Layer | Fill | Outline |
---|
Map layers
Theme | Visible | Selectable | Appearance | Zoom Range (now: 0) |
---|
Fill | Stroke |
---|---|
Collaborating Authors
Computer Modelling Group Ltd
Numerical Simulation for Hydrogen Storage and Bio-Methanation
MousaviMirkalaei, Seyed Mousa (Computer Modelling Group Ltd) | Zarei, Faraj (Computer Modelling Group Ltd)
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.
- Europe (1.00)
- North America > United States > Texas > Kleberg County (0.24)
- North America > United States > Texas > Chambers County (0.24)
- Research Report > New Finding (0.69)
- Research Report > Experimental Study (0.54)
Ranking of Geologic and Dynamic Model Uncertainties for Carbon Dioxide Storage in Saline Aquifers
Ates, Harun (Aramco Americas) | Gupta, Anuj (Aramco Americas) | Chandrasekar, Vikram (Computer Modelling Group Ltd) | Vaidya, Ravimadhav (Aramco Americas) | AlMajid, Muhammad (Saudi Aramco) | Yousif, Zuhair (Saudi Aramco)
Abstract Growing concerns over global climate change is also increasing the interest in developing technologies to reduce the concentration of carbon dioxide (CO2) in the atmosphere. Geological Carbon Sequestration which injects CO2 into subsurface formations such as deep saline aquifers, depleted hydrocarbon reservoirs are some of the viable options to reduce CO2 emissions into the atmosphere. Deep saline aquifers are a particularly good choice due to their wide geographical distribution and proximity to emission sources that provide easy accessibility and storability of CO2. Saline aquifers, however, are data-poor systems that requires a thorough understanding of the impact of all factors and their uncertainties on long-term CO2 storage for risk assessment. This study considers a wide range of geologic and dynamic model uncertainties, including structural uncertainties, petrophysical heterogeneities, dynamic flow parameters and geochemical reactions to define the most critical parameters for different CO2 trapping mechanisms. Experimental design over stochastic modelling and sampling is used to minimize the computational cost of the study. A commercially available, compositional reservoir simulator with reactive transport modeling capability has been used in this study to account for the impact of potential geochemical reactions. Assumed reactive transport model considers the water solubility, ionization, and mineral trapping mechanisms of CO2 in saline reservoirs for a range of components of dissolved salts in the brine as well as the pH of the brine. Chemical reactions that may occur with the rock minerals (Kaolinite, Anorthite and Calcite) when adding the CO2 are prescribed as input into the simulator. Simulations also include effects of hysteresis and diffusion processes. Study shows that the most important parameter for all trapping mechanisms is the permeability since it controls the injection capacity. Beyond that, different combination of parameters with different range of uncertainties alter the ranking of factors influencing dissolution, ionization, hysteresis, mineralization and the movement of CO2 within the aquifer. There is no unique set of parameters that maximizes all storage mechanisms. There is a significant overlap and change in amount the amount of CO2 stored via different mechanisms depending on the parameter combinations. Study results also provide insights into how one can prioritize data gathering needs depending on the objectives, data uncertainties and their sensitivities for an aquifer site under consideration.
- Asia > Middle East (0.68)
- Europe (0.46)
- Geology > Mineral (1.00)
- Geology > Geological Subdiscipline > Geochemistry (0.71)
Application of Novel Advanced Numerical Modeling of Nanoparticles for Improved Oil Recovery: Laboratory- To Field-Scale
Hendraningrat, Luky (PETRONAS Research Sdn. Bhd) | Majidaie, Saeed (PETRONAS Research Sdn. Bhd) | Kechut, Nor Idah (PETRONAS Research Sdn. Bhd) | Tewari, Raj Deo (PETRONAS Research Sdn. Bhd) | Sedaralit, M Faizal (PETRONAS Research Sdn. Bhd) | Skoreyko, Fraser (Computer Modelling Group Ltd) | MousaviMirkalaei, Seyed Mousa (Computer Modelling Group Ltd) | Edmondson, Mark (Computer Modelling Group Ltd) | Chandrasekar, Vikram (Computer Modelling Group Ltd)
Abstract The deployment at the field-scale of a novel technique to improve oil recovery using nanoparticles injection is challenging. It requires a comprehensive evaluation of a series of laboratory experiments, to translate and validate the mechanisms into a numerical model to predict accurately and reduce uncertainty parameters. This paper describes the application of novel advanced reservoir modeling for nanoparticles from pore-scale to field-scale, using an offshore Malaysian oilfield as a pilot field case. A series of laboratory experiments (fluid-fluid and fluid-rock) and numerical studies: nanofluid formulation, pore-scale studies, validation, and upscaling process into the field-scale model were carried out. The development of nanofluids was formulated to meet key criteria such as compatibility and thermal stability at the intended field condition. Prior to coreflooding tests with native core, a series of experiments to observe mechanisms were carried out. The results of the laboratory experiments were then validated in the 1D coreflooding model. The procedure was continued with observed critical parameters being scaled-up into 3D field-scale model before running the prediction scenarios. The newly developed nanofluids for the intended field performed well in compatibility and thermal stability tests at reservoir temperature. Precipitation and sedimentation were not observed in this solution. The wettability alteration to more water-wet was observed with consistent results through interfacial tension measurements, contact angle measurements, and relative permeability measurements. Coreflooding was performed using native core, and the reduction of residual oil saturation was approximately 25% between pre- and post-nanoflooding. The adsorption of nanofluids was measured to be around 1.12 mg/g of rock. All these results were input into the model and the history match quality index achieved an acceptable match of ~95%. Several critical parameters for the upscaling process were investigated such as reaction rate of particle aggregation, adsorption, and retention factor. During the scale-up process, the velocity of the fluids and pressure drop were conserved because the recovery is sensitive to flooding rate and the viscosity of the fluids are pressure dependent. The field-scale model was run for the intended field location. The potential of using nanoparticles was evaluated and compared to the no further activity scenario giving an additional recovery factor of approximately 1% per year. The developed method of novel robust advanced reservoir modeling for nanoparticles creates a new reference as the first application in the world of novel advanced numerical modeling at field-scale.
- North America > United States > Texas (0.28)
- Europe > United Kingdom > North Sea > Central North Sea (0.25)
Evaluation of a Superior Shale EOR Application in the Eagle Ford Shale
Venepalli, Kiran K. (Computer Modelling Group Ltd) | Downey, Robert A. (Shale Ingenuity LLC) | Erdle, James C. (Computer Modelling Group Ltd) | Nohavitza, Jack (EP Energy)
Abstract Oil production from horizontal shale oil wells in the Eagle Ford began in 2008 and reached a peak of 1.65 Million BOPD in March 2015. By November, 2020, 25,210 shale oil wells were producing 754,000 BOPD. Estimated oil recovery from the Eagle Ford shale is 4 to 7 percent of OOIP. In this paper, we introduce a novel EOR process, designated herein as "superEOR" that can increase the production and recovery of oil from the Eagle Ford shale much more than natural gas or CO2, while reducing the cost per barrel of recovered oil, and the environmental impacts of oil production. A superior shale oil EOR method is proposed that utilizes a triplex pump to inject a solvent liquid into the shale oil reservoir, and an efficient method to recover the injectant at the surface, for storage and reinjection. The process is designed and integrated during operation using compositional reservoir simulation in order to optimize oil recovery. Compositional simulation modeling of Eagle Ford shale wells that have been used in a natural gas cyclic injection pilot project was conducted to obtain a history match on oil, gas, and water production. The matched model was then utilized to evaluate the shale oil EOR method under a variety of operating conditions. The modeling indicates incremental oil production of 300% over primary EUR may be achieved in the first five years of EOR operation, and more than 500% over primary EUR after 10 years. The process can be implemented at pressures below initial reservoir pressure to mitigate interwell communication, which rendered the previous cyclic natural gas injection method ineffective. The method, which is patented, has numerous advantages over cyclic gas injection, such as much greater oil recovery, much better economics/lower cost per barrel, lower risk of interwell communication, use of far less horsepower and fuel, shorter injection time, longer production time, smaller injection volumes, scalability, faster implementation, precludes the need for artificial lift, elimination of the need to buy and sell injectant during each cycle, ability to optimize each cycle by integration with compositional reservoir simulation modeling, and lower emissions. If implemented early in the life of a shale oil well, its application can slow the production decline rate, recover far more oil earlier and at lower cost, and extend the life of the well by several years, while precluding the need for artificial lift.
- 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 > Permian Basin > Wolfcamp Formation (0.99)
- (24 more...)
Advanced Reservoir Simulation: A Novel Robust Modelling of Nanoparticles for Improved Oil Recovery
Hendraningrat, Luky (Petronas Research Sdn. Bhd) | Majidaie, Saeed (Petronas Research Sdn. Bhd) | Ketchut, Nor Idah (Petronas Research Sdn. Bhd) | Skoreyko, Fraser (Computer Modelling Group Ltd) | MousaviMirkalaei, Seyed Mousa (Computer Modelling Group Ltd)
Abstract The potential of nanoparticles, which are classified as advanced fluid material, have been unlocked for improved oil recovery in recent years such as nanoparticles-assisted waterflood process. However, there is no existing commercial reservoir simulation software that could properly model phase behaviour and transport phenomena of nanoparticles. This paper focuses on the development of a novel robust advanced simulation algorithms for nanoparticles that incorporate all the main mechanisms that have been observed for interpreting and predicting performance. The general algorithms were developed by incorporating important physico-chemical interactions that exist across nanoparticles along with the porous media and fluid: phase behaviour and flow characteristic of nanoparticles that includes aggregation, splitting and solid phase deposition. A new reaction stoichiometry was introduced to capture the aggregation process. The new algorithm was also incorporated to describe disproportionate permeability alteration and adsorption of nanoparticles, aqueous phase viscosities effect, interfacial tension reduction, and rock wettability alteration. Then, the model was tested and duly validated using several previously published experimental datasets that involved various types of nanoparticles, different chemical additives, hardness of water, wide range of water salinity and rock permeability and oil viscosity from ambient to reservoir temperature. A novel advanced simulation tool has successfully been developed to model advanced fluid material, particularly nanoparticles for improved/enhanced oil recovery. The main scripting of physics and mechanisms of nanoparticle injection are accomplished in the model and have acceptable match with various type of nanoparticles, concentration, initial wettability, solvent, stabilizer, water hardness and temperature. Reasonable matching for all experimental published data were achieved for pressure and production data. Critical parameters have been observed and should be considered as important input for laboratory experimental design. Sensitivity studies have been conducted on critical parameters and reported in the paper as the most sensitive for obtaining the matches of both pressure and production data. Observed matching parameters could be used as benchmarks for training and data validation. Prior to using in a 3D field-scale prediction in Malaysian oilfields, upscaling workflows must be established with critical parameters. For instance, some reaction rates at field-scale can be assumed to be instantaneous since the time scale for field-scale models is much larger than these reaction rates in the laboratory.
- Asia (0.69)
- North America > United States (0.60)
Abstract La Cira Infantas (LCI) is the oldest oilfield in Colombia, with 100 years of oil production history spanning three periods: primary depletion, the first waterflood (WF) period, and the second WF period. After the first WF period, the field had neared its economic limit and an abandonment program was underway from 2003 to 2005. Partners Ecopetrol and Occidental made the decision to implement a waterflood redevelopment project in 2005 that included reconfiguration of the old WF areas and WF expansion into new areas. The partners formed integrated reservoir development and management teams (RDT and RMT) that have combined workovers, infill drilling, WF optimization, and other IOR/EOR methods. The oil production has increased from approximately 5,000 to over 43,000 bopd, which is above the predicted 40,000 bopd. One of the key components was WF conformance controls to improve sweep efficiency and to improve injection profiles across multiple stacked-sand layers. The selective injection method was implemented using multiple packers and side-pocket mandrels/valves. The design of selective injection strings involved complex engineering calculations and left some room for improvement. This paper describes a new workflow used to optimize the selective injection design using multiphase flow simulation based on actual WF patterns. A field pilot test used an inverted 5-spot WF pattern to demonstrate this new workflow. The simulation results predicted a 45% incremental oil production above the base case. The simulation optimization process reduced the number of mandrels/valves from nine to six, which saves about 30% of the associated completion costs compared with the initial completion proposal for this case study.
- South America > Colombia > Santander Department (1.00)
- Europe > United Kingdom > North Sea > Central North Sea (0.24)
- South America > Colombia > Tolima Department > Middle Magdalena Basin > Casabe Field (0.99)
- South America > Colombia > Santander Department > Middle Magdalena Basin > La Cira Infantas Field (0.99)
- South America > Colombia > Santander Department > Middle Magdalena Basin > Casabe Field (0.99)
- (5 more...)
Abstract Fluid-rock interactions can modify certain reservoir properties, notably porosity, permeability, wettability, and capillary pressure, and they may significantly influence fluid transport, well injectivity, and oil recovery. The profound influence of low-salinity-brine flooding is primarily based on wettability alteration, while that of CO2 flooding is based on oil swelling, viscosity reduction, and interfacial tension reduction. Low saline brine, when combined with CO2, leads to higher CO2 solubility and diffusion, and increased brine acidity. The low-salinity-brine-CO2 injection further contributes to the synergy of mechanisms underlying the two processes to improve oil recovery. A reactive transport model, which uses surface complexation reactions (SCR) to describe the equilibrium between the rock surface sites and ion species in the brine solution coupled with transport equation, was developed to predict a set of low-salinity-brine-CO2 flooding experiments conducted on carbonate rocks. While conducting batch simulations of the model, it was shown that the thermodynamic parameters reported in the literature for SCRs in a rock–brine system are not suited to natural carbonate rocks. The same thermodynamic parameters could not fit the model to experimental zeta potential data with pulverized and intact carbonate cores at varying potential determining ion concentrations. The model was further utilized to predict the effluent compositions of potential determining ions in single-phase flooding experiments on natural carbonate cores. The failure of thermodynamic parameters in the prediction of reactive transport single-phase experiments, implies that zeta potential is not enough to optimize such parameters for the reactive transport model. The reactive–transport model parameters were fitted to the single-phase experiments and a temperature-dependent relationship was generated for the thermodynamic parameters. Then, the optimized model was used in investigating the equilibrium between rock, oil and brine in a set of low-salinity-brine-CO2 flooding experiment. The model showed an incremental recovery of 28% over the formation water flooding, similar to the reported recovery from the experiment. The simulation results show that the incremental recovery can be associated with increased CO2 solubility leading to the formation of in-situ carbonated water to reduce interfacial tension and alter wettability. The performance of low-salinity-brine-CO2 flooding in terms of oil production, relative injectivity, and CO2 storage was evaluated on a field case study using field-specific injection parameters. The results demonstrate that the water injected, and injection scheme has a substantial influence on injectivity and oil production. The injectivity was significantly greater for the water-alternating-gas injection, mainly because the rock surface has an increased contact time with CO2-saturated brine. Meanwhile, carbonated water injection shows greater injectivity compared to formation water and low-salinity-brine, and also has higher oil recovery compared to low salinity waterflood and conventional waterflood in the respective order.
- Asia (1.00)
- North America > United States > Texas (0.68)
- Research Report > New Finding (1.00)
- Research Report > Experimental Study (1.00)
- Geology > Geological Subdiscipline (1.00)
- Geology > Rock Type > Sedimentary Rock > Carbonate Rock (0.89)
- Energy > Oil & Gas > Upstream (1.00)
- Government > Regional Government > North America Government > United States Government (0.46)
Field Surveillance and AI based Steam Allocation Optimization Workflow for Mature Brownfield Steam Floods
Kumar, Anjani (Computer Modelling Group Ltd) | Novlesky, Alex (Computer Modelling Group Ltd) | Bityutsky, Erykah (Computer Modelling Group Ltd) | Koci, Paul (Consultant for Occidental Petroleum Corporation) | Wightman, Jeff (Occidental Petroleum Corporation)
Abstract Heavy oil reservoirs often require thermal enhanced oil recovery (EOR) processes to improve the mobility of the highly viscous oil. When working with steam flooding operations, finding the optimal steam injection rates is very important given the high cost of steam generation and the current low oil price environment. Steam injection and allocation then becomes an exercise of optimizing cost, improving productivity and net present value (NPV). As the field matures, producers are faced with declining oil rates and increasing steam oil ratios (SOR). Operators must work to reduce injection rates on declining groups of wells to maintain a low SOR and free up capacity for newer, more productive groups of wells. Operators also need a strong surveillance program to monitor field operational parameters like SOR, remaining Oil-in-Place (OIP) distribution in the reservoir, steam breakthrough in the producers, temperature surveys in observation wells etc. Using the surveillance data in conjunction with reservoir simulation, operators must determine a go-forward operating strategy for the steam injection process. The proposed steam flood optimization workflow incorporates field surveillance data and numerical simulation, driven by machine learning and AI enabled Algorithms, to predict future steam flood reservoir performance and maximize NPV for the reservoir. The process intelligently determines an optimal current field level and well level injection rates, how long to inject at that rate, how fast to reduce rates on mature wells so that it can be reallocated to newly developed regions of the field. A case study has been performed on a subsection of a Middle Eastern reservoir containing eight vertical injectors and four sets of horizontal producers with laterals landed in multiple reservoir zones. Following just the steam reallocation optimization process, NPV for the section improved by 42.4% with corresponding decrease in cumulative SOR by 24%. However, if workover and alternate wellbore design is considered in the optimization process, the NPV for the section has the potential to be improved by 94.7% with a corresponding decrease in cumulative SOR by 32%. This workflow can be extended and applied to a full field steam injection project.
- Geology > Petroleum Play Type > Unconventional Play > Heavy Oil Play (0.69)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.46)
Abstract In the United Kingdom Continental Shelf (UKCS), a significant heavy oil prize of 9 billion barrels has been previously identified, but not fully developed. In the shallow unconsolidated Eocene reservoirs of Quads3 and 9, just under 3 billion barrels lie in the discovered, but undeveloped fields, of Bentley and Bressay. Discovered in the 1970s, they remain undeveloped due to the various technology challenges associated with heavy oil offshore and the presence of a basal aquifer. The Eocene reservoirs represent significant challenges to recovery due to the unconsolidated nature of the hydrocarbon bearing layers. The traditional view has been that such a nature represents a risk to successful recovery due to sand mobility; reservoir and near wellbore compaction; wormhole formation; and injectivity issues. We propose improving the ultimate oil recovery by a combination of aquifer water production and compaction drive. By interpreting public domain data from well logs, the range of geomechanical properties of Eocene sands have been determined. A novel approach to producing the heavy oil unconsolidated reservoirs of the UKCS is proposed by producing the aquifer via dedicated water producers situated close to the oil-water contact. The location was determined by sensitivity analysis of water producer location and production rates. By locating water producers at the OWC with a production rate of 20,000 bbls/day of fluids, the incremental recovery at the end of simulation is increased by 4.1% OOIP of the total modelrelative to the ‘no aquifer production’, casesuggesting a significant increase in recovery can be achieved by producing the aquifer. A rate of 30,000 bbld/day located at the OWC was found to increase incremental recovery by 5.8 %OOIP relative to the ‘no aquifer case’. In all cases, as the reservoir fluid pressure is reduced, oil recovery increases via compaction and reduced water influx into the oil leg. This reduced pressure leads to a higher tendency towards reservoir compaction which is expressed as a change in mean effective stress and porosity reduction.
- North America > United States (1.00)
- Europe > United Kingdom > North Sea > Northern North Sea (0.68)
- Geology > Petroleum Play Type > Unconventional Play > Heavy Oil Play (1.00)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (0.31)
- Europe > United Kingdom > North Sea > Northern North Sea > Viking Graben > P1078 > Dornoch Formation (0.99)
- Europe > United Kingdom > North Sea > Northern North Sea > Viking Graben > P1078 > Block 9/3b > Bentley Field > Dornoch Formation (0.99)
- Europe > United Kingdom > North Sea > Northern North Sea > East Shetland Basin > P 1575 > Block 9/2c > Kraken Field > Heimdal Formation (0.99)
- (25 more...)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Oil sand, oil shale, bitumen (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Reservoir geomechanics (1.00)
- (4 more...)
A Geochemical Model for Investigation of Wettability Alteration during Brine-Dependent Flooding in Carbonate Reservoirs
Awolayo, Adedapo (University of Calgary) | Sarma, Hemanta (University of Calgary) | Nghiem, Long (Computer Modelling Group Ltd) | Emre, Gorucu (Computer Modelling Group Ltd)
Abstract The impact of brine salinity and compositions on improving brine-dependent recovery processes has been an active research area over the past two decades. Various studies have demonstrated an improvement in oil recovery, attributed predominantly to the ability of the brine to alter rock’s wettability towards water-wetness. The proposed hypothesis is that the wettability of carbonate rocks is altered due to desorption of oil carboxylic groups from rock surfaces by the adsorbed sulfate, while the divalent cations are co-adsorbed. We developed a reactive transport model to test this hypothesis and considered wettability alteration through geochemical interactions among brine, oil and rock surface. In this model, we used various reaction pathways to account for the competition between oil acid-groups and active ionson the rock surface. The equations developed from various reactions are coupled with multiphase flow equations to control flow functions that ultimately determine the oil recovery. The model we developed was used to investigate the effects of ionic variations during carbonate coreflooding experiments. Thereafter, we extended DLVO (Derjaguin, Landau, Verwey and Overbeek) theory of surface forces to explain the molecular interactions between rock−brine−oil system by generating interfacial disjoining pressure and interaction energy. The model was tested by matching and predicting results from recently published flooding experimental studies related to ionically-modified brines conducted under single-phase and two-phase flow conditions. In these experiments, sulfate concentration in seawater was halved and quadrupled, and compared to injections of formation water and seawater. We found remarkable agreement with the produced ion histories reported from the single-phase tests, although there were delays in the produced sulfate concentration because of retention within the core. For two-phase experiments, the model yielded excellent replication of the produced ion histories and oil recoveries obtained during injection of various brines. Results show that increasing sulfate while maintaining the concentration level of other ions improved oil recovery up to 10% OOIP. However, when sulfate was reduced, neither additional oil was recovered nor sulfate ion production was delayed. Application of DVLO theory shows that disjoining pressure, which dictates the water film thickness, is extremely sensitive to sulfate content of the brine. Brines with more sulfate content exhibit higher disjoining pressure and energy barrier compared to brines with fewer sulfates. This suggests that increasing sulfate in the injected brine is essential to alter rock wettability.
- North America > United States (1.00)
- Europe (0.67)
- Asia > Middle East > UAE (0.29)
- Research Report > New Finding (1.00)
- Research Report > Experimental Study (0.86)
- Geology > Mineral (1.00)
- Geology > Geological Subdiscipline > Geochemistry (1.00)
- Geology > Rock Type > Sedimentary Rock > Carbonate Rock (0.89)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Carbonate reservoirs (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)
- Reservoir Description and Dynamics > Formation Evaluation & Management (1.00)