This session will look at capturing the characteristics of a reservoir at a suitable scale for the EOR process and understanding.
For any application of results of detailed EOR core analysis, there must be a feasible framework to capture this into the shared earth model. Most commonly a 3D static model is used. Any such model that represents the reservoir, that captures a best possible understanding of the behavior of fluid movements in the field in discussion for EOR, is of value. This would include investigations of deviations and ranges of this model.
Fluid flow in the reservoir is of main importance for EOR modeling, where factors like capturing the stratigraphic and structural framework in detail, understanding of and being able to position the depositional environment(s) and its properties within such a framework, and, where applicable, understanding of flow paths along and/or across barriers (structural or depositional), are of importance.
Fluid characterization is also critical component in the understanding the fluid flow in the porous media. EOS modeling and variation in fluid properties with various injectants during various EOR processes has to be captured and defined accurately in the Reservoir rock-fluid characterization.
Laboratory studies of EOR processes are an integral part of EOR screening and evaluation of process suitability for reservoir types. Laboratory experiments are performed to understand the basic mechanisms and to quantify the incremental recovery benefits under controlled conditions These studies help in understanding the EOR inputs, efficacy of the process, interaction between injectants and rock and fluid. However, to scale up the results from the simple laboratory experiment to a pilot or field scale requires the help of numerical modeling. History matching of laboratory experiments results viz, miscible gas flooding, iWAG, ASP, and FAWAG flooding; In-situ Combustion (ISC) tube experiments helps to understand the basic physics, fluid flow behaviour at micro scale and firming up the important input data, viz reaction kinetics, IFT and change in relative permeability curves and ROS, adsorption of chemicals etc. for full field simulation. Thus, simulation of the experiments helps in the tuning of these parameters to adequately mimic the process at the laboratory scale. This study helps to understand the injectants rate, timing, slug size, adsorption of chemicals, generation, destruction and regeneration of foams, residual oil saturation and its distribution and impact of by-products like Asphaltene precipitation, emulsion etc. on the recovery process. Relative permeability and effect of hysteresis plays important role in the estimation of incremental oil due to EOR processes. Simulation of relative permeability experiments along with hysteresis mechanism provides insight of fluid flow in rock and realistic estimates of saturation end points and saturation path.
This session will present and discuss how simulation of complex EOR laboratory experiments is being used to gain better understanding, and how it is helpful in designing the EOR processes at pilot/field scale. Understanding of scale up issues associated with converting the core flood results to pilot or field scale is also critical for the successful designing.
Hydrocarbon exploration and production are inherently risky activities. Reservoir development plans and management decisions depend on geological, economic, and technological uncertainties that can have varied impact on EOR projects and may be affected by the reservoir characteristics, recovery mechanism, and stage of field development.
Reservoir uncertainties could be static or dynamic. The level of uncertainties is dependent on the source and quality of subsurface data capture and processing. Identifying and narrowing of the range of uncertainties is a critical process in developing a robust numerical simulation model to estimate reservoir potential and make sound decisions regarding EOR field development.
EOR projects are complex and costly. As a major step from a laboratory to full field application, a pilot test to assess processes and economics of a particular application can be crucial in reducing project risk and designing a successful full field application. Simulation of the pilot test is important and there are many issues that need to be considered. Reservoir modeling of the pilot area with appropriate boundary conditions (confined vs. unconfined and interference from outside the pilot area), selecting the well/grid system and determination of the initial waterflood baseline are all key steps.
The utilisation of analytical solutions and the learning through previous pilot testing are important. Particular importance should be placed on analysis of pilot results with history matching based on relevant and reliable data obtained as part of the pilot. The importance of working with all members of the asset team is stressed.
Understanding mechanisms of multi-phase flow and displacement through porous rocks is crucial for reliable modeling and simulation of oil recovery under various EOR techniques. The outcome of the complex interplay of the factors affecting multi-phase flow including two- and three-phase relative permeability, capillary pressure, and hysteresis is difficult to predict and cannot be adequately accounted for in the current standard approach used in the oil industry.
In this session, we present recent improvements in our understanding of the physics of multi-phase flow in porous media as well as the new tools and approaches being developed for more accurate mathematical modeling and numerical simulation of oil recovery by various EOR techniques. Recent advancements in the modelling of gas, water-alternating-gas (WAG), and simultaneous gas and water (SWAG) injection will also be discussed and the validity of the formulation used in existing simulators will be evaluated.
Of critical importance to any EOR process is accurately representing how the injected agent contacts the remaining oil. Since this is a pore and core scale process, how we upscale those effects and represent them in both “fine” and “coarse” scale models will reflect how useful those models are at screening likely behaviour in the field, design of subsequent pilots, and, ultimately, full field implementations.
This session will include both the upscaling of core and lab scale results into suitable reservoir scales, as well as downscaling field measurements to allow calibration of screening and process model. Discussion topics are closely related to Session 2 on capturing the reservoir heterogeneity and characterisation and Session 4 on honouring the field imaging resolutions and will build on those discussions, aiming to address the key question “what scale should we actually screen at?”
Full-field simulation is a useful tool to forecast reservoir performance, to identify regions of unswept oil, and to optimize recovery from an EOR process. An accurate reservoir simulator that simulates and models the physics of the EOR process is based on an accurate description of the reservoir incorporating the reservoir heterogeneity. Accurate reservoir description provides a strong basis for history matching to results in a dynamic description that can be used for full-field simulations. A good definition of past and future operations is critical to make accurate reservoir forecasts. A complicating factor is where the process requires full compositional modelling, the clash between process and heterogeneity resolution and the memory restrictions placed by a large number of components required for equation of state characterisation. Use of large grid block sizes can result in unrealistic numerical dispersion that can yield errors in predicted recoveries. One approach is to generate type curves for cross-sectional fine scale descriptions and then scale these results to full-field predictions. Also data requirements and specifics of simulation of chemical, thermal, microbial EOR and low salinity water (LSW) processes at sector and field levels are targeted to be captured in this session.
Several case studies for full-field simulations will be presented and their applications towards reservoir forecasting, infill drilling, and process optimization will be discussed. Limitations of current reservoir simulators for EOR simulations will be detailed and the latest innovations in reservoir simulation will be presented.
Since numerical reservoir simulation became endemic in the oil and gas industry, it has become a crucial part of our subsurface toolbox. An over-reliance on simulators can lead to “solutions” being put forward as correct because “that’s what the simulator produced”. Clearly, the answer to this is experience and mentoring junior engineers.
In EOR simulation the answer is not necessarily so straight-forward. The systems are more complex and the number of experts is far fewer. This means, as a discipline, our understanding of the limitations of EOR is vital.
This session will discuss the various factors limiting EOR simulation. Factors ranging from simulation input (fluid properties, accurate geomodeling), through processing (understanding appropriate upscaling, incorporating pilot test results), and understanding uncertainties.
Case studies will illustrate how experienced reservoir engineers can bring the same level of professional scepticism to EOR as we bring to conventional simulation.
Reservoir management is a continuous process that spans the entire life of a field and becomes more important in fields under EOR application. Modern reservoir management approach tends to rely heavily on reservoir simulation tools in the decision making process. EOR processes are generally more complex and expensive than conventional field depletion plans and require a comprehensive monitoring and surveillance plans. As such, evaluation and mid-course corrections are more rigorous. Simulation with its strong evaluative and predictive capabilities is used as a tool to investigate multiple options and choose the optimum plan for reservoir management.
During the recent years with the increasing capability in the industry of real time data acquisition and monitoring, the need for quickly updating and integrating the latest data into reservoir models for quick reservoir management decisions has gained more importance. Also, given significant uncertainty associated with recovery forecasts from the EOR processes, there is growing emphasis on reliable quantification of these uncertainties. Optimisation tools are being routinely used in reservoir simulation these days to refine further the processes to maximise the value from the investments.
This session will look at capturing the recent trends in EOR modeling and how the companies are benefited in their decision making process. Several case histories would be presented and discussed highlighting the application of EOR modeling in reservoir management.