Injection Enhanced Oil Recovery Research Articles

Mechanism and destruction status of CO2 BLEVE during CO2 geological storage and enhanced oil recovery injection process

In CO2-oil recovery enhancement technology, the occurrence of a Boiling Liquid Expansion Vapor Explosion (BLEVE) can result in dangerous events that endanger the lives and health of workers, while also leading to significant economic losses. This happens when there is an excessive injection concentration and volume of CO2, coupled with container defects. To address the limited research on the mechanism and destruction of BLEVE, this study conducts experiments to explore these issues. The experimental results reveal that the bursting piece ruptures at a temperature of 36 °C, and the specimen explodes when the pressure intensity exceeds the residual strength of the specimen, reaching 69.97 MPa. The findings indicate that parameters, such as initial pressure, initial temperature, and failure pressure, can impact the risk of CO2 BLEVE occurrence and the propagation of explosion shock waves. The pressure inside the container during the BLEVE process fluctuates due to the joint action of the leakage rate and gasification rate of liquid CO2. This research provides a framework for evaluating the risk of CO2 BLEVE during CO2 geological storage and enhanced oil recovery injection processes, offering theoretical support for BLEVE prevention and control.

Importance of critical point for the phase behavior of a reservoir fluid

It is a fundamental assumption behind a cubic equation of state that the phase behavior of a pure component can be expressed in terms of its critical temperature and pressure. This paper shows that the location of the critical point also for multicomponent reservoir fluids influences the phase behavior throughout the gas and liquid region. An equation of state model that matches the critical point and the saturation pressure at the reservoir temperature is likely to provide a good match of the phase behavior of a reservoir fluid at all conditions experienced during oil and gas production. An experimental critical point is seldom available for a reservoir fluid but the critical point can be estimated from correlations in the molar ratio of C7+ and lighter hydrocarbons. When PVT data exists, such estimated critical point can be used as an extra datapoint when assigning critical properties to an equation of state model. This is particularly useful as a constraint when the equation of state is to be used for gas injection enhanced oil recovery calculations. When the available PVT data is limited to a saturation point at the reservoir temperature, a reliable equation of state model can be developed by only tuning to the saturation pressure and the estimated critical point. The presented method is applicable to reservoir oils and gas condensates with a C7+ mole% of at least 10.

Impact of gas composition and reservoir heterogeneity on miscible sour gas flooding — A simulation study

Proper handling of the produced sour gas is a big challenge for operating companies due to the serious environmental and technical problems caused by H2S and CO2. The reinjection of the produced sour gas into oil reservoirs is an environmentally friendly as well as an economically attractive method due to the low investment cost and incremental oil recovery. However, the sour gas injection for enhanced oil recovery (EOR) is a relatively new approach with numerous uncovered perspectives, especially in a heterogeneous reservoir. The objective of this study is to investigate the effect of gas composition and reservoir heterogeneity on the miscible displacement of reservoir oil using sour gas.The reservoir oil consisting of 15 mol% H2S and 4 mol% CO2 from an oilfield in the North Caspian region was used. First, the phase behavior alteration of reservoir oil due to the injection of various gases, namely H2S, CO2, CH4, acid, and sour gas was analyzed. Then, the effect of gas type on minimum miscibility pressure (MMP) was investigated based on a semi-analytical tie-line method. Moreover, 2D and 3D numerical simulations were conducted to understand the oil recovery performance of various gas injection options and the effect of permeability heterogeneity on sour gas flooding efficiency. The findings showed that higher H2S content in the injected gas narrows the two-phase envelope and decreases the bubble point pressure. Moreover, it was observed that MMP decreases with increasing H2S concentration, which provides a favorable condition for achieving miscibility. Additionally, an increase in H2S concentration in sour gas improves its oil recovery efficiency by extending gas breakthrough time and elongating the plateau period of oil rate. These results are useful for designing, optimizing, and implementing sour gas injection for EOR in oil reservoirs that have access to sour gas sources.

Investigating Enhanced Oil Recovery in Unconventional Reservoirs Based on Field Case Review, Laboratory, and Simulation Studies

Aimed at advancing gas injection enhanced oil recovery (EOR) technologies in unconventional reservoirs, this study comprised a series of activities to bridge the gap between the theoretical study and actual field applications. Twenty-four EOR pilot tests were collected from the major unconventional plays in North America to evaluate the performance of different EOR technologies. Fit-for-purpose experiments and simulations were performed to investigate the effects of injection rate and pressure on EOR performance, as well as to reveal the effectiveness of huff “n” puff (HnP) cycles in actual field operations. The selection of injection rate and pressure as key parameters for investigation was based on field observations and communications with oil and gas operators because these two parameters play critical roles in both facility design and overall cost for an EOR project. Results showed that miscible EOR with a high gas injection rate and pressure is required for field operations because the injected gas needs to penetrate and extract oil from the tight matrix. Experimental results indicated that there is a correlation between oil recovery and the logarithm of core volume for miscible EOR. Immiscible gas EOR could not yield a satisfactory EOR response in actual reservoirs because the injected gas tends to flow through fractures instead of penetrating the matrix to interact with oil. Results also showed that reaching minimum miscibility pressure (MMP) does not guarantee an optimum EOR operation in unconventional reservoirs. Pressure higher than MMP is preferred in field operations. When designed properly, up to a tenfold oil production rate boost is achievable in field applications within a short period. However, such a high-performance operation is only effective in the first several HnP cycles due to the limited gas penetration depth into the rock matrix.

Case Study: Mature Wells Given New, Carbon-Storage Purpose With Subsurface Data

To ensure success in exploration and production activities, oil and gas companies rely on subsurface data to gain insights that guide operational decisions over the life of their wells. But as wells near the end of their lives and production slows or stops, wells are subsequently shut and abandoned, and the accompanying subsurface data are set aside. However, these data still hold tremendous value when it comes to evaluating mature, near-end-of-life wells and fields to determine if they are suitable candidates for carbon capture, utilization, and storage (CCUS). Reusing wells and fields for CO2 injection provides an opportunity to reduce the time and cost for developing new CCUS infrastructure required by energy mix diversification efforts while avoiding the steep expenses commonly associated with decommissioning. In most cases, when the production cycle ends and all usable hydrocarbons have been extracted, the topside facilities are dismantled, the wellbore is permanently plugged and abandoned, and the surrounding land or seabed is returned to its natural condition. Historically, this complex, multistep process has been a cost center for oil and gas businesses, requiring monumental investment that grows even higher for offshore and deepwater fields. However, now that the CCUS industry is aggressively expanding, operators are presented with the possibility of turning decommissioned wells into a profit center by selling CO2 storage capacity to others. CO2 storage is a crucial component of the CCUS value chain as permanently storing CO2 is the cornerstone of large-scale emissions reductions. The storage process entails capturing, compressing, and injecting CO2 into a reservoir of porous rock beneath an impermeable layer of caprock, which functions as a seal. The caprock prevents the CO2 from reaching the surface, as do other trapping mechanisms including structural, residual, solubility, and mineral trapping. As a result, CO2 is safely stored in geological formations. This is similar to the unexplored state of oil and gas reserves trapped underground for millions of years. Carbon-storage processes are not a new concept in the oil and gas industry. As part of normal well operations, operators routinely perform the CO2 injection enhanced oil recovery (EOR) technique. If CO2 returns to the surface and is separated and then reinjected to form a closed loop when utilizing this EOR method, this results in permanent CO2 storage, which strongly supports the viability for repurposing mature decommissioned wells. In response to growing interest in CCUS and governments worldwide committing to reach a net-zero target for CO2 emissions in the coming decades, a consortium of 20 organizations including research institutions, operators, and regulatory authorities joined together to create REX-CO2 (ReUsing Existing Wells for CO2 Capture and Storage). As part of the REX-CO2 consortium, Ikon Science collaborated with the British Geological Survey (BGS) in the phases of a study that evaluated the potential for well reuse in the UK Continental Shelf (UKCS). It’s forecast that 1,211 wells across 230 fields will be decommissioned through 2028 in the UKCS to the tune of $60 billion, according to Britain’s Oil & Gas Authority’s 2021 Decommissioning Cost Estimate report.

Experimental study on the evaluation of surfactant/polymer flooding for enhancing oil recovery in Kumkol Oil Field

Chemical enhanced oil recovery (EOR) methods are shown to sweep the residual oil by altering physical properties of fluids after waterflooding to improve oil recovery. This work presents an experimental study on the surfactant/polymer injection for EOR in sandstone reservoirs. Interfacial tension measurements, emulsification and rheology tests are performed to select the best candidates from thirteen commercial surfactants and five commercial polymers. The performance of the preferred surfactant and polymer candidates in EOR is evaluated through a series of core flooding experiments on both homogeneous and heterogenous sand packs. Different injection schemes are investigated. The results show that the polymer injection and polymer-surfactant-mixture slug can effectively displace the residual oil as the polymer injection improves efficiency of the sweeping front. Core flooding experiments on the heterogenous sand pack show that injecting polymer in the first, followed by surfactant slug yields the better performance compared with combined polymer-surfactant-mixture injection as the polymer pre-flush improves the vertical conformance of the surfactant solution and the final recovery.

Experimental evaluation of enhanced oil recovery in unconventional reservoirs using cyclic hydrocarbon gas injection

The significant amount of gas produced from unconventional reservoirs in the US in recent years has reduced market prices for hydrocarbon gas and created an opportunity for using low-cost gas in enhanced oil recovery (EOR) projects. In addition to its availability in large quantities and at low cost, injecting produced gas back into the reservoir prevents flaring the gas, reducing environmental concerns associated with greenhouse gas emissions to the atmosphere. Furthermore, while CO2 has shown tremendous success as an EOR injectant in huff-and-puff operations in tight liquid-rich shales, the lack of sufficient pipeline infrastructure supplying low-cost CO2 as well as operational issues (e.g., corrosion) has forced field operators to consider other gas options, such as produced gas, to substitute for or mix with CO2.While limited, experimental and numerical studies conducted on produced gas huff-and-puff in unconventional resources have shown promising results and highlighted the great potential of this technique for enhanced oil recovery from ultra-tight shale resources. The objective of the current work is to investigate the feasibility of produced gas huff-and-puff operations in one of the major oil-producing shale formations in North America further by performing several flow experiments using various mixtures of hydrocarbon gases. Three reservoir-condition core-flooding experiments are carefully designed and executed on shale core plugs in the absence and presence of proppant-filled fractures. After establishing initial two-phase brine-oil conditions in the core samples, hydrocarbon gas is injected into the medium through a huff-and-puff approach. The cycle of injection-soaking-production is repeated multiple times in each experiment. The results show that the use of hydrocarbon gas in huff-and-puff operations has great potential similar to CO2 for enhanced oil recovery from tight shale rocks and can lead to remarkable oil recovery. The hydrocarbon gas mixture in the fracture penetrates the matrix due to pressure and concentration gradients during the injection and soaking periods and forces the oil to leave the matrix during the depressurization process. It is observed that the rate of oil production is high in the first cycle and decreases in subsequent cycles as the rate of mass transfer and the amount of oil remaining in the matrix decrease. The average oil production due to the cyclic gas injection process in an intact and fractured composite rock sample was more than 48 and 21%, respectively. The results show that even though the ultratight formations could be heavily fractured, a proper cyclic gas injection EOR scheme could potentially improve oil recovery from the shale oil reservoirs, significantly.

A novel correlation for modeling interfacial tension in binary mixtures of CH₄, CO₂, and N₂ + normal alkanes systems: Application to gas injection EOR process

The Enhanced Oil Recovery (EOR) has received significant attention in recent years by the cessation of primary production of several reservoirs and also the increasing global demand for energy. Miscible gas flooding is one of the most popular EOR techniques. Interfacial Tension (IFT) data plays an important role in determining Minimum Miscibility Pressure (MMP) as well as estimating the recovery performance of the EOR schemes, and the production potential of fractured reservoirs. CH₄, CO₂, and N₂ are the gases widely used for gas injection EOR practices. Normal alkanes can represent the real crude oil samples as they are their most abundant constituents. Acquiring knowledge about the IFT between vapor phase and n-alkanes can shed light on the governing mechanisms between the injected gas phase and the real crude oil in EOR projects. Experimental determination of IFT is often associated with the high cost and arduous and timely procedures. The theoretical works need expensive numerical and computational effort. Data-based methods can offer a promising alternative to compensate for the disadvantages of the mentioned methods. An extensive database including 606, 1131, and 469 data samples of IFT between normal n-alkanes and CH₄, CO₂, and N₂ was utilized in this study to develop predictive models. Proper input variables were analyzed and selected for modeling. The Group Method of Data Handling (GMDH) was used in this study. Separate models were developed for the three vapor phases. The Root Mean Square Errors (RMSE) of 1.24, 1.29, and 1.15 mN/m for respective CH₄, CO₂, and N₂ systems indicate the acceptable accuracy of the developed model. The models were compared with the models available in the literature. It was revealed that the proposed GMDH models provide superior predictions for a wide range of pressure and temperature. External validation was performed using a very recently published dataset to check for the generality of the proposed models. Finally, a systematic method was proposed to select the best predictive model based on the n-alkane type and operational parameters of pressure and temperature. The findings of this study can be utilized in designing and planning efficient EOR schemes.

Robust Value Quantification of Enhanced Oil Recovery Methods Using Ensemble-Based Optimization

Summary Over the last decades, the development of different oil reservoirs with gas or chemical enhanced oil recovery (EOR) methods have been studied, and the EOR effects of the recovery methods are found to be sensitive to fluid and rock properties in the reservoirs. The use of a single reservoir model with the assumption of known reservoir parameters is not enough to guarantee an accurate prediction of EOR effects. The best decision related to the injection strategies of EOR methods can be appropriately found using an optimization setup that accounts for the uncertainty quantification in the reservoir. In this paper, we present mathematical tools for optimizing and ranking the value of the commonly used EOR methods. The methodology is demonstrated with Smartwater, carbon dioxide (CO2), and polymer EOR methods on synthetic 2D and 3D oil reservoirs. To capture the uncertainties in the reservoirs, we use an ensemble of geological realizations obtained by engineering upscaling of the initial model. The usefulness of this study is to improve the understanding of the actual benefit of EOR methods and to provide a methodology that quickly allows users to appropriately predict EOR injection strategies that maximize the annually discounted economic values of the injected and production data. The control variables of optimization problems include EOR gas rate or chemical concentration, water rates, oil rate, or bottomhole pressures. An ensemble-based optimization method with covariance adaptation is used to solve the optimization problem. For the different reservoirs considered, we find the optimal well controls for EOR methods. A comparative study of the economic benefits of the optimal solutions of EOR methods using optimized waterflooding as a reference point is presented. CO2 is found to rank high compared with other EOR methods in both cases. Finally, we investigate the effect of different injection costs of CO2 on the optimization results of CO2 EOR methods for the 3D reservoir field.

Optimization of Water-Alternating-CO2 Injection Field Operations Using a Machine-Learning-Assisted Workflow

Summary This paper will present a robust workflow to address multiobjective optimization (MOO) of carbon dioxide (CO2)-enhanced oil recovery (EOR)-sequestration projects with a large number of operational control parameters. Farnsworth unit (FWU) field, a mature oil reservoir undergoing CO2 alternating water injection (CO2-WAG) EOR, will be used as a field case to validate the proposed optimization protocol. The expected outcome of this work would be a repository of Pareto-optimal solutions of multiple objective functions, including oil recovery, carbon storage volume, and project economics. FWU’s numerical model is used to demonstrate the proposed optimization workflow. Because using MOO requires computationally intensive procedures, machine-learning-based proxies are introduced to substitute for the high-fidelity model, thus reducing the total computation overhead. The vector machine regression combined with the Gaussian kernel (Gaussian-SVR) is used to construct proxies. An iterative self-adjusting process prepares the training knowledge base to develop robust proxies and minimizes computational time. The proxies’ hyperparameters will be optimally designed using Bayesian optimization to achieve better generalization performance. Trained proxies will be coupled with multiobjective particle swarm Optimization (MOPSO) protocol to construct the Pareto-front solution repository. The outcomes of this workflow will be a repository containing Pareto-optimal solutions of multiple objectives considered in the CO2-WAG project. The proposed optimization workflow will be compared with another established methodology using a multilayer neural network (MLNN) to validate its feasibility in handling MOO with a large number of parameters to control. Optimization parameters used include operational variables that might be used to control the CO2-WAG process, such as the duration of the water/gas injection period, producer bottomhole pressure (BHP) control, and water injection rate of each well included in the numerical model. It is proved that the workflow coupling Gaussian-SVR proxies and the iterative self-adjusting protocol is more computationally efficient. The MOO process is made more rapid by squeezing the size of the required training knowledge base while maintaining the high accuracy of the optimized results. The outcomes of the optimization study show promising results in successfully establishing the solution repository considering multiple objective functions. Results are also verified by validating the Pareto fronts with simulation results using obtained optimized control parameters. The outcome from this work could provide field operators an opportunity to design a CO2-WAG project using as many inputs as possible from the reservoir models. The proposed work introduces a novel concept that couples Gaussian-SVR proxies with a self-adjusting protocol to increase the computational efficiency of the proposed workflow and to guarantee the high accuracy of the obtained optimized results. More importantly, the workflow can optimize a large number of control parameters used in a complex CO2-WAG process, which greatly extends its utility in solving large-scale MOO problems in various projects with similar desired outcomes.

The Effects of Co2 Injection Amount and Formation of In-Situ New Phase on Oil Phase Behavior During Co2 Injection Enhanced Oil Recovery (Eor) in Tight Oil Reservoirs

The Effects of Co2 Injection Amount and Formation of In-Situ New Phase on Oil Phase Behavior During Co2 Injection Enhanced Oil Recovery (Eor) in Tight Oil Reservoirs

Optimization of triple-alternating-gas (TAG) injection technique for enhanced oil recovery in tight oil reservoirs

After single-gas (SG) injection operations in tight oil reservoirs, a significant amount of oil is still unrecovered. To increase productivity, several sequencing gas injection techniques have been utilized. Given the scarcity of research on multiple-gas alternating injection schemes, this study propose an optimized triple-alternating-gas (TAG) injection for improved oil recovery. The performance of the TAG process was demonstrated through numerical simulations and comparative analysis. First, a reservoir compositional model is developed to establish the properties and composition of the tight oil reservoir; then, a suitable combination for the SG, double alternating gas (DAG), and TAG was selected via a comparative simulation process. Second, the TAG process was optimized and the best case parameters were derived. Finally, based on the oil recovery factors and sweep efficiencies, a comparative simulation for SG, DAG, and TAG was performed and the mechanisms explained. The following findings were made: (1) The DAG and TAG provided a higher recovery factor than the SG injection and based on recovery factor and economic advantages, CO2 + CH4 + H2S was the best choice for the TAG process. (2) The results of the sensitivity analysis showed that the critical optimization factors for a TAG injection scheme are the injection and the production pressures. (3) After optimization, the recovery factor and sweep efficiency of the TAG injection scheme were the best. This study promotes the understanding of multiple-gas injection enhanced oil recovery (EOR) and serves as a guide to field design of gas EOR techniques.

Enhancement of Heavy Oil Recovery with High CO2 Injection Rates in Silica Nanochannel

Abstract CO2 injection enhanced oil recovery has become one of the most important approaches to develop heavy oil from reservoirs. However, the microscopic displacement behavior of heavy oil in the nanochannel is still not fully understood. In this paper, we use CO2 as the displacing agent to investigate the displacement of heavy oil molecules confined between the hydroxylated silica nanochannel by nonequilibrium molecular dynamics simulations. We find that for heavy oil molecules, it requires more much higher displacing speed to fully dissipate the residual oil which is found related to the decreased CO2 adsorption on the silica nanochannel. A faster CO2 gas injection rate will lower the CO2 adsorption inside the nanochannel, and more CO2 will participate in the displacement of the heavy oil. The results from this work will enhance our understanding of the CO2 gas displacing heavy oil recovery and design guidelines for heavy oil recovery applications.

A New Effective Multiwalled Carbon Nanotube-Foam System for Mobility Control

SummaryNanoparticles have improved a surfactant's ability to create long-lasting foam. Recent studies have widely recommended the use of silica nanoparticles to enhance foam stability. This paper presents an experimental investigation of a new and highly effective alpha olefin sulfonate (AOS)–multiwalled carbon nanotube (MWCNT) system for mobility control during gas enhanced oil recovery (EOR) operations.The new AOS–MWCNT system was evaluated for its foam stability at 150°F using a high-pressure view cell. The MWCNT was obtained as solid particles of aspect ratio up to 100 and silica nanoparticles of median size of 118 nm. The foam system was optimized for its maximum half-life by varying the concentration of the AOS and the nanotube from 0.2 to 1% and 250 to 1,000 ppm, respectively. Compatibility testing with salts was done as well. Coreflood experiments with 1.5-in.-diameter, 6-in.-long Berea sandstone cores were run to calculate the mobility reduction factor at 150°F. Nitrogen foam was injected into the core at 80% foam quality in the tertiary recovery mode, and the pressure drop across the core was measured. The formation brine had a salinity of 5 wt% sodium chloride (NaCl), and the foaming solutions were prepared with 2 wt% NaCl.The optimal concentrations of the AOS solution and the nanotubes for maximum foam stability were determined to be 0.5% and 500 ppm, respectively. The optimized AOS–MWCNT system yielded 60% greater nitrogen foam half-life (32 minutes) than an optimized AOS–silica system at 150°F. The foam half-life of a stand-alone 0.5% AOS solution was 7 minutes. In the presence of crude oil, the foam half-life decreased for all the tested systems. Coreflood experiments at 150°F showed a significant increase in the mobility reduction factor when the new AOS–MWCNT system was used as the foamer instead of stand-alone AOS or AOS–silica system. The new foaming system was stable through the duration of the experiment, yielding foam in the effluent samples. There was no formation damage observed. Salt tolerance for the MWCNT nanofluid was higher than the silica nanofluid.Foam needs to be stable for long periods of time to ensure effective mobility control during gas injection for EOR. This paper investigates a new highly effective AOS-multiwalled carbon nanotube system that outperforms the AOS–silica foaming systems in terms of foam stability and mobility control at 150°F.

CFD Simulation of the Oil Displacement in Micromodel for Enhanced Oil Recovery Application

Diminishing hydrocarbon reserves in oil reservoirs and the need to sustain continuous oil production have prompted researchers to further investigate Enhanced Oil Recovery (EOR) techniques. Researchers also test run these processes before EOR fluid injection into the reservoir to maximise oil production whilst minimising reservoir damage and fluid loss. This study aims to simulate oil displacement during the injection of two different types of EOR injection fluid, namely of water and polymer, using a commercial CFD software known as ANSYS Fluent. A heterogeneous 2D micromodel that has randomised pore network was selected as the basis of the flow system. By doing so, it is hoped to replicate a reservoir prototype using an innovative approach in a 2D geometry that appropriately simplifies complex reservoir properties represented. Initially, micromodel is fully saturated with crude oil. Then, water and polymer are injected separately on a case-to-case basis at flowrate of 0.8 mL/min. Visual inspection of the phase fraction contour results found that polymer flooded micromodel had smaller regions of oil volume fraction as compared to that of water flooded micromodel. Polymer flooded micromodel also had smaller and more branched fingering front as compared to water flooded micromodel. The analysis found that polymer flooding had better oil displacement efficiency as compared to traditional water flooding due to higher mobility ratio, reduced viscous fingering and lower residual oil saturation.

Enhanced Oil Recovery in the Wolfcamp Shale by Carbon Dioxide or Nitrogen Injection: An Experimental Investigation

SummaryWe present a comprehensive investigation of gas injection for enhanced oil recovery (EOR) in organic-rich shale using 11 coreflooding experiments in sidewall core plugs from the Wolfcamp Shale, and three additional coreflooding experiments using Berea Sandstone. Our work studies the effect of pressure, minimum miscibility pressure (MMP), soak time, injection-gas composition, and rock-transport properties on oil-recovery factor. The injection gases were carbon dioxide (CO2) and nitrogen. The core plugs were resaturated with crude oil in the laboratory, and the experiments were performed at reservoir pressure and temperature using a design that closely replicates gas injection through a hydraulic fracture, minimizes convective flow, and exaggerates the fracture to the reservoir-rock ratio. We accomplished this by surrounding the Wolfcamp reservoir-rock matrix with glass beads. Computed-tomography (CT) scanning enabled the visualization of the compositional changes with time and space during the gas-injection experiments and gas chromatography provided the overall change in composition between the crude oil injected and the oil recovered.As gas surrounds the oil-saturated sample, a peripheral, slow-kinetics vaporization/condensation process is the main production mechanism. Gas flows preferentially through the proppant because of its high permeability, avoiding the formation and displacement of a miscible front along the rock matrix to mobilize the oil. Instead, the gas surrounding the reservoir-core sample vaporizes the light and intermediate components from the crude oil, making recovery a function of the fraction of oil that can be vaporized into the volume of gas in the fracture at the prevailing thermodynamic conditions. The mass transfer between the injected gas and the crude oil is sufficiently fast to result in significant oil production during the first 24 hours, but slow enough to cause the formation of a compositional gradient within the matrix that exists even 6 days after injection has started. The peripheral and the slow-kinetics aspects of the recovery mechanism are a consequence of the low fluid-transport capacity associated with the organic-rich shale that is saturated with liquid hydrocarbons.Our results show CO2 overperforms nitrogen as an EOR injection gas in organic-rich shale, and higher injection pressure leads to higher oil recovery, even beyond the MMP. The gas-injection scheme should allow enough time for the mass transfer to occur between the injected gas and the crude oil; we achieved this in the laboratory with a huff ’n’ puff scheme. Our results advance the understanding of gas injection for EOR in organic-rich shale in a laboratory scale, but additional work is required to rigorously scale up these observations to better design field applications.

Modified Peng-Robinson equation of state for CO2/hydrocarbon systems within nanopores

Phase behavior of confined fluid demonstrates significant deviation from that of bulk fluid because of the strong molecule-wall interaction and geometric constraint in confined space, resulting in the inapplicability of the classical cubic equation of state (EOS). The objective of this work is to modify the Peng-Robinson EOS (PR EOS) with respect to both the attractive parameter and the covolume term to reflect the impact of molecule-wall interaction and geometric constraint, respectively. The modified PR EOS is applied to compute the phase diagrams of CO2+n-C4H10 and CO2+n-C10H22 binary mixtures, CO2+n-C4H10+n-C10H22 ternary mixture, and CO2+Eagle Ford condensate in nanopores. In this work, correlations of both critical temperature and critical pressure shift with nanopore sizes are proposed to compute the confined attractive parameter and the confined covolume in the modified PR EOS. The proposed EOS model is validated by both the critical temperature and the critical pressure shift data collected from literature. Results demonstrate that confinement effect in nanopores impose an overall shrinkage to the two-phase diagrams of all the CO2-hydrocarbon systems. The upper dew-point pressure of the Eagle Ford condensate sample is calculated to be 2972.6 psi, with a suppression of 27.56% compared to the bulk value of 4103.6 psi. Moreover, the size of the two-phase region in the ternary diagram and the minimum miscibility pressure also decrease in confined space, which is in favor of the miscible gas injection enhanced oil recovery with a higher possibility of achieving first contact miscibility.

Interaction of low salinity surfactant nanofluids with carbonate surfaces and molecular level dynamics at fluid-fluid interface at ScCO2 loading

HypothesisThe advanced low salinity aqueous formulations are yet to be validated as an injection fluid for enhanced oil recovery (EOR) from the carbonate reservoirs and CO2 geosequestration. Interaction of various ionic species present in the novel low salinity surfactant nanofluids with scCO2/CO2 saturated aqueous phase interface and at the interface of CO2 saturated aqueous phase/mixed wet (with CO2 and Decane) limestone surface at the conditions of low salinity at reservoir conditions are to yet to be understood. ExperimentsThis study, carried out for the first time in low salinity at scCO2 loading conditions at 20 MPa pressure and 343 K temperature, comprises of wettability study of the limestone surface by aqueous phase contact angle measurements using ZrO2 nanoparticles (in the concentration range of 100–2000 mg/L) and 0.82 mM Hexadecyltrimethylammonium bromide (CTAB) surfactant. Molecular dynamics simulations results were used to understand the underlying mechanism of wettability alteration and interfacial tension (IFT) change. FindingsThis study reveals that a low dosage (100 mg/L) of ZrO2 nanoparticles forming ZrO2-CTAB nano-complexes helps in wettability alteration of the rock surface to more water-wetting state; certain ionic species augment this effect when used in appropriate concentration. Also, these nano-complexes helps in scCO2/CO2 saturated aqueous phase IFT reduction. This study can be used to design advanced low salinity injection fluids for water alternating gas injection for EOR and CO2 geosequestration projects.

CO2-prepad injection EOR simulation and sensitivity analysis considering miscibility and geomechanics in tight oil reservoirs

Injecting CO2 pre-pad into tight reservoirs before hydraulic fracturing is a promising way to improve the productivity of single well. In this method, CO2 should be injected into the formation at a high rate. Also the miscibility of CO2 and oil with the changes of intricate geomechanics during this process are complex. Meanwhile, the geological and operating parameters have a dramatic influence to oil production and is lack of systematic research. In this study, a fluid model of crude oil was established to evaluate the impact of CO2 on oil volume and viscosity. Then, a compositional numerical model coupled miscibility and geomechanics were set up to analyze enhanced oil recovery (EOR) potential under different miscible degree with in-situ stress field. Ultimately, in accordance with multiple nonlinear regression production forecast models, Sobol, FAST (Fourier Amplitude Sensitivity Test), and DGSM (derivation-based Global Sensitivity Measure) methods were utilized to study the main factors affecting cumulative production. The results shown that CO2 almost has the same effect on the volume of these tight oil and has the most significant effect on the viscosity of crude oil we studied by comparing. The production of miscible flooding is 38.2% and 16.4% higher than that of immiscible and near-miscible flooding, respectively. The formation were compacted during production especially in the early stage, hence the production of the model with geomechanics was 23.3% less than the model of non-geomechanics. The first-order sensitivity indexes of bottom-hole flow pressure, reservoir thickness and fracture conductivity are about 0.808, 0.176 and 0.004 respectively obtained by Sobol method, consistent with two other methods. This result shows that bottom-hole flow pressure, reservoir thickness and fracture conductivity are the most important factors affecting production, and bottom-hole flow pressure has the most significant impact on production. This work investigates how miscibility and geomechanics effect on production as well as clarified the factors affecting production for CO2 pre-pad injection, providing vital insights into operating in tight reservoirs for oil field.

A unified intelligent model for estimating the (gas + n-alkane) interfacial tension based on the eXtreme gradient boosting (XGBoost) trees

The interfacial tension (IFT) between the injecting gas and host oil is a key parameter that affects the ultimate displacement efficiency and gas injection enhanced oil recovery (EOR) performance. The accurate characterization of the IFT between varying n-alkanes and injecting gases is crucial to obtaining deeper insight into the predominating mechanisms behind the interfacial behaviors of (gas + oil) systems, and in turn ensuring the optimal design of gas injection EOR projects. Laboratory measurement of the IFT usually requires expensive experimental apparatus, time-consuming operation procedure and cumbersome data deduction. This paper proposed the use of a novel supervised learning (SL) method, namely the eXtreme gradient boosting (XGBoost) trees, for the fast estimation of (gas + n-alkane) IFT. A unified estimation model was constructed for varying injecting gas species and n-alkanes based on a large database consisting of a number of 1561 data sets. Results showed that the unified model is capable of accurately reproducing the experimental IFT based on pressure, temperature, n-alkane molecular weight and gas composition. It was also demonstrated that the new model outperforms the multi-layer perceptron (MLP), support vector regression (SVR) and existing correlations in terms of accuracy and robustness. Furthermore, the permutation importance (PI) was applied to quantify the importance of each input feature to the IFT, which concluded that the ranking of features in terms of decreasing importance to the (gas + n-alkane) IFT are: pressure ≫ n-alkane molecular weight > gas composition > temperature.