application

Abstract Unconventional reservoirs like shale oil/gas are expected to play a major role in many unexplored regions, globally. Shale resource evaluation involves the estimation of Total Organic Carbon (TOC) which correlates to the prospective capability of generating and containing hydrocarbons. Direct measurement of TOC through geochemical analysis is often not feasible, and hence researchers have focused on indirect methods to estimate TOC using analytical and statistical techniques. Accordingly, this work proposes the application of artificial intelligence (AI) techniques to leverage routinely available well logs for the prediction of TOC. Multiple algorithms are developed and compared to rank the most optimum solution based on efficiency analysis. Support Vector Regression (SVR), Random Forest (RF), and XGBoost algorithms are utilized to analyze the well-log data and develop intelligent models for shale TOC. A process-based approach is followed starting with systematic data analysis, which includes the selection of the most relevant input parameters, data cleaning, filtering, and data-dressing, to ensure optimized inputs into the AI models. The data utilized in this work is from major shale basins in Asia and North America. The AI models are then used to develop TOC predictor as a function of fundamental open-hole logs including sonic, gamma-ray, resistivity, and density. Furthermore, to strengthen AI input-output correlation mapping, a k-fold cross-validation methodology integrating with the exhaustive-grid search approach is adopted. This ensures the optimized hyperparameters of the intelligent algorithms developed in this work are selected. Finally, developed models are compared to geochemically derived TOC using a comprehensive error analysis schema. The proposed models are teted for veracity by applying them on blind dataset. An error metrics schema composed of root-mean-squared-error, and coefficient of determination, is developed. This analysis ranks the respective AI models based on the highest performance efficiency and lowest prediction error. Consequently, it is concluded that the XGBoost and SVR-based TOC predictions are inaccurate yielding high deviations from the actual measured values in predictive mode. On the other hand, Random Forest TOC predictor optimized using k-fold validation produces high R values of more than 0.85 and reasonably low errors when compared to true values. The RF method overpowers other models by mapping complex non-linear interactions between TOC and various well logs.

doi: 10.2118/214383-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

SPE-214383-MS

Country:

Asia (0.90)
North America > Canada (0.29)
Europe > Austria (0.28)

Geophysics: Geophysics (0.46)

Industry: Energy > Oil & Gas > Upstream (1.00)

Oilfield Places:

North America > United States > South Dakota > Williston Basin > Bakken Shale Formation (0.99)
North America > United States > North Dakota > Williston Basin > Bakken Shale Formation (0.99)
North America > United States > Montana > Williston Basin > Bakken Shale Formation (0.99)
(6 more...)

SPE Disciplines:

Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Shale oil (1.00)
Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Shale gas (1.00)
Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (1.00)

Technology: Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning > Support Vector Machines (0.87)

Samarkin, Yevgeniy (King Fahd University of Petroleum and Minerals) | Amao, Abduljamiu Olalekan (King Fahd University of Petroleum and Minerals) | Aljawad, Murtada Saleh (King Fahd University of Petroleum and Minerals) | Sølling, Theis Ivan (King Fahd University of Petroleum and Minerals) | AlTammar, Murtadha J. (Saudi Aramco) | Alruwaili, Khalid M. (Saudi Aramco)

High-Temperature DAP Treatments of Carbonate Rocks for Proppant Embedment Severity Mitigation

Abstract Fractured carbonate formations composed of chalk and limestone rock lithologies develop several issues over time, reducing fractures’ conductivity. One such issue is the embedment of the proppant that happens due to the soft nature of the carbonate rocks. Reduction of fractures’ conductivity results in the need for refracturing operations that require pumping tremendous amounts of water. The refracturing operations can be avoided if the fractures are maintained conductive for a longer time. This research targets reducing the severity of proppant embedment issues in carbonate formations through rock hardening by diammonium hydrogen phosphate (DAP) treatment. The chalk and limestone rock samples were treated with a DAP solution of 0.8M concentration at three temperatures, namely 30°C (ambient), 50°C, and 80°C. The samples were treated by immersion in solution, in which rocks were kept reacting for 72 hours. The treated samples were analyzed using the SEM-EDX technique to identify new minerals and changes in the morphology of the rock samples. Moreover, the changes in the hardness of the samples were analyzed by the impulse hammering technique. In addition, the proppant embedment scenario was mimicked in the rocks by utilizing Brinell hardness measurements before and after their treatment. The SEM analysis demonstrated that the treatment of carbonate rocks with a DAP solution results in the formation of hydroxyapatite (HAP) minerals. In addition, it was observed that the temperature of the treatment affects the crystallization patterns of the HAP minerals. Further results demonstrated that DAP treatment at elevated temperatures significantly improves the hardness of the samples. Young’s modulus of the rock samples increased by up to 60 - 80% after the treatment. In addition, studies have shown the improvement of rocks’ resistance to indentations. The sizes of the dents created by the Brinell hardness device were smaller than before the treatment. Overall, it was demonstrated that the Brinell hardness of the rock samples improved by more than 100%. This research demonstrated that treating carbonate rocks with DAP solution results in their hardening and improved samples’ resistance to indentation. Moreover, the treatment of rock samples at temperatures similar to reservoir conditions even further improves the mechanical properties of the carbonate rocks. Upscaling laboratory DAP treatment techniques for reservoir applications will introduce new practical methods for maintaining the long-term conductivity of propped fractures. Such a procedure will help avoid refracturing operations, resulting in better and more sustainable management of water resources.

doi: 10.2118/214368-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

SPE-214368-MS

Country:

Europe (0.94)
North America > United States (0.48)

Genre: Research Report > New Finding (1.00)

Industry:

Materials > Chemicals (1.00)
Energy > Oil & Gas > Upstream (1.00)

Oilfield Places: Europe > Poland > Baltic Basin (0.99)

SPE Disciplines:

Well Completion > Hydraulic Fracturing > Fracturing materials (fluids, proppant) (1.00)
Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Carbonate reservoirs (1.00)
Reservoir Description and Dynamics > Reservoir Characterization (1.00)

Al-Ghamdi, Ahmed (Saudi Aramco) | Al-Jawad, Murtada (King Fahd University of Petroleum and Minerals) | Mahmoud, Mohamed (King Fahd University of Petroleum and Minerals)

Paradigm Shift in Conventional Hydraulic Fracturing - Emerging Fracturing Techniques Using Thermochemical Fluids

Abstract Hydraulic fracturing has long been an established well stimulation technique in the oil & gas industry, unlocking hydrocarbon reserves in tight and unconventional reservoirs. The two types of hydraulic fracturing are proppant fracturing and acid fracturing. Recently, a new of hydraulic fracturing is emerging which is delivering yet more enhanced production/injection results. This paper conducts a critical review of the emerging fracturing techniques using Thermochemical fluids. The main purpose of hydraulic fracturing is to break up the reservoir and create fractures enhancing the fluid flow from the reservoir matrix to the wellbore. This is historically achieved through either proppant fracturing or acid fracturing. In proppant fracturing, the reservoir is fractured through a mixture of water, chemicals and proppant (e.g. sand). The high-pressure water mixture breaks the reservoir, and the proppant particles enter in the fractures to keep it open and allow hydrocarbon flow to the wellbore. As for acid fracturing, the fractures are kept open through etching of the fracture face by acid such as Hydrochloric Acid (HCl). An emerging technique of hydraulic fracturing is through utilization of thermochemical solutions. These environmentally friendly and cost-efficient are not reactive as surface conditions, and only react in the reservoir at designated conditions through reservoir temperature or pH-controlled activation techniques. Upon reaction, the thermochemical solutions undergo an exothermic reaction generating in-situ foam/gases resulting in creating up to 20,000 psi in-situ pressure and temperature of up to 700 degrees Fahrenheit. Other reported advantages from thermochemical fracturing include the condensate bank removal (due to the exothermic reaction temperature) and capillary pressure reduction.

doi: 10.2118/214376-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

SPE-214376-MS

acid, al-majed, al-nakhli, ammonium chloride, application, asphaltene inhibition, asphaltene remediation, complex reservoir, condensate reservoir, core analysis, drilling fluid chemistry, drilling fluid formulation, drilling fluid property, drilling fluid selection and formulation, drilling fluids and materials, Engineering, europe government, experiment, flow assurance, fluid loss control, fracture, fracturing fluid, fracturing materials, Hassan, hydrate inhibition, Hydrate Remediation, hydraulic fracturing, injection, Journal, Mahmoud, microfracture, oilfield chemistry, paraffin remediation, patent, permeability, Petroleum Science, Production Chemistry, proppant, reaction, remediation of hydrates, Reservoir Characterization, reservoir geomechanics, scale inhibition, scale remediation, seismic surveying, stimulation, survey article, thermochemical fluid, united states government, Upstream Oil & Gas, wax inhibition, wax remediation

Country:

Europe (0.93)
North America > United States > Texas (0.47)

Genre:

Research Report (0.47)
Overview (0.46)

Geophysics: Geophysics > Seismic Surveying (0.68)

Industry: Energy > Oil & Gas > Upstream (1.00)

Oilfield Places:

North America > United States > Texas > West Gulf Coast Tertiary Basin > Eagle Ford Shale Formation (0.99)
North America > United States > Texas > Sabinas - Rio Grande Basin > Eagle Ford Shale Formation (0.99)
North America > United States > Texas > Maverick Basin > Eagle Ford Shale Formation (0.99)

SPE Disciplines:

Well Completion > Hydraulic Fracturing > Fracturing materials (fluids, proppant) (1.00)
Reservoir Description and Dynamics > Reservoir Characterization > Reservoir geomechanics (1.00)
Production and Well Operations > Production Chemistry, Metallurgy and Biology > Inhibition and remediation of hydrates, scale, paraffin / wax and asphaltene (1.00)
(4 more...)

Technology: Information Technology (0.68)

Case Study of the Use of a Digital Twin for Leak Detection and Quantification in Underground Gas Storage Wells

Baronio, Emanuele (Snam Spa) | Abdo, Elia (Snam Spa) | Mauro, Stefano (Politecnico di Torino) | Troise, Mario (Politecnico di Torino) | Salamina, Laura (Politecnico di Torino)

Abstract Underground gas storage (UGS) are essential components in energy security. However, UGS wells present a complicated and delicate combination of elements where ensuring safe and secure functionality over long periods is paramount. Today, with the advancement of continuous remote monitoring and digitalization, evaluating the integrity of UGS wells has become quicker and more efficient. This paper showcases how a digital twin is used to evaluate and forecast the link between leaks and temperature and pressure trends in a UGS well, allowing the identification and quantification of defects and, subsequently, well barrier integrity. UGS wells present additional criticalities with respect to normal production wells due to its longer life span and the repetitive production and injection cycles. This makes early and accurate leak detection essential for a safe management of the well barriers. The proposed digital twin has been developed using material and energy balances and considering each annulus as a separate control volume. Each control volume can exchange heat and mass through predesigned barriers. Simulating evolution in time of pressure and temperature in the control volumes., and comparing results with data from field, allows the identification of position and size of leaks. A genetic algorithm is applied to optimize placement of leaks on their specific barriers. The system aims to identify the position and dimension of possible leaks by matching historical pressure, temperature, and flow data. Once a leak is identified, a risk assessment is conducted to evaluate the overall integrity of the well. If the status of the well is found to be critical enough, an intervention may be planned. The system has been in use for little over a year and has shown great potential in accurate and efficient identification of leaks. This has accelerated the process of well integrity evaluation and allowed timely interventions on wells that required it. On the other hand, the process has highlighted cases where previous assumptions about leak location and size were corrected using the digital twin, therefore reducing the costs of interventions. Finally, the model showcased a clear readiness for predictive capabilities aimed to select, plan and design fit for purpose mitigating actions. This paper highlights the power that a digital twin can present leveraging field data with advanced algorithms. The paper also showcases workflows that allow convenient, efficient, and timely evaluation of well integrity, which leads to safer operating conditions and lower operational costs.

doi: 10.2118/214357-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

SPE-214357-MS

Country:

Europe (0.68)
North America > United States (0.47)
Asia > Middle East > UAE (0.29)

Industry: Energy > Oil & Gas > Upstream (1.00)

SPE Disciplines:

Reservoir Description and Dynamics > Storage Reservoir Engineering > Natural gas storage (1.00)
Health, Safety, Environment & Sustainability (1.00)
Data Science & Engineering Analytics > Information Management and Systems (1.00)

Technology:

Information Technology > Data Science > Data Mining (0.88)
Information Technology > Artificial Intelligence (0.67)

Electric Submersible Generators – Using ESPs in an Unfamiliar Way

Collins, Charles Evan (Baker Hughes) | Frazier, Kenneth Joel (Baker Hughes) | Coates, Bryan (Baker Hughes)

Abstract Electrical Submersible Pumps (ESP) have been used to produce fluids for almost a century in many different industries. Since the 1800s, people have been using hydroelectric dams to produce power, demonstrating the viability of harnessing the potential energy from elevated water sources. However, there is a tremendous opportunity to partially recover that same potential during the yearly reinjection of billions of cubic meters of water in the oil, gas, and geothermal industries by combining the principles from both. The electrical submersible generator (ESG) is a modern interpretation of an old idea. The ESG can generate electricity to meet surface power needs or feed directly into the grid to create a revenue stream under the proper injection conditions. In typical configurations, a standard centrifugal pump is used in combination with an induction motor. Rather than operating the motor in a conventional manner to convert electrical energy to mechanical work, the motor is operated in such a way for the mechanical work of the pump to be converted into electrical energy. Other configurations are optional such as using more conventional turbine pump designs and permanent magnet motors. After the successful completion of a few installations, several changes have been made to optimize the machinery and enhance the equipment operation. Through these efforts, significant knowledge has been gained about how these machines work. For a successful completion, factors including third-party controls, run-away speeds, fluid / reservoir properties, and starting techniques must all be considered. This paper explores the ESG’s design considerations, theoretical underpinnings, and potential future applications. This will involve a review of field operations, installation procedures, and lessons learned. The conclusions of CFD analysis and installations in the actual world will be presented to support the assumptions.

doi: 10.2118/214361-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

SPE-214361-MS

Country: North America > United States (1.00)

Industry: Energy > Oil & Gas > Upstream (1.00)

Oilfield Places:

Europe (0.89)
Asia > Philippines (0.89)

SPE Disciplines:

Reservoir Description and Dynamics > Non-Traditional Resources > Geothermal resources (1.00)
Reservoir Description and Dynamics > Improved and Enhanced Recovery (1.00)
Production and Well Operations > Artificial Lift Systems > Electric submersible pumps (1.00)
Reservoir Description and Dynamics > Formation Evaluation & Management (0.88)

Technology: Information Technology (0.46)

MousaviMirkalaei, Seyed Mousa (Computer Modelling Group Ltd) | Zarei, Faraj (Computer Modelling Group Ltd)

Numerical Simulation for Hydrogen Storage and Bio-Methanation

Abstract The potential applications of hydrogen as an energy vector as a part of the solution to decarbonize emissions from use of natural gas and transportation is the subject of much research. Hydrogen storage in the geological subsurface helps to mitigate the effects of fluctuating energy production from renewable energy sources. Nevertheless, there is little comprehensive work on full scale simulation of all the processes associated with the injection, storage and re-producing of hydrogen. Physical phenomena involved in this process include mixing of hydrogen with native components in the reservoir and potentially cushion gas, ga, relative permeability hysteresis, solubility of various gases into the aqueous phase; effect of hydrogen impurity (e.g., CO2, H2S, CH4) and bio-methanation in the presence bacteria. Numerical simulation can be used for dynamic numerical modelling of the storage when all these complex processes are in action. Solubility of hydrogen can be modelled using a solubility table, Henry's correlation, or K-values table. The effect of other gases on the geochemistry of the rock and fluid can be studied in detail using chemical and geochemical reaction concepts. The activity of bacteria in an underground hydrogen storage field may result in synthetic methane production. Such reactions can be modelled based on bacterial activity levels using Arrhenius type reactions. The level of biomass activity depends on salinity, temperature and bacterial types and availability of nutrients. A sub-sector from a North Sea reservoir is used to simulate these processes described and predictions of individual injection/production at various cycles are created. Issues regarding improved monitoring and design of laboratory experiments for future field operations are highlighted. This study shows how simulation can be instrumental in understanding and designing underground hydrogen storage projects, providing predictions of storage volumes, produced gas quality and quantity under various scenarios. The paper also describes the reaction parameters, upscaling, and tuning techniques required for simulation at full field scale.

doi: 10.2118/214395-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

SPE-214395-MS

application, biomethanation, co 2, cushion ga, dissolution, europe government, Geochemistry, hydrogen, hydrogen netzero, hysteresis, natural gas storage, numerical simulation, reaction, reservoir simulation, solubility, underground hydrogen storage, united states government, Upstream Oil & Gas

Country:

Europe (1.00)
North America > United States > Texas > Kleberg County (0.24)
North America > United States > Texas > Chambers County (0.24)

Genre:

Research Report > New Finding (0.69)
Research Report > Experimental Study (0.54)

Industry: Energy > Oil & Gas > Upstream (1.00)

SPE Disciplines:

Reservoir Description and Dynamics > Storage Reservoir Engineering > Natural gas storage (1.00)
Reservoir Description and Dynamics > Reservoir Simulation (1.00)

Technology: Information Technology > Mathematics of Computing (0.62)

Abstract This work describes a statistical rock-physics driven inversion of seismic acoustic impedance and Ultra Deep Azimuthal Resistivity (UDAR) log data, acquired while drilling, to estimate porosity, water saturation and litho-fluid facies classes around the wellbore. Despite their limited resolution, surface seismic data integrated with electromagnetic resistivity log measurements improve the description of rock properties by considering the coupled effect of pore space and fluid saturation in the joint acoustic and electrical domains. The key aspect of the proposed inversion is that it does not explicitly use a forward model, rather the correlation between the petrophysical properties and the resulting geophysical responses is inferred probabilistically from a training dataset. The training-set is generated combining available borehole information with statistical rock-physics modelling approach. In the inversion process, given co-located measurements of seismic acoustic impedance and logging-while-drilling electromagnetic resistivity data, the pointwise probability distribution of rock-properties is derived directly from the training dataset by applying the kernel density estimation algorithm. A non-parametric statistical approach is employed to approximate non-symmetric volumetric distributions of petrophysical properties and to consider the characteristic non-linear relationship linking water-saturation with resistivity. Given an a-priori facies classification template for the samples in the training-set, it is possible to model the multimodal, facies-dependent, behavior of the petrophysical properties, together with their distinctive correlation patterns. A facies-dependent parameterization allows the effect of lithology on acoustic and resistivity response to be implicitly considered, even though the target properties of inversion are only porosity and saturation. To provide a realistic uncertainty quantification of the estimated rock-properties, a plain Bayesian framework is described which accounts for rock-physics modelling error and to propagate seismic and resistivity data uncertainties to the inversion results. In this respect, the uncertainty related to the scale difference among the well-log data and seismic is addressed by adopting a scale reconciliation strategy based on probabilistic function. This allows transforming physically equivalent measures from one resolution to another and consistently estimate the corresponding changes in the probability distributions. The described rock physics-driven inversion can be performed efficiently during drilling, following the acquisition and inversion of UDAR data, as the time-consuming step of estimating a probabilistic model from the training-set, can be separated from inversion itself. This is of particular interest in geosteering, where the training-phase can be performed before drilling, during well planning operations. After training, the resulting probabilistic model can be stored as a look-up table. Hence, the prediction of rock-properties, given the co-located measurements of seismic acoustic impedance and log-while-drilling electromagnetic resistivity, reduces to a fast look-up table search. The inversion workflow is validated on a clastic oil-bearing reservoir located offshore Norway, where geosteering was used to guide the placement of a horizontal appraisal well in a complex structural setting. A complete set of well logs from four nearby exploration wells is used to construct the training dataset. Porosity, water-saturation, and litho-fluid facies are estimated along the geosteered well path given a 2D curtain section of ultra deep azimuthal resistivity and the corresponding acoustic impedance section available from the 3D surface seismic data. Prior to running the inversion, the acoustic impedance data was properly depth-matched with the resistivity section using a non-rigid matching algorithm. The joint inversion results show that the proposed methodology provides realistic estimates of the rock-property distributions around the wellbore to depths of investigation of 50m. These results constitute useful information to support geosteering decisions and can also be used, post-drilling, to update or optimize existing reservoir models.

doi: 10.2118/214407-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

SPE-214407-MS

Country:

North America > United States (0.46)
Europe > Norway (0.34)
Europe > Austria (0.28)

Genre:

Research Report > New Finding (0.34)
Research Report > Experimental Study (0.34)

Geophysics: Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (1.00)

Industry: Energy > Oil & Gas > Upstream (1.00)

SPE Disciplines:

Well Drilling > Drilling Measurement, Data Acquisition and Automation > Logging while drilling (1.00)
Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
Reservoir Description and Dynamics > Reservoir Characterization > Seismic modeling (1.00)
(2 more...)

Technology:

Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Bayesian Inference (0.88)
Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models > Directed Networks > Bayesian Learning (0.66)

A Control Volume Material Balance Approach and Its Applications to Real-Time Flow Diagnostics

Zhang, Nan (University of Stavanger) | Andersen, Pål Østebø (University of Stavanger) | Rong, Chunming (University of Stavanger)

Abstract In this paper, we propose a Control Volume Material Balance (CVMB) approach for proxy reservoir simulation and apply it to real-time flow diagnostics. Instead of utilizing a comprehensive reservoir simulator, it estimates the saturations distributions by mapping the mass difference between injected and produced fluids recorded at wells into 3D grid blocks. On this basis, we perform real-time flow diagnostics to evaluate the dynamic heterogeneity of the instantaneous displacement flow field which can be used for making effective and opportune decisions to improve oil recovery. CVMB solves the pressure and flow fields implicitly, and the transport equations explicitly. It incorporates 3D heterogenous rock properties. The fundamental idea of the CVMB method is to divide the 3D flow field into a series of 1D well-pair Control Volumes (CVs). A well-pair Control Volume is composed of grid blocks in the intersection of the sweep and drainage regions of the injector and producer. The fluid flow in and out of the 1D CV can only occur at the wells, and the in-situ fluid volumes are determined by the well flow rates and the well allocation factors. In each CV, we assume the displacement in the grid blocks is piston-like and follows the 1D order of ascending forward time-of-flight. The fluid saturation distributions are determined by defining the cut-off time-of-flight for the displacement front. We show how the CVMB method improves the pattern-based mass balance approaches in the following aspects: 1) enables real-time flow diagnostics in terms of the hydrocarbon dynamic Lorenz coefficient without a comprehensive reservoir simulator; 2) enhances the simplicity and extensibility of the pattern-based mass balance approach without mapping between grid blocks and streamlines; 3) reduces the smearing effects in conventional mass balance approach by defining 1D CVs using forward time-of-flight. The proposed CVMB method utilizes the historical well flow rates as the input to estimate the swept regions and its average saturation with remarkable efficiency and sufficient accuracy for real-time flow diagnostics.

doi: 10.2118/214428-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

SPE-214428-MS

Country:

North America > United States > Texas (0.28)
Europe > Austria (0.28)

Industry: Energy > Oil & Gas > Upstream (1.00)

SPE Disciplines:

Reservoir Description and Dynamics > Reservoir Simulation (1.00)
Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
Reservoir Description and Dynamics > Improved and Enhanced Recovery > Waterflooding (1.00)
(2 more...)

Technology:

Information Technology > Modeling & Simulation (1.00)
Information Technology > Architecture > Real Time Systems (1.00)

Potential of Deep Eutectic Solvents in the Upstream Oil and Gas Industry

Hamdi, Zakaria (Heriot-Watt University) | Koshekov, Shaberdi (Politecnico Di Torino) | Bataee, Mahmood (Curtin University Malaysia)

Abstract Oil and gas will be the main part of our future energy sources, despite of emerging and expanding of renewable energies. Enhanced Oil Recovery (EOR) plays an important role in the future oil and gas industry as the conventional oil reserves will shrink. Heavy oil reservoirs will be the main target of EOR methods because of the high number of existing heavy oil reservoirs. Surfactants are the most efficient chemical EOR method for many unconventional reservoirs as previous studies suggest. The problem with this EOR method is that these projects have high costs and raised environmental concerns. Ionic liquids (ILs) are introduced as an alternative material to surfactants, however, the cost of their synthesis and purification processes are high. Besides, some of them are toxic and have non-biodegradable properties which limit their commercial usage. Recently, a new form of ILs produced and called Deep Eutectic Solvents (DESs). The discovered material is more affordable and environmentally friendly and hence, it is considered to be an alternative material for existing conventional ILs. DESs are cheap, easy to produce, non-toxic, reusable, bio-degradable, and environmentally friendly. These materials consist of two or more cheap and safe components which will form a eutectic mixture. The melting point of the final mixture is lower than its components. In this study, the effectiveness of DESs in the EOR is analysed and evaluated to consider it as a new injection material for chemical EOR. This material has specific properties which improve the efficiency of EOR processes. Some of the favourable properties are stable emulsion between phases, interfacial tension (IFT) reduction, wettability change, recovery enhancement, and avoiding formation damage which is discussed and analysed in this paper. Moreover, the cost of the process is hugely reduced compared with other chemical injection methods. As the result, the main factor for the recovery enhancement is wettability alteration and the chance of viscosity. Besides, only malonic and acid-based DESs formed emulsions with oil, and the other types of DESs did not show emulsification properties. The IFT value increased for heavy oil reservoirs, while for reservoirs with light/medium oil IFT was reduced. Furthermore, DESs did not show formation damage which is a bonus point for this method. As the final result, Choline Chloride Glycerol showed the best recovery with an extra 30% to the original production.

doi: 10.2118/214427-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

SPE-214427-MS

Country:

Asia > Middle East (0.47)
Europe > Austria (0.28)

Genre: Research Report > New Finding (1.00)

Industry:

Energy > Oil & Gas > Upstream (1.00)
Materials > Chemicals > Commodity Chemicals > Petrochemicals (0.75)

SPE Disciplines:

Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Oil sand, oil shale, bitumen (1.00)
Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)

Reactive Transport Modelling of H2 Storage in Depleted Gas Fields: An Approach to Implement Biogeochemical Reactions in a Compositional Reservoir Simulator

Abstract The demand for large scale energy storage has been increasing for the integration of highly fluctuating energy production from renewables. Depleted gas fields are among the most suitable candidates for underground hydrogen storage, with well-known high-quality reservoir petrophysical characteristics, huge storage capacities and good sealing. However, biogeochemical interactions of hydrogen with rock-brine-resident gas could lead to hydrogen degradation as it is a favoured substrate for many anaerobic microorganisms. Thus, reservoir-scale predictive tools able to simulate these complex and tightly coupled physical, chemical, and biological phenomena are necessary for better investment decisions. A novel approach to model underground hydrogen storage biogeochemical reactions in a commercial compositional reservoir simulator is presented, tested, and analyzed. The significance of this work is the inclusion of bacterial exponential growth and decay in the numerical models which is essential for a more realistic prediction of hydrogen behaviour in subsurface. This has been embedded in a well-known reservoir simulation tool, GEM unconventional and compositional reservoir simulator, frequently used in the oil and gas industry for subsurface 3D problems. First, a conceptual biogeochemical model was conceived, and the underlying reactions were identified. The reaction mechanisms allow to consider the tight coupling between biochemical and geochemical processes. Then, a set of numerical cases, based on the conceptual biogeochemical model, were simulated in batch mode using two software: PHREEQC geochemical code and GEM reservoir simulator. The cases follow a step increase in the model complexity by adding bacterial growth and decay. GEM does not support the Monod kinetics which describes the microorganism's growth; thus, a tuning of the Arrhenius equation parameters was performed to match the Monod formula over the substrate(s) concentrations of interest. Finally, the Arrhenius formulation was further customized to include bacterial exponential growth and decay by an adequate bacterial stoichiometry implementation in which the bacteria was defined as molar aqueous component. The numerical simulations proved that a properly tuned Arrhenius kinetic model may reproduce the Monod dynamics with acceptable accuracy. In addition, for the most complete and complex case (D), GEM results show a good benchmark with PHREEQC ones, attesting the fact that a properly customized Arrhenius model, integrating the kinetics of both substrates and bacteria, and being modelled with a single (or two if decay is also considered) stoichiometric reaction, is able to appropriately capture underground hydrogen storage biogeochemical reactivity. In the cases considered, results show that the geochemistry has a limited impact on the biochemical process. However, the impact depends on pure geochemical limiting factors, i.e., presence of free protons. The study recommends that the estimation of kinetic parameters of biological processes (e.g., Methanogenesis) should be prioritized in future experimental campaigns to better understand their influence on underground hydrogen storage.

doi: 10.2118/214434-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

SPE-214434-MS

Country:

North America > United States (0.46)
Europe > Austria (0.28)

Genre:

Research Report > New Finding (0.86)
Research Report > Experimental Study (0.54)

Industry: Energy > Oil & Gas > Upstream (1.00)

SPE Disciplines:

Reservoir Description and Dynamics > Storage Reservoir Engineering > Natural gas storage (1.00)
Reservoir Description and Dynamics > Reservoir Simulation (1.00)
Reservoir Description and Dynamics > Reservoir Characterization (1.00)

Technology:

Information Technology > Software (0.46)
Information Technology > Modeling & Simulation (0.34)
Information Technology > Artificial Intelligence > Representation & Reasoning (0.34)