Deriving Alkali Polymer Parameter Distributions from Core Flooding by Applying Machine Learning in a Bayesian Framework to Simulate Incremental Oil Recovery

2020 ◽  
Author(s):  
Dominik Steineder ◽  
Gisela Vanegas ◽  
Torsten Clemens ◽  
Markus Zechner
Keyword(s):  
Machine Learning ◽  
Oil Recovery ◽  
Bayesian Framework ◽  
Core Flooding ◽  
Incremental Oil Recovery ◽  
Parameter Distributions

Conditioning Model Ensembles to Various Observed Data (Field and Regional Level) by Applying Machine-Learning-Augmented Workflows to a Mature Field with 70 Years of Production History

2021 ◽  
pp. 1-18
Author(s):  
Gisela Vanegas ◽  
John Nejedlik ◽  
Pascale Neff ◽  
Torsten Clemens
Keyword(s):  
Machine Learning ◽  
Oil Recovery ◽  
Numerical Models ◽  
Operating Conditions ◽  
Model Parameters ◽  
Large Set ◽  
Model Parameter ◽  
Production History ◽  
Hydrocarbon Fields ◽  
Parameter Distributions

Summary Forecasting production from hydrocarbon fields is challenging because of the large number of uncertain model parameters and the multitude of observed data that are measured. The large number of model parameters leads to uncertainty in the production forecast from hydrocarbon fields. Changing operating conditions [e.g., implementation of improved oil recovery or enhanced oil recovery (EOR)] results in model parameters becoming sensitive in the forecast that were not sensitive during the production history. Hence, simulation approaches need to be able to address uncertainty in model parameters as well as conditioning numerical models to a multitude of different observed data. Sampling from distributions of various geological and dynamic parameters allows for the generation of an ensemble of numerical models that could be falsified using principal-component analysis (PCA) for different observed data. If the numerical models are not falsified, machine-learning (ML) approaches can be used to generate a large set of parameter combinations that can be conditioned to the different observed data. The data conditioning is followed by a final step ensuring that parameter interactions are covered. The methodology was applied to a sandstone oil reservoir with more than 70 years of production history containing dozens of wells. The resulting ensemble of numerical models is conditioned to all observed data. Furthermore, the resulting posterior-model parameter distributions are only modified from the prior-model parameter distributions if the observed data are informative for the model parameters. Hence, changes in operating conditions can be forecast under uncertainty, which is essential if nonsensitive parameters in the history are sensitive in the forecast.

Non-Edible Oil Based Surfactant For Enhanced Oil Recovery

2021 ◽  
Author(s):  
Adekunle Tirimisiyu Adeniyi ◽  
Ijoma Onyemaechi
Keyword(s):  
Methyl Ester ◽  
Sodium Hydroxide ◽  
Sodium Carbonate ◽  
Oil Recovery ◽  
Sodium Dodecyl ◽  
Synthetic Surfactant ◽  
Chemical Flooding ◽  
Core Flooding ◽  
Incremental Oil Recovery ◽  
Increasing Demand

Abstract After the primary and secondary oil recoveries, a substantial amount of oil is left in the reservoir which can be recovered by tertiary methods like the Alkaline-Surfactant Flood. Reasons for having some unproduced hydrocarbon in the reservoir include and not limited to the following; forces of attraction fluid contacts, low permeability, high viscous fluid, poor swept efficiency, etc. Although, it is possible to commence waterflooding together chemical injection at the start of production. Reservoir simulation with commercial simulator, could guide in selecting the most appropriate period to commence chemical flooding. In this study, the performance of a new synthetic surfactant produced from Jatropha Curcas seed was compared with that of a selected commercial surfactant in the presence of an alkaline and this shows that the non-edible Jatropha oil is a natural, inexpensive and a renewable source of energy for the production of anionic surfactants and a good substitute for commercial surfactants like Sodium Dodecyl Sulphate (SDS). The Methyl Ester Sulfonate (MES) surfactant showed no precipitation or cloudiness during stability test and was able to reduce the Interfacial Tension (IFT) to 0.018 mN/m and 0.020 mN/m in the presence of sodium carbonate and sodium hydroxide respectively as alkaline at low surfactant concentration. The optimum alkaline surfactant formulation in terms of oil recovery performance obtained from the core flooding experiment corresponds to a concentration of sodium carbonate (0.5wt%), sodium hydroxide (0.5wt%) mixed in distilled water and Methyl Ester Sulfonate (MES) surfactant (1wt%). The injection of 0.5 percentage volume of alkaline surfactant slug produced an incremental oil recovery of 26.7% and 29% respectively. With these incremental oil recoveries, increasing demand for hydrocarbons product could be met, and returns on investment portfolio will be improved.

Analyzing the Influence of Salinity on Produced Water Re-Injection

2021 ◽  
Author(s):  
Adekunle Tirimisiyu Adeniyi ◽  
Chimgozirim Prince Ejim
Keyword(s):  
Oil Recovery ◽  
Produced Water ◽  
Core Sample ◽  
Production Performance ◽  
Core Flooding ◽  
Daily Rate ◽  
Reservoir Conditions ◽  
Cumulative Production ◽  
Water Disposal ◽  
Incremental Oil Recovery

Abstract Produced water reinjection (PWRI) is one of the methods employed by oilfield operators to optimize production while conforming to increasingly stringent produced water disposal policies. Different produced water species from different facilities also have different salinities as a result of entrainment of treatment fluids, precipitation of salts at surface conditions, etc. During re-injection operations, the salinity of the injection fluid has to be accounted for as it affects the production. Previous studies have focused on laboratory analysis by core flooding. While this approach is indeed reasonable and offers a first-hand impression of the reservoir conditions, it presents a problem of cost and the age-old opinion that the core sample may not be representative of the entire reservoir. Therefore, I have employed a computer modeling approach using a commercial simulator to analyze the influence of salinity on production during produced water re-injection. It was found that the salinity truly affects production. Re-injection of produced water with salinity equal to the reservoir salinity of 1000 ppm was compared to three cases of re-injection of produced water from extraneous sources having salinities of 100 ppm, 500 ppm and 10000 ppm. It was found that salinity of 10000 ppm gave the best oil production performance for the reservoir model; a daily rate of 40 STB/DAY and an oil cumulative production of 40,000 STB. Incremental salinity of injected produced water led to incremental oil recovery. The mechanism resulting in incremental recovery was attributed to the increase in viscosity and decrease in mobility as the salinity increases.

Effect of Oil and Water Interfacial Tension on Oil Recovery of Surfactant-Polymer Flooding

2012 ◽  
Vol 524-527 ◽  
pp. 1798-1801
Author(s):  
You Yi Zhu ◽  
Yi Zhang ◽  
Qing Feng Hou ◽  
Hua Long Liu ◽  
Guo Qing Jian
Keyword(s):  
Interfacial Tension ◽  
Oil Recovery ◽  
Polymer Flooding ◽  
Core Flooding ◽  
Physics Simulation ◽  
Low Interfacial Tension ◽  
Incremental Oil Recovery

The oil and water (O/W) interfacial tension affecting on oil recovery of surfactant-polymer (SP) flooding was studied based on Berea core flooding tests. The results of SP flooding physics simulation tests showed that when the O/W interfacial tension decreased, the incremental oil recovery of SP flooding increased accordingly, when the O/W interfacial tension decrease to 5×10-3mN/m level, near the highest oil recovery of SP flooding can be obtained. The SP flooding system with low interfacial tension can obtain 7-15% incremental oil recovery more than that with high IFT system.

scholarly journals Application of Nanofluid Injection for Enhanced Oil Recovery (EOR)

2021 ◽  
Vol 23 (08) ◽  
pp. 751-761
Author(s):  
Abdelrahman El-Diasty ◽  
◽  
Hamid Khattab ◽  
Mahmoud Tantawy ◽  
◽  
...  
Keyword(s):  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Oil Field ◽  
Porous Rocks ◽  
Core Flooding ◽  
Rock Interaction ◽  
Fluid Properties ◽  
Incremental Oil Recovery

The use of nanofluids has been investigated and established for several applications in the oil and gas industry. Using nanoparticles for Enhanced Oil Recovery (EOR) applications underlines their small size in comparison with the size of the rock pore throats; consequently, they could easily transport into porous rocks with minimum retention effect and permeability reduction. Nanoparticles can significantly increase the oil recovery by enhancing both the fluid properties and fluid-rock interaction properties. In this study, commercial silica nanoparticles dispersions were used in standard core flooding experiments to evaluate the effect of the nanofluid injection on the incremental oil recovery. This will open the door for taking the nanotechnology from the lab to the oil field.

Determination of Optimum Parameters for Anaerobic Thermophilic Bacterium Injection using Commercial Simulator: Core Flooding Validation and Sensitivity

2020 ◽  
Author(s):  
A. Koto
Keyword(s):  
Oil Recovery ◽  
Simulation Experiment ◽  
Previous Experiment ◽  
Core Sample ◽  
Thermophilic Bacterium ◽  
Injection Rate ◽  
Core Flooding ◽  
Optimum Parameters ◽  
Result Show

The objective of this paper is to determine the optimum anaerobic-thermophilic bacterium injection (Microbial Enhanced Oil Recovery) parameters using commercial simulator from core flooding experiments. From the previous experiment in the laboratory, Petrotoga sp AR80 microbe and yeast extract has been injected into core sample. The result show that the experiment with the treated microbe flooding has produced more oil than the experiment that treated by brine flooding. Moreover, this microbe classified into anaerobic thermophilic bacterium due to its ability to live in 80 degC and without oxygen. So, to find the optimum parameter that affect this microbe, the simulation experiment has been conducted. The simulator that is used is CMG – STAR 2015.10. There are five scenarios that have been made to forecast the performance of microbial flooding. Each of this scenario focus on the injection rate and shut in periods. In terms of the result, the best scenario on this research can yield an oil recovery up to 55.7%.

scholarly journals Investigation on degradation mechanism of polymer blockages in unconsolidated sandstone reservoirs

e-Polymers ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 55-60
Author(s):  
Wenting Dong ◽  
Dong Zhang ◽  
Keliang Wang ◽  
Yue Qiu
Keyword(s):  
Oil Recovery ◽  
Degradation Mechanism ◽  
Injection Pressure ◽  
Polymer Flooding ◽  
Core Flooding ◽  
Reservoir Properties ◽  
Thermal Analyzer ◽  
Sandstone Reservoirs ◽  
Suction Index ◽  
Weighing Method

AbstractPolymer flooding technology has shown satisfactorily acceptable performance in improving oil recovery from unconsolidated sandstone reservoirs. The adsorption of the polymer in the pore leads to the increase of injection pressure and the decrease of suction index, which affects the effect of polymer flooding. In this article, the water and oil content of polymer blockages, which are taken from Bohai Oilfield, are measured by weighing method. In addition, the synchronous thermal analyzer and Fourier transform infrared spectroscopy (FTIR) are used to evaluate the composition and functional groups of the blockage, respectively. Then the core flooding experiments are also utilized to assess the effect of polymer plugs on reservoir properties and optimize the best degradant formulation. The results of this investigation show that the polymer adsorption in core after polymer flooding is 0.0068 g, which results in a permeability damage rate of 74.8%. The degradation ability of the agent consisting of 1% oxidizer SA-HB and 10% HCl is the best, the viscosity of the system decreases from 501.7 to 468.5 mPa‧s.

scholarly journals Practical CO2—WAG Field Operational Designs Using Hybrid Numerical-Machine-Learning Approaches

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1055
Author(s):  
Qian Sun ◽  
William Ampomah ◽  
Junyu You ◽  
Martha Cather ◽  
Robert Balch
Keyword(s):  
Machine Learning ◽  
Oil Recovery ◽  
History Matching ◽  
Optimization Problems ◽  
Learning Technologies ◽  
Petroleum Engineering ◽  
Support Vector ◽  
Learning Approaches ◽  
Field Development ◽  
Proxy Models

Machine-learning technologies have exhibited robust competences in solving many petroleum engineering problems. The accurate predictivity and fast computational speed enable a large volume of time-consuming engineering processes such as history-matching and field development optimization. The Southwest Regional Partnership on Carbon Sequestration (SWP) project desires rigorous history-matching and multi-objective optimization processes, which fits the superiorities of the machine-learning approaches. Although the machine-learning proxy models are trained and validated before imposing to solve practical problems, the error margin would essentially introduce uncertainties to the results. In this paper, a hybrid numerical machine-learning workflow solving various optimization problems is presented. By coupling the expert machine-learning proxies with a global optimizer, the workflow successfully solves the history-matching and CO2 water alternative gas (WAG) design problem with low computational overheads. The history-matching work considers the heterogeneities of multiphase relative characteristics, and the CO2-WAG injection design takes multiple techno-economic objective functions into accounts. This work trained an expert response surface, a support vector machine, and a multi-layer neural network as proxy models to effectively learn the high-dimensional nonlinear data structure. The proposed workflow suggests revisiting the high-fidelity numerical simulator for validation purposes. The experience gained from this work would provide valuable guiding insights to similar CO2 enhanced oil recovery (EOR) projects.

scholarly journals Photon-magnon response to fluid variability and saturation levels in sandstone reservoirs

2020 ◽  
Vol 17 (6) ◽  
pp. 1065-1074
Author(s):  
Abdullah Musa Ali ◽  
Amir Rostami ◽  
Noorhana Yahya
Keyword(s):  
Oil Recovery ◽  
Relative Permittivity ◽  
Wave Interaction ◽  
Heterogeneous Porous Media ◽  
Injection System ◽  
Bragg Grating ◽  
Fibre Bragg Grating ◽  
Core Flooding ◽  
Oil Saturation ◽  
Fluid Saturation

Abstract The need to recover high viscosity heavy oil from the residual phase of reservoirs has raised interest in the use of electromagnetics (EM) for enhanced oil recovery. However, the transformation of EM wave properties must be taken into consideration with respect to the dynamic interaction between fluid and solid phases. Consequently, this study discretises EM wave interaction with heterogeneous porous media (sandstones) under different fluid saturations (oil and water) to aid the monitoring of fluid mobility and activation of magnetic nanofluid in the reservoir. To achieve this aim, this study defined the various EM responses and signatures for brine and oil saturation and fluid saturation levels. A Nanofluid Electromagnetic Injection System (NES) was deployed for a fluid injection/core-flooding experiment. Inductance, resistance and capacitance (LRC) were recorded as the different fluids were injected into a 1.0-m long Berea core, starting from brine imbibition to oil saturation, brine flooding and eventually magnetite nanofluid flooding. The fluid mobility was monitored using a fibre Bragg grating sensor. The experimental measurements of the relative permittivity of the Berea sandstone core (with embedded detectors) saturated with brine, oil and magnetite nanofluid were given in the frequency band of 200 kHz. The behaviour of relative permittivity and attenuation of the EM wave was observed to be convolutedly dependent on the sandstone saturation history. The fibre Bragg Grating (FBG) sensor was able to detect the interaction of the Fe3O4 nanofluid with the magnetic field, which underpins the fluid mobility fundamentals that resulted in an anomalous response.

scholarly journals Manipulation of surface charges of oil droplets and carbonate rocks to improve oil recovery

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jian Hou ◽  
Ming Han ◽  
Jinxun Wang
Keyword(s):  
Zeta Potential ◽  
Oil Recovery ◽  
Carbonate Rocks ◽  
Zwitterionic Surfactant ◽  
Surface Charges ◽  
Oil Droplets ◽  
Zeta Potentials ◽  
Potential Value ◽  
Oil Water ◽  
Incremental Oil Recovery

AbstractThis work investigates the effect of the surface charges of oil droplets and carbonate rocks in brine and in surfactant solutions on oil production. The influences of the cations in brine and the surfactant types on the zeta-potentials of both oil droplets and carbonate rock particles are studied. It is found that the addition of anionic and cationic surfactants in brine result in both negative or positive zeta-potentials of rock particles and oil droplets respectively, while the zwitterionic surfactant induces a positive charge on rock particles and a negative charge on oil droplets. Micromodels with a CaCO3 nanocrystal layer coated on the flow channels were used in the oil displacement tests. The results show that when the oil-water interfacial tension (IFT) was at 10−1 mN/m, the injection of an anionic surfactant (SDS-R1) solution achieved 21.0% incremental oil recovery, higher than the 12.6% increment by the injection of a zwitterionic surfactant (SB-A2) solution. When the IFT was lowered to 10−3 mM/m, the injection of anionic/non-ionic surfactant SMAN-l1 solution with higher absolute zeta potential value (ζoil + ζrock) of 34 mV has achieved higher incremental oil recovery (39.4%) than the application of an anionic/cationic surfactant SMAC-l1 solution with a lower absolute zeta-potential value of 22 mV (30.6%). This indicates that the same charge of rocks and oil droplets improves the transportation of charged oil/water emulsion in the porous media. This work reveals that the surface charge in surfactant flooding plays an important role in addition to the oil/water interfacial tension reduction and the rock wettability alteration.

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