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Chemical flooding methods
Effective Cementing Solutions for CCS Wells is a half-day Training Course that will focus on the challenges of completing and cementing Carbon Capture and Storage wells. For CCS wells, the design should start with the completion size required to achieve the desired CO2 injection rate. Dual containment is essential; the second barrier must not only be designed for the corrosive environment but the second barrier and its associated equipment must be periodically inspected or tested. The differences between CCS wells and conventional oil and gas wells require a different approach to well design. If CCS wells were to be designed using established methods for oil and gas, the wells might fail to maintain integrity to prevent undetected migration of stored CO2.
Petroleum Engineering, University of Houston, 2. Metarock Laboratories, 3. Department of Earth and Atmospheric Sciences, University of Houston) 16:00-16:30 Break and Walk to Bizzell Museum 16:30-17:30 Tour: History of Science Collections, Bizzell Memorial Library, The University of Oklahoma 17:30-19:00 Networking Reception: Thurman J. White Forum Building
- Research Report > New Finding (0.93)
- Overview (0.68)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Mineral (0.72)
- Geology > Rock Type > Sedimentary Rock > Carbonate Rock (0.68)
- (2 more...)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (0.93)
The recent significant influx of large amounts of government incentives for a variety of green initiatives including CCS and CCUS has created a rush to drill and complete CO2 injection wells. However, the necessary corrosion data to make informed choices for corrosion resistance in these wells is minimal at best. Some oil and gas professionals have argued that there is no difference between the more than 40 years of petroleum experience with CO2 EOR and planned CCS wells. This comparison is not a valid one and can be risky considering the need for very long-term containment of CO2 required by regulators. This article presents a comparison between CO2 EOR and CCS for injection well metallurgy and explains why this comparison is invalid.
- Energy > Oil & Gas > Upstream (1.00)
- Government > Regional Government > North America Government > United States Government (0.33)
- North America > Canada > Saskatchewan > Williston Basin > Weyburn Field > Mission Canyon Formation (0.99)
- North America > Canada > Saskatchewan > Williston Basin > Weyburn Field > Madison Formation (0.99)
- North America > Canada > Saskatchewan > Williston Basin > Weyburn Field > Forbisher Formation (0.99)
- North America > Canada > Saskatchewan > Williston Basin > Weyburn Field > Charles Formation:Middale Formation (0.99)
- Well Completion > Well Integrity > Subsurface corrosion (tubing, casing, completion equipment, conductor) (1.00)
- Reservoir Description and Dynamics > Storage Reservoir Engineering > CO2 capture and sequestration (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)
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- Geology > Rock Type > Sedimentary Rock > Carbonate Rock (0.68)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (0.47)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (0.93)
The important role of optimized injection wells has been recognized as a crucial element of reservoir management for optimum field development. Over the years, diverse approaches have been deployed to optimize fluid conformance in injection wells to enhance the effectiveness of water/gas/polymer flooding, ultimately maximizing field recovery. The functionality of most applied technologies to provide optimum injection conformance has been limited as the properties of injection wells are continually changing. This article presents an overview of oilfield production data for using the first and only autonomous outflow control devices and demonstrates their benefit in various well-injection applications in the Middle East, Norway, North America, and China by optimizing well injectivity. Multiple surveillance data such as injection logging tool (ILT), distributed temperature sensing (DTS),and step-rate and injectivity test data have proven the success of FloFuse both in terms of achieving the target injection profile and controlling the thief zones.
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Waterflooding (1.00)
- Well Completion > Completion Monitoring Systems/Intelligent Wells > Flow control equipment (0.98)
- Production and Well Operations > Well & Reservoir Surveillance and Monitoring > Production logging (0.94)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (0.90)
On the Evaluation of Coal Strength Alteration Induced by CO2 Injection Using Advanced Black-Box and White-Box Machine Learning Algorithms
Lv, Qichao (National Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum (Beijing) (Corresponding author)) | Zheng, Haimin (Engneering & Design Deptment, CNOOC Research Institute Cooperation) | Li, Xiaochen (CNPC Bohai Drilling Engineering Company Limited) | Mohammadi, Mohammad-Reza (Department of Petroleum Engineering, Shahid Bahonar University of Kerman) | Hadavimoghaddam, Fahimeh (Ufa State Petroleum Technological University) | Zhou, Tongke (Department of Chemical Engineering, University of Manchester) | Mahmoudzadeh, Atena (Department of Petroleum Engineering, Shahid Bahonar University of Kerman) | Hemmati-Sarapardeh, Abdolhossein (Department of Petroleum Engineering, Shahid Bahonar University of Kerman (Corresponding author))
Summary The injection of carbon dioxide (CO2) into coal seams is a prominent technique that can provide carbon sequestration in addition to enhancing coalbed methane extraction. However, CO2 injection into the coal seams can alter the coal strength properties and their long-term integrity. In this work, the strength alteration of coals induced by CO2 exposure was modeled using 147 laboratory-measured unconfined compressive strength (UCS) data points and considering CO2 saturation pressure, CO2 interaction temperature, CO2 interaction time, and coal rank as input variables. Advanced white-box and black-box machine learning algorithms including Gaussian process regression (GPR) with rational quadratic kernel, extreme gradient boosting (XGBoost), categorical boosting (CatBoost), adaptive boosting decision tree (AdaBoost-DT), multivariate adaptive regression splines (MARS), K-nearest neighbor (KNN), gene expression programming (GEP), and group method of data handling (GMDH) were used in the modeling process. The results demonstrated that GPR-Rational Quadratic provided the most accurate estimates of UCS of coals having 3.53%, 3.62%, and 3.55% for the average absolute percent relative error (AAPRE) values of the train, test, and total data sets, respectively. Also, the overall determination coefficient (R) value of 0.9979 was additional proof of the excellent accuracy of this model compared with other models. Moreover, the first mathematical correlations to estimate the change in coal strength induced by CO2 exposure were established in this work by the GMDH and GEP algorithms with acceptable accuracy. Sensitivity analysis revealed that the Spearman correlation coefficient shows the relative importance of the input parameters on the coal strength better than the Pearson correlation coefficient. Among the inputs, coal rank had the greatest influence on the coal strength (strong nonlinear relationship) based on the Spearman correlation coefficient. After that, CO2 interaction time and CO2 saturation pressure have shown relatively strong nonlinear relationships with model output, respectively. The CO2 interaction temperature had the smallest impact on coal strength alteration induced by CO2 exposure based on both Pearson and Spearman correlation coefficients. Finally, the leverage technique revealed that the laboratory database used for modeling CO2-induced strength alteration of coals was highly reliable, and the suggested GPR-Rational Quadratic model and GMDH correlation could be applied for predicting the UCS of coals exposed to CO2 with high statistical accuracy and reliability.
- North America > United States (1.00)
- Asia > China (0.67)
- Europe > United Kingdom > England (0.28)
- Asia > Middle East > Turkey (0.28)
- Overview (1.00)
- Research Report (0.68)
- North America > United States > Texas > Anadarko Basin (0.99)
- North America > United States > Oklahoma > Anadarko Basin (0.99)
- North America > United States > Kentucky > Illinois Basin (0.99)
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- Reservoir Description and Dynamics > Storage Reservoir Engineering > CO2 capture and sequestration (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)
- Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (1.00)
A One-Dimensional Convolutional Neural Network for Fast Predictions of the Oil-CO2 Minimum Miscibility Pressure in Unconventional Reservoirs
Sun, Hao (Schulich School of Engineering, University of Calgary) | Chen, Zhangxin (Schulich School of Engineering, University of Calgary (Corresponding author))
Summary Miscible carbon dioxide (CO2) injection has proven to be an effective method of recovering oil from unconventional reservoirs. An accurate and efficient procedure to calculate the oil-CO2 minimum miscibility pressure (MMP) is a crucial subroutine in the successful design of a miscible CO2 injection. However, current numerical methods for the unconventional MMP prediction are very demanding in terms of time and computational costs which result in long runtime with a reservoir simulator. This work proposes to employ a one-dimensional convolutional neural network (1D CNN) to accelerate the unconventional MMP determination process. Over 1,200 unconventional MMP data points are generated using the multiple-mixing-cell (MMC) method coupled with capillarity and confinement effects for training purposes. The data set is first standardized and then processed with principal component analysis (PCA) to avoid overfitting. The performance of the proposed model is evaluated with testing data. By applying the trained model, the unconventional MMP results are almost instantly produced and a coefficient of determination of 0.9862 is achieved with the testing data. Notably, 98.58% of predicting data points lie within 5% absolute relative error. This work demonstrates that the prediction of unconventional MMP can be significantly accelerated, compared with the numerical simulations, by the proposed well-trained deep learning model with a slight impact on the accuracy.
- North America > Canada > Alberta (0.46)
- Asia > Middle East > UAE (0.28)
- North America > United States > Texas (0.28)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)
- Data Science & Engineering Analytics > Information Management and Systems > Neural networks (1.00)
A New Gradient-Accelerated Two-Stage Multiobjective Optimization Method for CO2-Alternating-Water Injection in an Oil Reservoir
Liu, Shuaichen (School of Petroleum Engineering, China University of Petroleum (East China)) | Yuan, Bin (School of Petroleum Engineering, China University of Petroleum (East China) / Key Laboratory of Unconventional Oil & Gas Development (China University of Petroleum (East China)) (Corresponding author)) | Zhang, Wei (School of Petroleum Engineering, China University of Petroleum (East China))
Summary CO2-water-alternating-gas (CO2-WAG) is a reservoir development method that can simultaneously enhance oil recovery and achieve CO2 storage. However, improperly designed parameters for CO2 injection and oil production may significantly reduce the oil displacement efficiency and CO2 storage. Furthermore, optimizing the injection parameters is computationally expensive due to the high computational cost of the compositional simulation. This work aims to propose an efficient optimization method to obtain a series of well-control schemes that balance maximizing net present value (NPV) and CO2 storage for decision-makers. Given the number of CO2-WAG cycles and the duration of each cycle, we optimize the water injection rate, gas injection rate, and half-cycle for the injection well and the bottomhole pressure (BHP) for the production well. In this paper, a two-stage optimization strategy is proposed to enhance the optimization efficiency. The first stage performs the surrogate-assisted single-objective optimizations of each considered objective. It is designed to find the endpoints of the Pareto front that connect all solutions of the multiobjective optimization; this stage not only provides important search directions for the subsequent multiobjective optimization but also improves the accuracy of the surrogate model near the Pareto front. The second stage is the surrogate-assisted multiobjective optimization, which aims to find all the solutions along the Pareto front based on the Pareto endpoints obtained from the first stage. In addition, this study successfully combines the gradient of the objective functions with the meta-heuristic algorithm during the multiobjective optimization, which ensures a faster convergence to the global optimum. The proposed multiobjective optimization algorithm shows faster convergence than the conventional optimization methods when applied to the three multiobjective optimization test functions. Finally, a comparison with the conventional multiobjective optimization is conducted based on one test function and two benchmark reservoir simulation models to verify the correctness and efficiency of the proposed method. It is confirmed that the proposed method outperforms the conventional ones for the optimization of CO2-WAG injection.
- North America > United States > Texas (0.46)
- North America > Canada > Alberta (0.28)
- Energy > Oil & Gas > Upstream (1.00)
- Water & Waste Management > Water Management > Lifecycle > Disposal/Injection (0.92)
- Asia > Middle East > Iraq > Basra Governorate > Arabian Basin > Widyan Basin > Mesopotamian Basin > Rumaila Field > Zubair Formation (0.99)
- Asia > Middle East > Iraq > Basra Governorate > Arabian Basin > Widyan Basin > Mesopotamian Basin > Rumaila Field > Shuaiba Formation (0.99)
- Asia > Middle East > Iraq > Basra Governorate > Arabian Basin > Widyan Basin > Mesopotamian Basin > Rumaila Field > Nahr Umr Formation (0.99)
- Reservoir Description and Dynamics > Storage Reservoir Engineering > CO2 capture and sequestration (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Waterflooding (1.00)
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Surfactant Enhanced Oil Recovery Improves Oil Recovery in a Depleted Eagle Ford Unconventional Well: A Case Study
Ataceri, I. Z. (Texas A&M University) | Saputra, I. W. R. (Texas A&M University) | Bagareddy, A. R. (Texas A&M University) | Elkady, M. H. (Texas A&M University) | Schechter, D. S. (Texas A&M University) | Haddix, G. W. (Third Wave Production LLC (Corresponding author)) | Brock, V. A. (Third Wave Production LLC) | Raney, K. H. (Third Wave Production LLC) | Strickland, C. W. (Third Wave Production LLC) | Morris, G. R. (Auterra Operating LLC)
Summary A simple huff “n” puff (HnP) injection and flowback using a nonionic surfactant solution to drive enhanced oil recovery (EOR) in a depleted Eagle Ford “black oil” unconventional well has been executed and analyzed. The pilot injection was performed in December 2020, with pressures below the estimated fracture gradient. More than 12,300 bbl of surfactant solution were injected into the 6,000-ft lateral. In January 2021, the well was put back on production with oil and water flow rate data being gathered and samples collected. Within 3 months of the well being put back onto production after surfactant stimulation, the well produced at oil rates over five times what it had produced before stimulation. The current oil rates (through October 2022; 22 months after stimulation) are still twice the prestimulation rates. Using a long-term hyperbolic fit to historical data as the “most likely” production scenario in the absence of stimulation as a “baseline,” incremental recovery was estimated using the actual oil production data to date. Economic analysis with prevailing West Texas Intermediate (i.e., WTI) prices at the time of production and the known costs of the pilot result in project payout time less than 1 year and project internal rate of return in excess of 80%, with only incremental production to date. These results prove the potential for technoeconomic viability of HnP EOR techniques using surfactants for wettability alteration in depleted unconventional oil wells. The well was chosen from a portfolio of unconventional Eagle Ford black oil window wells that were completed in the 2012–2014 time frame. The goal of the test was to demonstrate successful application of laboratory work to the field and economic viability of surfactant-driven water imbibition as a means of incremental EOR. The field design was based on laboratory work completed on oil and brine samples from the well of interest, with rock sampled from a nearby well at the same depth. The technical and economic objectives of the field test were to (1) inject surfactant solution to contact sufficient matrix surface area that measurable and economically attractive amounts of oil could be mobilized, (2) measure the amount of surfactant produced in the flowback stream to determine the amount of surfactant retained in the reservoir, and (3) prove the concept of using wettability alteration in conjunction with residual well energy in a depleted well to achieve economically attractive incremental recovery. Surfactant selection was completed in the laboratory using oil and brine gathered from potential target wells, and rock from nearby wells completed in the same strata. Several surfactant formulations were tested, and a final nonionic formulation was chosen on the basis of favorable wettability alteration and improved spontaneous imbibition recovery. The design for the pilot relied on rules of thumb derived from unconventional completion parameters. Rates, pressures, and injectant composition were carefully controlled for the single-day “bullhead” injection. Soak time between injection and post-stimulation restart of production was inferred from laboratory-scale imbibition trials. Post-stimulation samples were gathered, while daily oil and water rates were monitored since production restart. Flowback samples were analyzed for total dissolved solids (TDS), ions, and surfactant concentration.
- Geology > Mineral (1.00)
- Geology > Petroleum Play Type > Unconventional Play > Shale Play (0.46)
- Geology > Geological Subdiscipline > Geomechanics (0.46)
- Energy > Oil & Gas > Upstream (1.00)
- Materials > Chemicals > Commodity Chemicals > Petrochemicals (0.68)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Shale gas (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Gas-injection methods (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)
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Immiscible Viscous Fingering at the Field Scale: Numerical Simulation of the Captain Polymer Flood
Beteta, A. (Institute of GeoEnergy Engineering, Heriot-Watt University (Corresponding author)) | Sorbie, K. S. (Institute of GeoEnergy Engineering, Heriot-Watt University) | Johnson, G. (Ithaca Energy (UK) Limited)
Summary Immiscible fingering in reservoirs results from the displacement of a resident high-viscosity oil by a significantly less viscous immiscible fluid, usually water. During oil recovery processes, where water is often injected for sweep improvement and pressure support, the viscosity ratio between oil and water can lead to poor oil recovery due to the formation of immiscible viscous fingers resulting in oil bypassing. Polymer flooding, where the injection water is viscosified by the addition of high-molecular-weight polymers, is designed to reduce the impact of viscous fingering by reducing the ratio. A considerable effort has been made in the past decade to improve the mechanistic understanding of polymer flooding as well as in developing the numerical simulation methodologies required to model it reliably. Two key developments have been (i) the understanding of the viscous crossflow mechanism by which polymer flooding operates in the displacement of viscous oil and (ii) the simulation methodology put forward by Sorbie et al. (2020), whereby immiscible fingering and viscous crossflow can be simply matched in conventional reservoir simulators. This publication extends the work of Beteta et al. (2022b) to conceptual models of a field case currently undergoing polymer flooding—the Captain field in the North Sea. The simulation methodology is essentially “upscaled” in a straightforward manner using some simple scaling assumptions. The effects of polymer viscosity and slug size are considered in a range of both 2D and 3D models designed to elucidate the role of polymer in systems both with and without “water slumping.” Slumping is governed by the density contrast between oil and water, the vertical communication of the reservoir and the fluid velocity, and, when it occurs, the injection of water channels along the bottom of the reservoir directly to the production well(s). It is shown that polymer flooding is very applicable to a wide range of reservoirs, with only modest injection viscosities and bank sizes returning significant volumes of incremental oil. Indeed, oil incremental recoveries (IRs) of between 29% and 89% are predicted in the simulations of the various 2D and 3D cases, depending on the slug design for both nonslumping and slumping cases. When strong water slumping is present, the performance of the polymer flood is significantly more sensitive to slug design, as alongside the viscous crossflow mechanism of recovery, a further role of the polymer is introduced—sweep of the “attic” oil by the viscous polymer flood, which is able to overcome the gravity-driven slumping, and we also identify this mechanism as a slightly different form of viscous crossflow. In slumping systems, it is critical to avoid disrupting the polymer bank before sweeping of the attic oil has been performed. However, as with the nonslumping system, modest injection viscosities and bank sizes still have a very significant impact on recovery. The conceptual models used here have been found to be qualitatively very similar to real field results. Our simulations indicate that there are few cases of viscous oil recovery where polymer flooding would not be of benefit.
- North America > United States (1.00)
- Europe > United Kingdom > North Sea > Central North Sea > Moray Firth (0.25)
- Energy > Oil & Gas > Upstream (1.00)
- Water & Waste Management > Water Management > Lifecycle > Disposal/Injection (0.34)
- North America > United States > Alaska > North Slope Basin > Milne Point Field > Kuparuk Formation (0.99)
- Europe > United Kingdom > North Sea > Southern North Sea > Southern Gas Basin > Silver Pit Basin > Block 49/30c > Davy Fields > Brown Field > Rotliegend Formation (0.99)
- Europe > United Kingdom > North Sea > Central North Sea > Moray Firth > Moray Firth Basin > Block 13/22a > Captain Field > Captain Formation (0.99)