Dominique Guerillot

This paper proposes building realistic synthetic models of carbonate reservoirs typical of those frequently occurring in the Middle East, particularly in the State of Qatar. Based on published data, these models represent the Upper Jurassic Arab C and D reservoirs which are among the most abundant and economically important. They are well studied and most of the reservoir data is available in literature. In these models, the rock and fluid properties are based on actual fields. Developing and upgrading these models with partners and sponsors will lead to advanced reservoir engineering workflows for enhancing oil recovery, screening and benchmarking various innovative scenarios of field development and uncertainty assessment. This stimulates effective collaboration, knowledge and expertise sharing and establishes better practices in carbonate reservoir engineering.

January 1992 The simplest representation of a reservoir is a homogeneous tank with uniform properties throughout. Characterizing such a simplified model requires merely enough data to define its volume and basic petrophysical properties. This information can then be used to help forecast reservoir behavior and compare possible production scenarios. But efficient exploitation of reserves requires a more sophisticated approach. Reservoirs have been created by complex sedimentary and diagenetic processes, and modified by a history of tectonic change. Rather than resembling simple tanks, reservoirs are heterogeneous structures at every scale. The need for accurate characterization is vital for oil company economic planning (next page, top). In the past, geologists have used expert knowledge to interpolate between wells and produce basic reservoir models. However, during the last ten years, this effort has been transformed by statistical modeling offering insight into the effects of hete...

This paper presents a realistic synthetic case study based on data and materials integrated from public domain research carried out by the authors. The selected geological formation contains an abundance of oil reserves in the Middle East, and is classified among the most economically important. In comparison with on-site well testing operations, the computer-based workflow used in this study does not require to shut in any well or change production. Hence, the oil field production and water injection can be maintained suitably and sustainably. It is proposed to build multi-layered sector models to better capture both overall regional reservoir behavior and local effects between alternating rings of production and injection wells, even between individual multi-lateral wells and in the wellbore vicinity. It is shown that different horizontal variogram range influences phase productivity indices of wells, which may highly impact the accuracy and precision of production forecasts in pl...

This paper is dedicated to the modeling, analysis, and numerical simulation of a two-phase non-Darcian flow through a porous medium with phase-coupling. Specifically, we introduce an extended Forchheimer–Darcy model where the interaction between phases is taken into consideration. From the modeling point of view, the extension consists of the addition to each phase equation of a term depending on the gradient of the pressure of the other phase, leading to a coupled system of differential equations. The obtained system is much more involved than the classical Darcy system since it involves the Forchheimer equation in addition to the Darcy one. This model is more appropriate when there is a substantial difference between the phases’ velocities, for instance in the case of gas/water phases, and applications in oil recovery using gas flooding. Based on the Buckley–Leverett theory, including capillary pressure, we derive an explicit expression of the phases’ velocities and fractional wat...

Summary The mechanistic foam population balance (PB) model has clear physics, but it is generally challenging to be applied due to the high computational cost and the difficulty for determining a number of kinetic foam parameters. In this presentation, a simplified mechanistic foam PB model was developed and applied for simulating enhanced oil recovery (EOR) process in the laboratory. An improved foam coalescence function for oil destabilizing effect and dry-out effect on foam was incorporated into the mechanistic foam PB model, and a simplified mechanistic foam PB model was obtained after local equilibrium approximation. The simplified mechanistic foam PB model was first validated by fractional flow theory. Then, it was applied for history matching an efficient foam EOR process performed in the laboratory. These experiments involves foam flooding tests (co-injection of surfactant and nitrogen) in the absence of crude oil, foam tests in the presence of residual oil after water flooding and a series of foam quality scan tests in the presence of residual oil after foam flooding. The parameters for oil saturation dependent function were estimated after numerical simulation of foam transport in the presence of water flooded residual oil, while the parameters for foam dry-out function was estimated after history matching the steady state foam quality scan data at residual oil saturation after foam flooding. The simulation results were also compared with those obtained from the foam PB model and foam local equilibrium (LE) model of a commercial simulator in terms of history matching quality and computational costs. It is found that the numerically calculated pressure gradient, cumulative oil recovery and effluent surfactant concentration reproduce the experimental results notably well. Both the steady-state and transient foam flows can be reproduced reasonably well by the simplified mechanistic foam PB model. Moreover, the simplified mechanistic PB model is more efficient in terms of computational cost in comparison to the full physics PB model, thereby appearing to be a potentially effective tool for modeling at field scale.

Fractional flow theory still serves as a powerful tool for validation of numerical reservoir models, understanding of the mechanisms, and interpretation of transport behavior in porous media during the Chemical-Enhanced Oil Recovery (CEOR) process. With the enrichment of CEOR mechanisms, it is important to revisit the application of fractional flow theory to CEOR at this stage. For surfactant flooding, the effects of surfactant adsorption, surfactant partition, initial oil saturation, interfacial tension, and injection slug size have been systematically investigated. In terms of polymer flooding, the effects of polymer viscosity, initial oil saturation, polymer viscoelasticity, slug size, polymer inaccessible pore volume (IPV), and polymer retention are also reviewed extensively. Finally, the fractional flow theory is applied to surfactant/polymer flooding to evaluate its effectiveness in CEOR. This paper provides insight into the CEOR mechanism and serves as an up-to-date reference...

Summary Geological Carbon Storage (GCS) consists in injecting CO2 into geological formations with the aim of storing it there for several hundreds of years and longer to reduce the amount of CO2 emitted in the atmosphere and to mitigate or slow down climate changes. This paper proposes to study a synthetic deep saline aquifer located in Qatar and the seismic response induced by a CO2 injection. We will describe the static geological model and the dynamic flow inside this model we used. The high-resolution model has been upscaled to reach a reasonable size for the fluid flow model. Then the methodology used to generate the seismic data is explained. A petro-elastic model has been used to transform the simulation model (pressure, saturation) into a synthetic seismic, which then allowed us to see the seismic response to the CO2 injection. The results appear to be dominate by the pressure build-up due to injection.

The fluid injection in sedimentary formations may generate geochemical interactions between the fluids and the rock minerals, e.g., CO2 storage in a depleted reservoir or a saline aquifer. To simulate such reactive transfer processes, geochemical equations (equilibrium and kinetics equations) are coupled with compositional flows in porous media in order to represent, for example, precipitation/dissolution phenomena. The aim of the decoupled approach proposed consists in replacing the geochemical equilibrium solver with a substitute method to bypass the huge consuming time required to balance the geochemical system while keeping an accurate equilibrium calculation. This paper focuses on the use of artificial neural networks (ANN) to determine the geochemical equilibrium instead of solving geochemical equations system. To illustrate the proposed workflow, a 3D case study of CO2 storage in geological formation is presented.

In a reservoir, gravity forces lead fluids to stratify according to their density, and transitions zones appear around contacts (water-oil and gas-oil contacts). These transitions zones are gradual variations of saturation of each phase. These saturations are often generated using geostatistical methods leading to errors in the calculations of fluid in place. They must be calculated in a physical manner using capillary pressure curves associated with lithofacies. In this paper, a physical volumetric method to calculate the hydrocarbon in place with a high-resolution geological model is used on data coming from a synthetic field: the Brugge field. The uncertainties on hydrocarbons in place are evaluated using the Monte-Carlo method.

Waterflooding is the main technic to recover hydrocarbons in reservoirs. For a given set of wells (injectors and producers), the choice of injection/production parameters such as pressures, flow rates, and locations of these boundary conditions have a significant impact on the operating life of the wells. As a large number of combinations of these parameters are possible, one of the critical decision to make is to identify an optimal set of these parameters. Using the reservoir simulator directly to evaluate the impact of these sets being unrealistic considering the required number of simulations, a common approach consists of using response surfaces to approximate the reservoir simulator outputs. Several techniques involving proxies model (e.g., kriging, polynomial, and artificial neural network) have been suggested to replace the reservoir simulations. This paper focalizes on the application of artificial neural networks (ANN) as it is commonly admitted that the ANNs are the most ...

Decisions for field development of oil and gas reservoirs are often based on uncertainties assessment on forecast productions and other variables which are highly impacted by the uncertainties on the reservoir characteristics. Using geostatistical models, it would require thousands of flow simulations of several hours each to consider the geological uncertainties. Each of these simulations would require several hours even with current high power computers. To bypass this restriction due to the computation time, one approach consists to replace the simulator by an approximation of it, also called proxy. This paper focuses on the use of Artificial Neural Networks (ANN) proposing an innovative method to build an optimal ANN.

The geological static models of realistic contexts are described with high resolution meshes (HRM) and cannot be directly used as input for fluid flow reservoir simulators due to memory and/or running time constraints. The pragmatic approach consists in averaging the high resolution petrophysical values to assign to a low resolution mesh (LRM) used to perform reservoir simulations. Hence, predictions made with these coarser meshes are inevitably less accurate than those that would have been obtained on HRM. For compositional modelling, the loss of accuracy due to upscaling processes will come not only for the component displacements but also from the solution of the thermodynamic and/or geochemical equilibrium equations. For example, a chemical reaction of an acid on carbonated rock may highly depends on its concentration. Therefore, our main motivation here is to keep an HRM for calculating those chemical equilibriums. We propose to name this innovative approach “Compositional Dual Mesh Method” (CDMM). The CDMM is a formulation with two different meshes: The pressure equation is solved on a LRM using upscaled properties and the transport equation and chemical equilibrium are solved on a HRM.

Summary The feasibility of foam enhanced oil recovery (EOR) for a heterogeneous carbonate reservoir in the Middle East with medium temperature (55°C) and high formation salinity (above 16% TDS) is presented here. The promising surfactant formulations were firstly evaluated based on solubility tests and bulk foam tests. Afterwards, a series of core flooding experiments both in the absence and in the presence of crude oil were performed on Estaillades Limestone, a heterogeneous carbonate presenting reasonable similarities with the actual formation. In these foam tests, the influence of foam quality, injection velocity and surfactant concentration on foam strength and incremental oil recovery were investigated. Then, the lab results were reproduced by numerical simulation using a commercial reservoir simulator, where the model parameters were obtained after history matching. Finally, a synthetic 2D heterogeneous model was established to investigate how foam can assist in improving oil recovery for a stratified heterogeneous reservoir. An Alkyl Poly-Glycoside (APG) surfactant was firstly selected based on its prominent foamability and foam stability from bulk foam tests. The optimal foam quality is found to be around 70% from foam quality scan tests in the absence of crude oil. Moreover, foam still can be generated under strongly oil-wet conditions, and it is observed that the presence of oil and surfactant concentration have negligible effects on the optimal foam quality. However, the foam strength in high quality scheme is largely dependent on the surfactant concentrations. More than 20% OOIP of the water flooded residual oil was recovered after co-injecting 5.0 total pore volume (TPV) of nitrogen and 0.5 wt.% APG surfactant (in synthetic seawater brine) at 70% foam quality (4 ft./d). The numerical simulation results indicate that the permeability effect on foam strength and foam stability need to be considered in order to accurately model the foam behavior in heterogeneous reservoirs. In this presentation, the foam dry-out, shear thinning, surfactant concentration, permeability and oil saturation effects on foam transport in a heterogeneous carbonate were systematically investigated. The results of this study demonstrated the feasibility of foam EOR for a strongly oil-wet and heterogeneous carbonate reservoir with medium temperature and high formation salinity.

... Various studies carried out using this software package are described in this article in order to point out the possible utilisations : 1. An industrial crystalizer 2. A new membrane reactor for large-scale mammalian cell cultures 3. A waste-water treatment plant primary clarifier 4. A ...