Estimation Of CO2 Storage Capacity Research Articles

Sedimentological and petrophysical characterization of the Bokabil Formation in the Surma Basin for CO2 storage capacity estimation

Large-scale geological sequestration of CO2 is one of the most effective strategies to limit global warming to below 2 °C, as recommended by the Intergovernmental Panel on Climate Change (IPCC). Therefore, identifying and characterizing high-quality storage units is crucial. The Surma Basin, with its four-way dip closed structures, high-quality reservoirs, and thick regional cap rocks, is an ideal location for CO2 storage. This study focuses on the Bokabil Formation, the most prominent reservoir unit in the Surma Basin. Detailed petrographic, petrophysical, XRD, and SEM analyses, along with mapping, have been conducted to evaluate the properties of the reservoir and cap rock within this formation. The Upper Bokabil Sandstone in the Surma Basin ranges from 270 to 350 m in thickness and consists of fine- to medium-grained subarkosic sandstones composed of 70–85% quartz and 5–12% feldspar, with good pore connectivity. Petrophysical analysis of data from four gas fields indicates that this unit has a total porosity of 21–27.4% and a low shale volume of 15–27%. Cross plots and outcrop observations suggest that most of the shales are laminated within the reservoir. The regional cap rock, known as the Upper Marine Shale (UMS), ranges in thickness from 40 to 190 m and contains 10–40 nm nano-type pores. A higher proportion of ductile materials with a significant percentage of quartz in the UMS indicates higher capillary entry pressures, enhancing its capacity to hold CO2. Using the CSLF method with a 6% cut-off of the available pore volume, it is estimated that 103 Mt, 110 Mt, 205 Mt, and 164 Mt of CO2 can be effectively stored in the Sylhet, Kailashtila, Habiganj, and Fenchuganj structures, respectively. Due to the shallow depth of the storage unit and the thick cap rock, the southern Surma Basin is the optimal location for CO2 injection.

Estimation of CO2 storage capacities in saline aquifers using material balance

Estimating CO2 storage capacities is crucial in developing carbon capture and storage projects. Material balance equation (MBE) methods, widely employed for oil and gas reserve estimation, offer a direct approach to estimating CO2 storage capacities. However, previous MBE methods rely on an original fluid in-place volume calculated using volumetric methods to estimate CO2 storage capacities, lacking validation for accuracy. It is essential to accurately estimate the original fluid in-place volume, representing the pore volume, as it substantially influences CO2 storage capacity. This study presents a refined MBE method that ensures accurate estimates of CO2 storage capacities by validating the original fluid in-place volumes in saline aquifers. The accuracy of this method was evaluated by comparing it with a commercial reservoir simulator for a synthetic aquifer example and the Sleipner L9 model. In the synthetic aquifer example, the relative error in CO2 storage capacity estimation with the proposed MBE method was only 2.09%, even when short-term (1-year) injection data were utilized. The proposed MBE method demonstrates consistent accuracy in estimating CO2 storage capacities under different aquifer properties, operating conditions, and MBE-related conditions. The proposed MBE method also accurately estimated the CO2 storage capacity in the Sleipner L9 model, achieving a relative error of 3.47%.

Comparative Study of CO2 Storage Capacity Estimation in Depleted Oil & Gas Reservoir: A Case Study in Vermillion Basin Gulf of Mexico

CO2 emissions rates have seen an exponential growth from the 19th century up till date, if no drastic measures and plans are implemented to prevent this exponential growth the consequence will be devastating. The notion of achieving net-zero greenhouse gas emissions gained prominence through the Paris Agreement, a groundbreaking accord reached at the United Nations Climate Change Conference. This agreement was devised to mitigate the impact of greenhouse gas emissions. To execute the net-zero CO2 emission plan, the USDOE has set a new goal to remove gigatons of carbon dioxide (CO2 ) from the atmosphere and durably store it for less than $100/ton of net CO2 -equivalent. Making such a goal a reality requires an accurate estimation of CO2 storage capacity for the successful implementation of Carbon Capture and Storage (CCS) technologies, and the assessment of the impact of CCS to the reduction of CO2 emissions. Hence this paper serves as a template for accurately estimating CO2 storage capacity in depleted saturated oil reservoirs with initial gas cap using three approaches: Volumetric, Production and Correlation-based methods and compares the accuracy of the estimates. A case study was conducted on a depleted VR273_Q combination sand in the Vermillion Basin, Gulf of Mexico (GOM). The deterministic and stochastic (P50) CO2 storage capacity estimates from the Volume-based method are 1.21 million tonnes (Mt) and 1.23 Mt respectively, while the deterministic CO2 storage capacity estimates from the Production and Correlationbased method are 1.32 Mt and 1.41 Mt respectively. All three approaches showed similar results, with little deviations attributed to petrophysical uncertainties arising from data gaps i.e., absence of well logs to key wells. However, these uncertainties are captured by Stochastic (P90) CO2 storage capacity estimates of 1.47 Mt from the Volume-based method. Although the Correlation-based approach slightly overestimates the CO2 storage capacity, it can be used as a starting point for quick estimation as it only requires production data which are readily available on various databases for GOM. Finally, through this paper, opportunities for concerned agencies to make well-informed energy-related policies and business decisions are made possible.

Screening, classification, capacity estimation and reservoir modelling of potential CO2 geological storage sites in the NW Adriatic Sea, Italy

In Italy, the central-northern Apennines and Adriatic Sea domains have been identified as potential CO2 storage areas. Although capacity estimates have been undertaken at a regional scale, more detailed research is required to reduce uncertainty. The present study helps address this gap by conducting a detailed screening of a representative area in the north-western Adriatic Sea for suitable CCS sites, using an extensive dataset composed of both public and private seismic and borehole data. Work included selecting suitable sites based on proposed selection criteria, calculating their theoretical and effective storage capacities applying a probabilistic approach, and then performing dynamic flow modelling on one of the selected sites that is representative of fractured carbonate reservoirs. Based on the screening results, a total of 21 out of 38 structures were selected as having the required characteristics suitable for CO2 storage. As expected, the clastic rock reservoirs have the greatest potential capacity, although some fractured carbonate reservoirs did yield important volumes due to their dual porosity / permeability characteristics. Modelling of one such site highlighted the complex interplay between primary and secondary porosity / permeability on plume migration and capacity estimation. Our results highlight the need to integrate analytical calculations with dynamic simulations for more detailed, site-specific studies to improve the estimates of CO2 storage capacity.

Assessment and uncertainty quantification of onshore geological CO2 storage capacity in China

We provide a probabilistic assessment of CO2 storage capacity in major sedimentary basins in China. Our approach embeds constraints associated with the increase of reservoir pore pressure due to injection of CO2 in the presence of resident brine. Pressure build-up must be limited to avoid fault reactivation, caprock failure, and possible leakage, resulting in more conservative estimates of CO2 storage capacity as compared to volumetric estimates.We rely on a numerical Monte Carlo framework considering uncertainty in the values of reservoir size and major geological formation attributes (i.e., absolute permeability, porosity, and reservoir compressibility). Our work shows that 10 major basins can potentially store, on average, 1350 Gt of CO2 during the next 30 years (lower and upper quartiles being 1100 and 1700 Gt of CO2, respectively). This far exceeds the likely amount (up to 175 Gt of CO2) required to be stored by 2050. Our analysis also suggests that 6 basins (located close to the largest emission areas) can store about 93 Gt (on average) of CO2 during the next 30 years. Underground carbon storage in China, coupled with other possible solutions, could meet the aims of the Announced Pledges Scenario (International Energy Agency) to mitigate global warming by 2060.We also perform a global sensitivity analysis to determine how our predictions of storage capacity may be affected by uncertainties in the simulation model input parameters. Moment-based global sensitivity metrics suggest that geological formation attributes are major sources of uncertainty, significantly affecting model outputs and the associated uncertainty.

Dynamic estimates of extreme-case CO2 storage capacity for basin-scale heterogeneous systems under geological uncertainty

Geological CO2 storage is expected to grow dramatically in the coming decades to meet global climate targets. Assessment of worldwide storage resources using static methods indicates significant theoretical potential for large-scale deployment. Dynamic capacity estimates are needed at the basin-scale that fully capture the impact of geological uncertainty and account for regional limits on pressure buildup. Accurate quantification of the risk of low or critically low capacity under extreme occurrences of heterogeneity will be increasingly important. There are significant challenges associated with efficient computation of low probability capacity within Monte Carlo frameworks at these scales. In this paper, we propose a workflow for uncertainty quantification that is able to efficiently estimate increasingly outer percentiles of dynamic capacity such as P1, P0.1, or even lower probability events. Our approach is based on the rare-event methodology that uses a subset simulation approach to concentrate sampling of the parameter space in the tail regions of the capacity distributions. This approach greatly speeds up uncertainty quantification for very small probabilities compared to standard Monte Carlo. We demonstrate the method by introducing a correlated heterogeneity field to a highly prospective basin-scale system that can support regional injection rates of 100 million tons annually. We find that the outer quantiles are more sensitive to the underlying geostatistical model compared to the median P50 capacity. This implies that for large-scale systems, well characterized heterogeneity is essential to identify the likelihood of very rare yet still relevant dynamic estimates of storage capacity.

Co2 Storage Capacity Estimation Of Depleted Oil And Gas Reservoirs In Indonesia

Implementation of co2 capture and geological storage technology at the scale needed To achieve a significant and meaningful reduction in co2 emissions requires knowledge of The available co2 storage capacity. Various geological formations located across many Islands in indonesia appear to be potential to store the anthropogenic co2, particularly in Depleted oil and gas reservoir. These depleted oil and gas reservoirs are appropriate Candidates for co2 storage. However, the capacity of this geological formation has not Been estimated yet. The objective of this study is to estimate the storage capacity of depleted Oil and gas reservoirs in indonesia using the methodology, developed by carbon Sequestration leadership forum (cslf). Screening result from our databases showed there Were 103 depleted oil and gas fields were considered depleted from their np/ult ratio (hydrocarbon cumulative production over ultimate recovery) which were 55%. However, Only 48 fields had complete data to estimate. We used the methodology that was Initially developed by cslf but then it had been simplified by poulsen et al. We considered This methodology as the most convenient to use in this country scale of assessment despite Of any simplification had been made. Estimation result showed riau and south sumatra Region have large storage capacities which are around 229 and 144 mtco2 respectively. The estimates of co2 storage capacity reflects the actual capacity that was based on data Availability during the assessment. The potential storage capacity might change as data Becoming more available. Hence, the storage capacity map resulted from this study is not Conclusive estimation. However, this study indicates that indonesia has huge potential of Co2 storage in depleted oil and gas reservoirs.

Injection data analysis using material balance time for CO2 storage capacity estimation in deep closed saline aquifers

Estimating the ultimate storage capacity of deep saline aquifers is important to address the formation potential to store the envisioned large volumes of CO2. Injection data (i.e. injection rate, bottomhole pressure, and cumulative injected volume of CO2) are routinely recorded during storage operations. These data contain valuable information on the subsurface (e.g. the reservoir pore volume and the formation storage capacity) that can be extracted. In this paper, we present a two-step graphical technique to infer the pore volume and the ultimate storage capacity of closed saline aquifers by analyzing the available injection data. First, the pore volume is inferred through adapting the concept of the material balance time. Material balance time is an approximate superposition time function developed to interpret production data from oil and gas wells operating at variable pressure/rate conditions during the boundary-dominated flow period. Using material balance techniques, the ultimate storage capacity is then estimated through linear extrapolation of the average pressure trend to the maximum allowable pressure the formation can withstand. The average pressure is not available in practice, but is can be obtained from the injection data. Two approaches are presented in this study to calculate the average pressure; namely the rigorous and the approximate approaches. Unlike the rigorous approach, the approximate approach does not require a prior knowledge of some reservoir properties (e.g. relative permeability, absolute permeability, formation porosity and thickness) to calculate the average pressure. To investigate its potential and reliability in analyzing CO2 injection data, the proposed technique is applied to four synthetic cases representing different well operating conditions. Results indicate that the approximate approach consistently overestimates the actual (simulated) storage capacity as compared to the rigorous approach. The agreement - between the inferred and the simulated reservoir pore volume, and between the analytical and numerical estimates of storage capacity - validates the potential application of the technique to CO2 storage in closed saline aquifers. The technique is further substantiated through application to a field data set utilized from a commercial-scale geological storage (CGS) project. Field data interpretation shows that the proposed technique can be utilized to identify the degree of hydraulic continuity and reservoir compartmentalization within a target formation by interpreting the corresponding pressure and rate responses.

Impact of petrophysical heterogeneities and fault representation on geological CO2 storage capacity estimation using coupled hydro-mechanical simulations

Impact of petrophysical heterogeneities and fault representation on geological CO2 storage capacity estimation using coupled hydro-mechanical simulations

Analytical and numerical modeling for the assessment of CO2 storage in the Pariñas geological formation - Talara, Peru

This research evaluates the CO2 storage capacity of the Pariñas Formation belonging to the Talara basin in Peru through analytical modeling based on mass balance equations and numerical modeling using IMEX CMG. Pariñas Formation has several depleted hydrocarbon reservoirs that presents favorable conditions for CO2 geological storage. It has an average porosity of 17.6% and a permeability of 640 mD in the horizontal direction consisting of sandstones with interspersed lutites layers. The study evaluates the depleted Bellavista oil deposits involving CO2 storage capacity estimation with CO2 and reservoir fluid (oil and water) interaction. It involves numerical modeling based on the reservoirs properties and CO2 injection simulation not exceeding the fracture pressure of the reservoir rock. This approach is the first one carried out in Peru and provides the chance to evaluate the CO2 storage capacity in a hydrocarbon reservoir in this part of the world, as a strategy to mitigate future global change impacts. The results indicate a storage capacity of 35.37 million tons of CO2, approximately. Besides, the sandstone reservoir of the Pariñas geological formation has adequate characteristics to serve as a CO2 storage reservoir. C30+ pseudo component shows greater sensitivity in its properties (temperature and critical pressure) adjusting the fluid properties with the experimental data (saturation pressure, viscosity and minimum miscibility pressure).

Experimental study of three-dimensional CO2-water drainage and fracture-matrix interactions in fractured porous media

Estimation of CO2 storage capacity in fractured porous reservoirs requires a better understanding of the CO2-water flow fundamentals in fracture-matrix systems. There are few core-flood experiments on three-dimensional CO2-water drainage in a fracture-matrix system, yet none have examined the impacts of the capillary continuity of fractures and fracture-matrix interactions. In this study, twelve drainage experiments were conducted in four fracture-matrix columns, each comprising a vertical stack of a cylindrical rock core, a filter paper serving as an analogue to a horizontal fracture, and a ceramic plate. The core sample was surrounded by open space at the top and circumferential sides to model fractures, allowing for 3-D CO2-water drainage in the rock core and displaced water draining across the horizontal fracture. X-ray computed tomography was conducted to visualize the dynamic invasion/drainage processes in four rock core samples showing contrasts in anisotropy, permeability, and heterogeneity. Experimental results show (1) the equilibrium CO2 saturations in the rock matrix vary from 0.10 to 0.60 at controlled capillary pressures up to 200 kPa, (2) the CO2 saturations in the matrix increaze with water saturation in the horizontal fracture resulting in better capillary continuity for water to drain across the fracture, and (3) the fracture water saturation can be enhanced by the non-uniform fracture capillary pressure and countercurrent flow of CO2 and water across the fracture-matrix interface. In the case of high fracture water saturation, matrix CO2 saturation largely depends on matrix anisotropy and heterogeneity. The core-scale experimental results contribute to understand the fracture-matrix interactions and CO2 storage efficiency in fractured porous media.

CO2 storage capacity estimation under geological uncertainty using 3-D geological modeling of unconventional reservoir rocks in Shahejie Formation, block Nv32, China

Underground CO2 storage is a promising technology for mitigating climate change. In this vein, the subsurface condition was inherited a lot of uncertainties that prevent the success of the CO2 storage project. Therefore, this study aims to build the 3D model under geological uncertainties for enhancing CO2 storage capacity in the Shahejie Formation (Es1), Nv32 block, China. The well logs, seismic data, and geological data were used for the construction of 3-D petrophysical models. The target study area model focused on four units (Es1 × 1, Es1 × 2, Es1 × 3, and Es1 × 4) in the Shahejie Formation. Well logs were utilized to predict petrophysical properties; the lithofacies indicated that the Shahejie Formation units are sandstone, shale, and limestone. Also, the petrophysical interpretation demonstrated that the Es1 reservoir exhibited high percentage porosity, permeability, and medium to high net-to-gross ratios. The static model showed that there are lateral heterogeneities in the reservoir properties and lithofacies; optimal reservoir rocks exist in Es1 × 4, Es1 × 3, and Es1 × 2 units. Moreover, the pore volume of the Es1 unit was estimated from petrophysical property models, ranging between 0.554369 and 10.03771 × 106 sm3, with a total volumetric value of 20.0819 × 106 sm3 for the four reservoir units. Then, the 100–400 realizations were generated for the pore volume uncertainties assessment. In consequence, 200 realizations were determined as an optimal solution for capturing geological uncertainties. The estimation of CO2 storage capacity in the Es1 formation ranged from 15.6 to 207.9 × 109 t. This result suggests the potential of CO2 geological storage in the Shahejie Formation, China.

CO2 storage capacity of anthracite coal in deep burial depth conditions and its potential uncertainty analysis: a case study of the No. 3 coal seam in the Zhengzhuang Block in Qinshui Basin, China

The storage of CO2 in deep unminable coal seams can mitigate greenhouse gas emissions. However, CO2 storage in deep anthracite coal is complex with some uncertainties in the estimation of CO2 storage capacity. Based on isothermal adsorption experiments and gas solubility experiments under high temperature and pressure conditions, the total storage capacity of CO2 in anthracite coal is discussed. The results show that the absolute adsorption amount is over 44 cm3/g at temperatures of 318.15, 335.65, and 353.15 K as well as adsorption equilibrium pressures of 10 MPa. The storage capacity of adsorbed and free gas is 35–70 cm3/g and 5–8 cm3/g, respectively, within a depth range of 1000–2000 m. The soluble gas can be ignored for its low content between 0.22 cm3/g and 0.28 cm3/g with a proportion of less than 1%. The storage capacity of CO2 may be estimated inaccurately because of the heterogeneity and uncertainty of the macroscopic geological conditions and coal reservoir parameters. Taking the No. 3 coal seam in Zhengzhuang block as an example, the storage priority area was divided into supercritical area and subcritical area with five sub-areas according to storage conditions, and the storage capacity was calculated, showing a relatively good storage potential.

Reaction of drilled-cores from the Janggi basin with CO2-saturated brine from subcritical to supercritical condition of CO2: Implications on sequestration of dissolved CO2

The CO2-brine-core reaction was studied to provide information for geological CO2 sequestration in the Janggi basin. Three drilled-core samples (two caprocks and one reservoir rock) at different depths in the basin were used for the reactions under subcritical and supercritical conditions of CO2 (10 bar–170 bar at 40 °C). Due to the dissolution of various ions from the cores during the reactions, the ion composition and concentration were changed in the brine, causing the experimentally determined solubility of CO2 in brine to change. Therefore, the change in the solubility of CO2 in brine was affected by the type of core and pressure. In addition, to simulate the effect of an additive on the CO2 solubility, alkyl-olefin sulfonate (AOS; 1 wt%), which is widely used for CO2 enhanced oil recovery (CO2-EOR), was added to the CO2-brine-reservoir rock reaction system. The addition of the surfactant contributed to improving the solubility of CO2 mainly in the high-pressure region. The change in the textural structure (mesopore and micropore) and chemical composition of core were also observed in nano-scale aspects despite the short experimental period (12 days). The introduction of AOS reduced the nano-scale structural change of the reservoir rock. The results in brine and cores can contribute to improving the understanding of CO2-brine-core reactions, because more accurate estimation of CO2 storage capacity after reactions can be feasible in designing and operating CO2 sequestration.

Estimation of CO2 Storage Capacity in a Depleted Gas Field on the Korea Continental Shelf

Estimation of CO2 Storage Capacity in a Depleted Gas Field on the Korea Continental Shelf

CO2 Sequestration-EOR in a Tight Oil Reservoir: Estimation of Dynamic CO2 Storage Capacity Using a Two-Stage Well Test

Evaluation of an accurate CO2 dynamic storage capacity, ultimate recycled CO2 and enhanced oil recovery (EOR) are key factors for a successful CO2 EOR project. The Yanchang Petroleum Company (YP)’s low permeability oil field is located at Ordos Basin - China with a very short and inefficient primary and secondary oil recovery and, therefore, YP proposed CO2 EOR as a potential tertiary oil recovery approach. In this work, the Wuqi reservoir in the Yanchang field is selected to evaluate the feasibility of full-field CO2 sequestration-EOR. The Wuqi reservoir has been in production for over a decade with historical data that can be used for a history matching process. To acquire essential dynamic data for evaluation of the CO2 injectivity/dynamic storage capacity, a specific two-stage pilot well test is proposed to inject first water and then CO2. It will provide relatively accurate calculated permeability for water (test phase 1) and CO2 (test phase 2) at the injection well. Also, the test will qualitatively estimate the location of water and CO2 fronts in the reservoir over time. Using two monitoring wells simultaneously, significantly increases the radius of investigation (ROI) that can be achieved for a given injection scenario and will also describe directional heterogeneity in the reservoir. When informed by the pilot test data, the model can be used to estimate the CO2 injection rate, ultimate cumulative CO2 injection and oil production and CO2 injection well numbers over 15 years of CO2 sequestration-EOR, which can be utilised for further techno-economic analysis of the project.

Estimation of Utsira CO2 Storage Capacity Based on Water Producing Modelling and Identification of Proper Water Producer Architecture

Utsira aquifer is well known from the CCS community as Sleipner gas project is storing CO2 in that aquifer since 1996. More than 17 million tons of CO2 have been injected to date. According to previous studies, CO2 storage capacity of the Utsira varies between 0.3 and 50.4 Gt. In this study, assuming specific parameters, the storage capacity is estimated about 1.7 Gt using analytical method. A full scale flow model of the aquifer has been used to model CO2 storage, considering CO2 migration and pressure raise to estimate the CO2 storage capacity, with or without water production. Water-CO2 relative permeabilities are selected based on a vertical equilibrium approach and validated when CO2 migration is compared to high resolution grid refinement around the injector areas. Optimizing injector well locations lead to an estimation of CO2 storage capacity of about 1.6 Gt without water production. This capacity can be increased to 3 Gt with about 1 Gt of formation water being produced during injection. The location and architecture of the water production wells were optimized: the wells should be subsea and should be operated with minimal requirement. Two production methods were compared: eruptive wells, producing water based on the formation overpressure induced by the CO2 storage; and activated wells using electrical submersible pumps (ESP). For each scenario, an optimization is proposed in terms of well count, well locations and well architecture designs. For the reservoir depth ranging between 500–1200 m below sea level and for such a high water production rate, the electrical submersible pumps (ESP) technology is a suitable application.

Incorporation of multi-phase solubility and molecular diffusion in a geochemical evaluation of the CO2 huff-n-puff process in liquid-rich shale reservoirs

Despite the development of horizontal well and hydraulic fracturing technologies, natural depletion is limited in low productivity, and thereby considerable hydrocarbon remains in low permeable shale reservoirs. Recent researches proved that the deployment of CO2 huff-puff process could extract the remained hydrocarbon. They quantified various mechanisms behind the process and proposed the potential for CO2 sequestration in the shale formation. However, thorough understanding of fluid transport in the CO2 huff-n-puff process has not been completed due to complexity in tight shale formations. They had a lack to analyze potential factors affecting fluid flow in the system of oil/CO2/brine/shale formation: 1) aqueous solubility; 2) molecular diffusion in aqueous and oleic phases; and 3) geochemistry. Therefore, this study diagnoses the potential factors affecting fluid flow during CO2 huff-n-puff process in the shale oil reservoirs. Then, their effects are quantified by analyzing shale oil recovery and CO2 storage capacity.Since a fraction of injected CO2 dissolves in water and oil during the CO2 huff-n-puff process, transportability is acquired by molecular diffusion in aqueous and oleic phases. In addition, dissolution of CO2 changes the pH of in-situ brine, which is a sensitive factor in geochemistry, and thereby would change physical properties of formation. Implementing these mechanisms, this study simulates the CO2 huff-n-puff process in shale oil reservoirs. It is observed that effects of aqueous solubility and geochemistry decrease oil production by 3.2% and 6%, respectively. Approximately, up to 9.5% of CO2 to be injected is sequestrated in depleted shale formation via solubility mechanism. Molecular diffusion in oleic phase increases the oil production by 2%, but that in aqueous phase is negligible. For the accurate estimation of oil production and CO2 storage capacity in the simulation of CO2 huff-n-puff process for shale oil reservoir, the comprehensive model should consider potential factors such as aqueous solubility, molecular diffusion, and geochemical reactions. Because the potential factors have been neglected in the works of other types of shale reservoirs, the proposed approaches expect to expand our understanding in the CO2 injection to tight and shale gas/oil reservoirs.

CO2 storage capacity estimation through static reservoir modelling: A case study of the lower Cretaceous Gage Sandstone reservoir in the offshore Vlaming Sub-basin, Perth Basin, Australia

The Lower Cretaceous Gage Sandstone is a deep saline aquifer which is overlain by the regionally extensive Lower Cretaceous South Perth Shale seal in the offshore Vlaming Sub-basin, Perth Basin, Australia. This paper is focused on the CO2 storage capacity estimation in the Gage Sandstone reservoir by integrating both the well and seismic data. After a 3D grid system was constructed, well log interpretations, depth converted interval velocity and seismic relative acoustic impedance data were imported into the 3D grids. The volume fraction of shale was first constructed combining the neural networks modelling and residual stochastic simulation from the well and seismic attributes data. Porosity was modelled using sequential Gaussian co-simulation with the volume fraction of shale model. The CO2 storage capacity was estimated using the total pore volume and storage coefficients in the US-DOE methodology. The best estimate (P50) of carbon storage capacity in the Gage Sandstone reservoir is 493 million tonnes based on the static reservoir modelling.

CO2 sequestration-EOR in Yanchang oilfield, China: Estimation of CO2 storage capacity using a two-stage well test

Depleted oil fields are often considered as the first target for carbon geo-sequestration. However, evaluation of an accurate CO2 dynamic storage capacity, ultimate recycled CO2 and enhanced oil recovery (EOR) are key elements for a successful project. The Yanchang Petroleum Company (YP)’s oil field is located at Ordos Basin and it is the second largest low permeability oil field in China with a very short and inefficient primary and secondary oil recovery. Thus, CO2 EOR was considered by YP to be an appropriate tertiary oil recovery approach. In this work, the Wuqi reservoir in the Yanchang field was selected to study the feasibility of full-field CO2 sequestration with EOR. The Wuqi reservoir has been in production for over a decade and has historical data that can be history matched. To acquire essential dynamic data for evaluation of CO2 injectivity/dynamic storage capacity, a specific two-stage well test design is proposed to inject first water and then CO2. It will provide accurate effective permeability estimates for water (test phase 1) and CO2 (test phase 2) at the injection well. The test will also inform the operator on the location water and CO2 fronts in the reservoir. Using two monitoring wells simultaneously, significantly increases the radius of investigation (ROI) that can be achieved for a given pumping scenario and will also describe the reservoir heterogeneity.