm (GA) and immune algorithm (IA) are used to determine the goal model's optimal solution. The objective of the second stage is to optimize resource scheduling satisfaction, and the resource storage locations determined in the first stage are assigned using a fuzzy trigonometric function formula and mathematical programming algorithm. The two-stage optimization methodology is shown using the deep-sea fire explosion incidence as an example. The results suggest that the transit time of resources from the resource storage site selection points to the operation points calculated by GA is 50% less than that obtained by IA, and the 4 time of IA is at least 5 times that of GA. The overall resource scheduling time is lowered by 41.1% compared to conventional shore-based terminals, the economic cost of an accident is minimized, and the life safety of on-site operators is improved. Throughout 1000 different seasons, the objective ideal value and average value of GA and IA are compared. GA has a slower convergence rate than IA, but its convergence quality is much higher. The quantity of emergency supplies given by each resource storage site may meet the resource need of the operational point. We believe that the model proposed in this study can guarantee the accuracy of prediction results in situations of small sample sizes, and its validity and applicability have been validated.

CO2 capture, utilization, and storage (CCUS) storage site selection using DEMATEL-based Grey Relational Analysis and evaluation of carbon emissions with the ARIMA method.

Various systems are increasing gradually to reduce environmental concerns carbon capture, use, and storage (CCUS) systems are one of the most preferred processes in this context. Special areas such as depleted oil and gas reservoirs, aquifer reservoirs, and salt cave reservoirs are required needed to use this technology and, considering various criteria to decide on these areas is necessary. In this study, the problem of choosing the most suitable CCUS site selection for Turkey is discussed. In the study, for the alternative areas (Adıyaman, Aksaray, Diyarbakır, Afyon, and Tekirdağ) determined, 11 sub-assessment criteria (cost, CO2 state, regional risk, infrastructure availability, reservoir permeability, storage capacity, thickness reservoir, porosity, transportation availability, sustainability, facilities in operation by application) were discussed under CCUS main criterias (carbon capture, carbon storage, and carbon use). The DEMATEL method was used for the weights of the evaluation criteria. Unweighted gray relational analysis (GRA) method and DEMATEL-based GRA method were used to rank the alternatives. According to unweighted GRA results, Aksaray, Adıyaman, Afyon, Tekirdağ, and Diyarbakır decisions are obtained, respectively. According to the weighted GRA results, Aksaray, Adıyaman, Tekirdağ, Afyon, and Diyarbakır decisions are obtained, respectively. Calculation results demonstrated that Aksaray region is the most suitable alternative CCUS area for both methods. The CO amount values for the next period were estimated for this area and evaluated with the auto-regressive integrated moving average (ARIMA) method by the Minitab. By considering 1013 days of CO data, according to the MA(1) model estimation results were obtained values between 410.899 (μg/m3) and 459.909 (μg/m3). With the installation of the CCUS facility, this value could be checked again by examining it. The use of real data in the study increases the effectiveness of the proposed approach.

Nonlinear mechanical characteristics and damage constitutive model of coal under CO2 adsorption during geological sequestration

Geological sequestration of CO2 is an effective way to achieve the goal of reducing global warming and carbon neutralization. The complex CO2–coal interaction will lead to the change of mechanical properties of coal. Therefore, evaluating the mechanical characteristics of deep coal seam after CO2 adsorption is of great significance for analyzing the geological characteristics and structural stability of deep strata and storage site selection. In this study, the triaxial compression test and acoustic emission (AE) test were used to evaluate the effect of CO2 adsorption pressure on the mechanical properties of coal mass. On the basis of the evolution characteristics of AE ring down count (RDC), fractal theory was used to analyze the deformation and fracturing evolution of coal. Besides, an elastic damage constitutive model describing the nonlinear stress-strain relationship of coal under CO2 adsorption is established. Results show that the growth of adsorption pressure develops the risk of damage and fracturing of coal. With the increase in adsorption pressure, the value of singularity index width Δα presents a downward trend, indicating the development of internal cracks and the increase in the complexity of microunit fracturing process. When the adsorption pressure is low, the gas in large cracks and pores leads to the generation of small AE signal that occupies the dominant position. High adsorption pressure increases the complexity and nonlinearity of coal deformation, strengthens the proportion of large AE signal, and leads to the increase in the average value of multifractal spectrum width Δf. With the increase in adsorption pressure, the fracturing degree of coal is higher, a mass of large-size cracks appears, and more AE spectrum presents intensive distribution. In the plastic stage, the load level is close to the strength limit, the microcracks intersect with each other, and the average value of Δα in this stage is the smallest.

Assessment of CO2 storage potential in reservoirs with residual gas using deep learning

[Formula: see text] injection into the underlying water leg of depleted hydrocarbon reservoirs is a desirable option for carbon storage as demonstrated by existing industrial-scale storage projects in these geologic environments. This study sheds light on the effect of residual methane on the [Formula: see text] storage efficiency as a screening criterion for selecting a water-bearing zone of a depleted gas reservoir to store [Formula: see text]. Using compositional reservoir simulations, we have evaluated the impact of residual methane on the injectivity, operational pressure, and long-term [Formula: see text] trapping efficiency during injection and postinjection stage in a reservoir model representative of the so-called “HC sand” gas reservoir in the High Island 24L field located in the offshore Texas State Waters. Results suggest that the presence of residual hydrocarbon gas negatively affects [Formula: see text] residual and dissolution trapping because it enhances the injectivity and pressure management arising from the increased mobility of [Formula: see text] plume in the vicinity of the injection zone due to its mixing with the resident residual hydrocarbon gas. We further investigate the application of artificial neural network (ANN)-based proxy models for fast-track modeling of [Formula: see text] storage in geologic structures associated with depleted gas reservoirs, aiming at the prediction of [Formula: see text] trapping efficiency. We then use the developed ANN model to perform Monte Carlo simulations for quantifying the uncertainty of geologic and reservoir parameters on [Formula: see text] trapping efficiency in these formations. It becomes evident that the residual hydrocarbon saturation is a key screening criterion for the storage site selection. The developed data-driven model can offer a robust and fast tool for screening the water-bearing zone of the depleted gas reservoirs by evaluating the efficiency of [Formula: see text] storage.

MULTI-CRITERIA ASSESSMENT (MCA) AND SELECTION OF A SOLID WASTE DISPOSAL SITE WITHIN WA MUNICIPALITY, UPPER WEST REGION, GHANA

Municipal solid waste management is a problem in most developing countries of the world. This is because of its nature, quantity generated, cost of transportation and the selection of final storage sites, which together presents a huge challenge for most municipalities. Improper solid waste disposal has serious environmental consequences which ultimately affects human health. The most common problems associated with improper selection and management of final waste disposal sites for solid waste include disease transmission, fire hazards, odour nuisance, air and water pollution, aesthetic nuisance. Economic cost arising from transportation due to long distances of travel to deposit solid waste also discourage the use of waste disposal sites. Municipal solid waste management is considered one of the most serious environmental and social problems faced by municipal authorities in developing countries.. This work considered the selection of a suitable site for the disposal of municipal solid waste generated within the Wa Municipality of the Upper West Region of Ghana, using Multi-Criteria Evaluation technique in G.I.S. To determine the most suitable waste disposal sites in the municipality, the study integrated environmental and socio-economic criteria including proximity to road networks, distance to residential and important built-up areas, water bodies to select the most optimal location for waste disposal. The results showed a total of three (3) proposed suitable sites, out of which a site with reasonably optimal distance as well as easily accessible to roads was preferred as the most suitable site for the municipal solid waste disposal (landfill) in the Wa Municipality.

Sensitivity Analysis Strategy to Assess the Salting-Out Problem during CO2 Geological Storage Process

The sensitivity analysis of the salting-out effect on well injectivity is a significant work in the research of geological storage of CO2 in deep saline aquifers, which is helpful in the selection of storage sites and the design of the injection strategy. We conduct a detailed sensitivity analysis about the salting-out process using the local sensitivity method and two global sensitivity methods. Sensitivity coefficients showed that brine salinity (XNaCl) has the highest sensitivity and interaction effect, the CO2 injection rate (QCO2) has a greater influence in the early stage of the salting-out process and a smaller influence in the end stage, and the other three parameters (empirical parameters related to the pore distribution m, the liquid residual saturation in the relative permeability function Splr, and the liquid residual saturation in the capillary pressure function Sclr) have a smaller sensitivity. This paper also analyzes the calculation amount of different sensitivity methods and suitable ways of obtaining the sensitivity coefficient and reveals the following. (1) The sensitivity coefficient changes dynamically with time, if only the sensitivity of the final state is taken into account on a long-time physical process, and some sensitive parameters during the process may be neglected. (2) The selection of the sample size should be based on the convergence of multiple calculations, and the results of the empirical calculation are uncertain. (3) The calculation of Sobol sensitivity is complicated, the results calculated by surrogate model depend on whether the sample is representative enough; on the other hand, it is feasible to use Sti-Si approximation to characterize the second-order sensitivity to reduce the computation. The research results not only reveal the sensitivity of the parameters related to the injection well salting-out problem during CO2 storage in deep saline aquifers but also guide the calculation of global sensitivity analysis with a similar physical process.

Characterizing the Effect of Capillary Heterogeneity on Multiphase Flow Pulsation in an Intermediate‐Scale Beadpack Experiment Using Time Series Clustering and Frequency Analysis

AbstractAn intermediate‐scale beadpack drainage experiment was conducted to investigate how simple layered lamination heterogeneity affects CO2 flow. Two simple layers of capillary barriers are manually packed in the tank and slow drainage was carried out using analog fluids to mimic the capillary‐ and gravity‐dominated CO2 upward migration process in deep saline aquifers. Nonwetting phase saturation time series clustering analysis and frequency analysis have been conducted on the experimental data. Additionally, modified invasion percolation numerical simulations were done on a digital model of the beadpack to compare to experimental results. Results show that capillary barriers can lead to strong pulsation behavior, which in turn can cause unexpected early breaching through other barriers. The inlet pressure is found to be able to respond to saturation changes in far regions of the domain, indicating that the wetting phase can transmit pressure changes from the other phase. Although static simulations were not able to capture all the dynamic behavior observed in the experiment, Monte Carlo composite simulation results combining many different realizations can better illustrate how the nonwetting phase will behave in the heterogeneous domain. Our results suggest the need for CO2 storage site selection with preference given to aquifers with more capillary barriers with finer grain sizes to avoid flow pulsation and to retard plume upward migration.

Experimental study on the evolution of rock strength and sealing properties under multi-cycles alternating loading

Different from the long-term and low-speed depletion of conventional gas fields or monotonous gas injection in carbon dioxide geological sequestration, the engineering background of multi-cycle intensive injection and production of underground gas storage (UGS) makes the dynamic sealing capacity and stability of the trap cap and pipe string under alternating load become the key problem that cannot be ignored. Firstly, the basic mechanical parameters of sandy mudstone and G-grade oil well cement were determined by conventional uniaxial tests, then, different upper load levels and alternating times were set to carry out alternating mechanical tests for sandy mudstone and G-grade oil well cement stone. The deformation, failure and stress-strain curve characteristics of the two types of rocks were analyzed, and the variation laws of the strength and elastic modulus with the upper stress and the alternating times of the two types of rocks were obtained: The strength of cement stone decreases, while that of sandy mudstone increases with the increase of upper limit stress and alternating times, and the reasons for the different laws of the two types of rocks were further analyzed. Then, after undergoing different alternating times with different upper load levels, the dynamic breakout pressure tests of two types of rocks were carried out by the step-by-step method. The results show that the breakthrough pressure of the two types of rocks decreased gradually and significantly with the increase of the alternating times. The dynamic evolution prediction model of the breakthrough pressure with the alternating times was established. And because the breakthrough pressure of the cement stone in the nondestructive state exceeds the measuring range of the equipment, the initial breakthrough pressure of the cement rock was also predicted by the prediction model of the breakthrough pressure. All of these results above can be significant reference value for the sealing evaluation of gas storage site selection and the real-time monitoring after it is put into operation.

A criteria-driven approach to the CO2 storage site selection of East Mey for the acorn project in the North Sea

Carbon Capture and Storage (CCS) is an essential tool in the fight against climate change. Any prospective storage site must meet various criteria that ensure the effectiveness, safety and economic viability of the storage operations. Finding the most suitable site for the storage of the captured CO2 is an essential part of the CCS chain of activity. This work addresses the site selection of a second site for the Acorn CCS project, a project designed to develop a scalable, full-chain CCS project in the North Sea (offshore northeast Scotland). This secondary site has been designed to serve as a backup and upscaling option for the Acorn Site, and has to satisfy pivotal project requirements such as low cost and high storage potential. The methodology followed included the filtering of 113 input sites from the UK CO2Stored database, according to general and project-specific criteria in a multi-staged approach. This criteria-driven workflow allowed for an early filtering out of the less suitable sites, followed by a more comprehensive comparison and ranking of the 15 most suitable sites. A due diligence assessment was conducted of the top six shortlisted sites to produce detailed assessment of their storage properties and suitability, including new geological interpretation and capacity calculations for each site. With the new knowledge generated during this process, a critical comparison of the sites led to selection of East Mey as the most suitable site, due to its outstanding storage characteristics and long-lasting hydrocarbon-production history, that ensure excellent data availability to risk-assess storage structures. A workshop session was held to present methods and results to independent stakeholders; feedback informed the final selection criteria. This paper provides an example of a criteria-driven approach to site selection that can be applied elsewhere.

Knowledge Mapping and Research Progress of Wind Energy Application Based on CiteSpace

The global demand for new energy has entered an unprecedented era, and the application of wind energy is one of the key contents in the development of new energy. Taking the “wind energy + application” in WOS (Web of Science) and CNKI database as the retrieval target, and the relevant papers retrieved as the research data, this paper uses the scientific knowledge mapping software (CiteSpace5) to carry out the keyword commonality analysis, cluster analysis and time mapping analysis on wind energy application scenarios.Finally, summarized research hotspots and forecasted its research trends in wind energy application scenarios in global and China. The results show that the international wind energy application research hotspots and trends are wind energy storage and wind power project site selection; In China there are offshore wind power and wind energy evaluation.