Carbon dioxide (CO2) storage in deep saline aquifers is a vital option for CO2 mitigation at a large scale. Determining storage capacity is one of the crucial steps toward large-scale deployment of CO2 storage. Results of capacity assessments tend toward a consensus that sufficient resources are available in saline aquifers in many parts of the world. However, current CO2 capacity assessments involve significant inconsistencies and uncertainties caused by various technical assumptions, storage mechanisms considered, algorithms, and data types and resolutions. Furthermore, other constraint factors (such as techno-economic features, site suitability, risk, regulation, social-economic situation, and policies) significantly affect the storage capacity assessment results. Consequently, a consensus capacity classification system and assessment method should be capable of classifying the capacity type or even more related uncertainties. We present a hierarchical framework of CO2 capacity to define the capacity types based on the various factors, algorithms, and datasets. Finally, a review of onshore CO2 aquifer storage capacity assessments in China is presented as examples to illustrate the feasibility of the proposed hierarchical framework.
CO2 foam fracturing fluid is widely used in unconventional oil and gas production because of its easy flowback and low damage to the reservoir. Nowadays, the fracturing process of CO2 foam fracturing fluid injected by coiled tubing is widely used. However, the small diameter of coiled tubing will cause a large frictional pressure loss in the process of fluid flow, which is not beneficial to the development of fracturing construction. In this paper, the temperature and pressure calculation model of gas, liquid, and solid three-phase fluid flow in the wellbore under annulus injection is established. The model accuracy is verified by comparing the calculation results with the existing gas, solid, and gas and liquid two-phase model of CO2 fracturing. The calculation case of this paper shows that compared with the tubing injection method, the annulus injection of CO2 foam fracturing fluid reduces the friction by 3.06 MPa, and increases the wellbore pressure and temperature by 3.06 MPa and 5.77°C, respectively. Increasing the injection temperature, proppant volumetric concentration, and foam quality will increase the wellbore fluid temperature and make the CO2 transition to the supercritical state while increasing the mass flow rate will do the opposite. The research results verify the feasibility of the annulus injection of CO2 foam fracturing fluid and provide a reference for the improvement of CO2 foam fracturing technology in the field.
A numerical reaction-transport model was developed to simulate the effects of microbial activity and mineral reactions on the composition of porewater in a 230-m-thick Pleistocene interval drilled in the Peru-Chile Trench (Ocean Drilling Program, Site 1230). This site has porewater profiles similar to those along many continental margins, where intense methanogenesis occurs and alkalinity surpasses 100 mmol/L. Simulations show that microbial sulphate reduction, anaerobic oxidation of methane, and ammonium release from organic matter degradation only account for parts of total alkalinity, and excess CO2 produced during methanogenesis leads to acidification of porewater. Additional alkalinity is produced by slow alteration of primary aluminosilicate minerals to kaolinite and SiO2. Overall, alkalinity production in the methanogenic zone is sufficient to prevent dissolution of carbonate minerals; indeed, it contributes to the formation of cemented carbonate layers at a supersaturation front near the sulphate-methane transition zone. Within the methanogenic zone, carbonate formation is largely inhibited by cation diffusion but occurs rapidly if cations are transported into the zone via fluid conduits, such as faults. The simulation presented here provides fundamental insight into the diagenetic effects of the deep biosphere and may also be applicable for the long-term prediction of the stability and safety of deep CO2 storage reservoirs.
Equilibration times of dissolved inorganic carbon (DIC) depend on conversion reactions between CO2(aq) and the dissociation products of carbonic acid [S = (H2CO3) + (HCO3−) + (CO32−)]. Here, we develop analytical equations and a numerical model to calculate chemical equilibration times of DIC during pH transitions in buffered and unbuffered solutions. We approximate the equilibration degree of the DIC reservoir by the smaller of the CO2(aq) and S pools at the new pH, since the smaller pool is always farther from equilibrium during the chemical evolution. Both the amount of DIC converted and the rate of conversion differ between a pH increase and decrease, leading to distinct equilibration times for these general cases. Alkalinity perturbations in unbuffered solutions initially drive pH overshoots (increase or decrease) relative to the new equilibrium pH. The increased rates of DIC conversion associated with the pH overshoot yield shorter equilibration times compared to buffered solutions. Salinity has opposing effects on buffered and unbuffered solutions, decreasing and increasing equilibration times, respectively.
In present paper, the mineral and fluid compositions of shale oil from the Songliao Basin are analyzed systematically using core samples, X-ray diffractometer (XRD), and gas chromatography (GC). The effects of shale mineral composition, pore size, temperature, and pressure on the mass density of the adsorbed layers are then studied utilizing molecular dynamics simulation. The results show that illite and quartz are predominant in the micro petrological components of the shale, and nC19 is the main carbon peak. The fluid consists primarily of n-alkane molecules, and nC19 is found to be representative of the shale oil composition. Moreover, the adsorbing effect of quartz-illite mixed wall is between that of a pure mineral wall (illite and quartz), indicating that the selection of a mixed wall is similar to the actual shale composition. If the pores are inorganic, the minimum pore size of only adsorption oil is smaller than the organic pores. The critical adsorption point of shale oil in inorganic pores is less than 3.2 nm. Furthermore, compared to pressure, the temperature has a more significant effect on fluid adsorption due to the correlation with the kinetic energy of alkane molecules. This research shows the oil occurrence status in inorganic matter nanopore with a mixed solid wall, and provides theoretical support for shale oil exploration.
The creep slope is a dynamic development process, from stable deformation to instability failure. For the slope with sliding zone, it generally creeps along the sliding zone. If the sliding zone controlling the slope sliding does not have obvious displacement, and the slope has unexpected instability without warning, the harm and potential safety hazard are often much greater than the visible creep. Studying the development trend of this kind of landslide is of great significance to slope treatment and landslide early warning. Taking Xiashan village landslide in Huishan Town, Xinchang County, Zhejiang Province as an example, the landslide point was determined by numerical simulation in 2006. Generally, the landslide is a typical long-term slow deformation towards the free direction. Based on a new round of investigation and monitoring, this paper shows that there are signs of creeping on the surface of the landslide since 2003, and there is no creep on the deep sliding surface. The joint fissures in the landslide area are relatively developed, and rainfall infiltration will soften the soft rock and soil layer and greatly reduce its stability. This paper collects and arranges the rainfall data of the landslide area in recent 30 years, constructs the slope finite element model considering rainfall conditions through ANSYS finite element software, and carries out numerical simulation stability analysis. The results show that if cracks appear below or above the slope’s sliding surface, or are artificially damaged, the sliding surface may develop into weak cracks. Then, the plastic zone of penetration is offset; In the case of heavy rain, the slope can unload itself under the action of rainfall. At this time, the slope was unstable and the landslide happened suddenly.
A new gravimetric geoid model, the KW-FLGM2021, is developed for Kuwait in this study. This new geoid model is driven by a combination of the XGM2019e-combined global geopotential model (GGM), terrestrial gravity, and the SRTM 3 global digital elevation model with a spatial resolution of three arc seconds. The KW-FLGM2021 has been computed by using the technique of Least Squares Collocation (LSC) with Remove-Compute-Restore (RCR) procedure. To evaluate the external accuracy of the KW-FLGM2021 gravimetric geoid model, GPS/leveling data were used. As a result of this evaluation, the residual of geoid heights obtained from the KW-FLGM2021 geoid model is 2.2 cm. The KW-FLGM2021 is possible to be recommended as the first accurate geoid model for Kuwait.
Recoverable geothermal resources are very important for geothermal development and utilization. Generally, the recovery factor is a measure of available geothermal resources in a geothermal field. However, it has been a pre-determined ratio in practice and sustainable utilization of geothermal resources was not considered in the previous calculation of recoverable resources. In this work, we have attempted to develop a method to calculate recoverable geothermal resources based on a numerical thermo-hydraulic coupled modeling of a geothermal reservoir under exploitation, with an assumption of sustainability. Taking a geothermal reservoir as an example, we demonstrate the effectiveness of the method. The recoverable geothermal resources are 6.85 × 1018 J assuming a lifetime of 100 years in a well doublet pattern for geothermal heating. We further discuss the influence of well spacing on the recoverable resources. It is found that 600 m is the optimal well spacing with maximum extracted energy that conforms to the limit of the pressure drop and no temperature drop in the production well. Under the uniform well distribution pattern for sustainable exploitation, the recovery factor is 26.2%, which is higher than the previous value of 15% when depending only on lithology. The proposed method for calculating the recoverable geothermal resources is instructive for making decisions for sustainable exploitation.
Correlations of rock-physics model inputs are important to know to help design informative prior models within integrated reservoir-characterization workflows. A Bayesian framework is optimal to determine such correlations. Within that framework, we use velocity and porosity measurements on unconsolidated, dry, and clean sands. Three pressure- and three porosity-dependent rock-physics models are applied to the data to examine relationships among the inputs. As with any Bayesian formulation, we define a prior model and calculate the likelihood in order to evaluate the posterior. With relatively few inputs to consider for each rock-physics model, we found that sampling the posterior exhaustively to be convenient. The results of the Bayesian analyses are multivariate histograms that indicate most likely values of the input parameters given the data to which the rock-physics model was fit. When the Bayesian procedure is repeated many times for the same data, but with different prior models, correlations emerged among the input parameters in a rock-physics model. These correlations were not known previously. Implications, for the pressure- and porosity-dependent models examined here, are that these correlations should be utilized when applying these models to other relevant data sets. Furthermore, additional rock-physics models should be examined similarly to determine any potential correlations in their inputs. These correlations can then be taken advantage of in forward and inverse problems posed in reservoir characterization.
Probabilistic hazard assessments for studying overland pyroclastic flows or atmospheric ash clouds under short timelines of an evolving crisis, require using the best science available unhampered by complicated and slow manual workflows. Although deterministic mathematical models are available, in most cases, parameters and initial conditions for the equations are usually only known within a prescribed range of uncertainty. For the construction of probabilistic hazard assessments, accurate outputs and propagation of the inherent input uncertainty to quantities of interest are needed to estimate necessary probabilities based on numerous runs of the underlying deterministic model. Characterizing the uncertainty in system states due to parametric and input uncertainty, simultaneously, requires using ensemble based methods to explore the full parameter and input spaces. Complex tasks, such as running thousands of instances of a deterministic model with parameter and input uncertainty require a High Performance Computing infrastructure and skilled personnel that may not be readily available to the policy makers responsible for making informed risk mitigation decisions. For efficiency, programming tasks required for executing ensemble simulations need to run in parallel, leading to twin computational challenges of managing large amounts of data and performing CPU intensive processing. The resulting flow of work requires complex sequences of tasks, interactions, and exchanges of data, hence the automatic management of these workflows are essential. Here we discuss a computer infrastructure, methodology and tools which enable scientists and other members of the volcanology research community to develop workflows for construction of probabilistic hazard maps using remotely accessed computing through a web portal.