Xian, Hong (Shell Global Solutions International BV) | Tueckmantel, Christian (Shell Global Solutions International BV) | Giorgioni, Maurizio (Shell Global Solutions International BV) | Wei, Lingli (Shell Global Solutions International BV) | Lai, Chee-Pan (Sabah Shell Petroleum Company Ltd)
The methodology of image feature and in particular fracture recognition, extraction and characterisation is based on the borehole image tool button response simulation model originally developed by Luthi (1990) for the water-based mud system and the principle of 2D fracture intensity (P32) to 3D fracture intensity/ volume (P33) transformation. The extracted conductive image features allow us to distinguish open fractures and karst features. Fracture aperture is calculated as a function of the button resistivity, tool current & voltage, mud resistivity and background rock resistivity. Fracture porosity is computed with consideration of fracture type, well type and condition. Fracture permeability is estimated by taking fracture aperture, type and intensity into account.
Alkaline-Surfactant-Polymer (ASP) injection into an oil reservoir triggers a series of geochemical reactions including reservoir mineral dissolution and precipitation of scales inside the reservoir and wellbores. Modelling these reactions is important for understanding the processes and designing the ASP formulation for optimal oil recovery. A number of reactive transport modelling (RTM) approaches have been reported in the literature so far, but none has addressed the importance of a geochemical database underpinning such simulations considering both equilibrium and kinetic reactions. In the meantime, experimental data available outside the oil industry can be used for calibrating reservoir mineral dissolution equilibrium constants in high pH solutions. In this paper, experimental data of dissolution of relevant reservoir minerals and precipitation of scale minerals are compiled and compared with predictions from the widely used geochemical modelling software PHREEQC. A new database calibrated to the experimental data is developed in PHREEQC format that can be used in Shell in-house reservoir simulator MoReS for ASP flood reactive transport simulations. In order to reproduce the sequence of the observed scale deposition during an ASP flood project, the kinetic rate laws for the mineral dissolution and precipitations have also been calibrated against the experimental data. Significant differences in the predicted mineral dissolution and precipitation between the calibrated database and the one from the official PHREEQC release demonstrate the necessity of geochemical database calibration for high pH environments.
In tight reservoirs development such as shale gas it is important and yet difficult to predict the size and orientation of the drainage area around a hydraulically fractured well. Often the drainage area is determined by near-well fractures. Diagnostic fracture injection test (DFIT) is an effective way of predicting many reservoir parameters. However, it is challenging to uniquely interpret fractures’ geometry, dimension and spacing. A forward model is desired to correlate the DFIT responses with different fracture configurations and the associated drainage area.
We present a 2D model that couples fluid flow with geomechanical deformations in hydraulically fractured reservoirs by solving Biot's equation. Both fluid pressure/velocity and deformations are solved on a finite element mesh. Fracture space is distinguished from the rest of the matrix by high porosity/permeability and low elastic strength. The FEM mesh is adaptively refined at the fractured area to allow the fractures to be reasonably thin and arbitrarily spaced. Pseudo time iteration is applied to seek for convergence between fracture opening/closure and fluid pressure changes. DFIT is simulated with the new numerical model with a single (bi-wing) fracture case and a complex fracture case. The complex fracture case is made by adding transverse fractures to the two wings of a single fracture. The numerical results reveal pressure changes of reservoir fluid due to matrix and fracture deformations as well as due to fluid leak-off. The model is able to generate synthetic well pressure data that show all the type curves given by analytical DFIT theory. The complex fracture case results in pressure transient such that the flow regime rapidly evolves into pseudo-radial flow.
For idealized bi-wing fracture cases, this model is consistent with existing analytical tools for DFIT interpretation. The advantages of this model are the ability to implement complex fractures, and the ability to extend to 3D for non-vertical fractures (briefly mentioned in the appendices).
Synthetic DFIT data from the model developed in this study has been compared to a field example from a shale gas reservoir. The discrepancy between the model result and field example suggests that some special constitutive law is needed for the modeled fracture areas to appropriately capture the real fracture closure process.
When a well is subjected to production or fracturing injection, the fluid flow is likely accompanied by the solid deformation. In most cases of conventional reservoirs, the initial pore volume is much larger than the volume changes that are caused by the matrix strain with competent rock grains. For this reason, the fluid flow is often modeled independently without coupling with deformation. In the cases of tight and shale gas reservoirs however, the pore volume is comparable to the strain caused volume changes. The fluid flow modeling then needs to be coupled with the solid deformation.
We present our work on modeling a hydraulically fractured reservoir subjected to production or injection, where the fluid and solid are coupled by solving Biot's equation. The model is capable of generating synthetic well test data that show all the characteristic type curves given by the analytical DFIT theory. The paper is organized as follows:
Carbonate reservoirs in the Middle East are highly heterogeneous with complex porosity systems and mixed-wet matrix properties. These characteristics strongly affect reservoir performance under waterflooding. This paper concerns a highly layered limestone reservoir with various levels of cyclicity in properties and can be described at a high level as consisting of two main bodies, i.e., an Upper zone and a Lower zone with permeability contrast of up to two orders of magnitude. The main part of the reservoir is currently under waterflooding. Field observations show that injected water tends to channel quickly through the Upper zone along the high permeability layers and bypass the oil in the Lower zone. Past studies have indicated that this water override phenomenon is caused by a combination of high permeability contrast and capillary forces which counteract gravity forces.
In this paper we will investigate different development options for such heterogeneous mixed-wet reservoirs aiming at improving recovery from the Lower zone: 1- Optimized waterflooding with infill wells, 2- Novel EOR options designed to overcome the capillary forces and improve vertical sweep. The EOR options include (a) polymer-assisted solutions consisting of injecting polymer in the Upper zone and water or miscible gas in the Lower zone; and (b) surfactant assisted solutions (foam and enhanced gravity drainage).
The main conclusions of the study are: 1- Waterflooding is an efficient recovery mechanism for the Upper zone and tight well spacing is required to improve recovery from the Lower zone; 2- The EOR processes have the potential of improving recovery from the Lower zone; 3- The most attractive EOR schemes are the polymer-based options which, when compared to the optimized waterflooding/infill scenario, lead to much higher recovery, lower volumes of water injected and significantly less water cycling and the requirement of fewer wells. The polymer-assisted solutions also require injecting much lower polymer volumes compared to conventional polymer flooding. Simulation results show that the process(es) are robust to injection rates, vertical heterogeneity, well completions and a range of polymer viscosities.
Carbonate reservoirs contain more than 50% of world’s remaining conventional hydrocarbon reserves and on average have relatively low recovery factors. With the era of “easy oil” (conventional oil and natural gas that are relatively easy to extract) phasing out, enhanced oil recovery (EOR) becomes increasingly important to maintain and extend the production from existing oil reservoirs.
Increasing energy demand coupled with the production decline in traditional hydrocarbon resources poses one of the main challenges for the oil industry. There are not many feasible solutions with current technologies to meet the energy demand. One of the proven technologies to increase the recovery is the gas injection EOR (enhanced oil recovery/enhanced gas recovery. During the last decade there is definitely an upward trend in gas injection processes (Oil&Gas Journal, 2014). As we are facing more and more complex reservoir-fluid systems, there is an increasing requirement for new, generally more complex, dynamic modelling capabilities. Several simplifying assumptions that were appropriate for the modelling of conventional oil and gas reservoirs are not always valid for the more complex fields. One of these assumptions is the absence of component transfer between the aqueous phase and the hydrocarbon phases. A related assumption is the absence of chemical interactions between fluids and reservoir rock.
This paper shows how these complex processes have been included in a general purpose reservoir simulator in a robust and numerically efficient way. Currently, there are two approaches, (1) sequential calls to the flow solver and the geochemical solver (i.e. explicit coupling); (2) incorporation of the geochemical equations into the flow solver (i.e. fully implicit coupling). However, the first approach has an intrinsic drawback of not guaranteeing consistency of calculated dissolved gas between the flow part and the geochemical reaction part. The second approach is inherently too computationally expensive, limiting the number of reactions and number of species that can be part of the simulations.
Our new approach is to ensure consistency of the calculated gas solubility between flow and geochemical solvers as in a fully implicit scheme while achieving computational efficiency as in the explicit coupling scheme. The coupling scheme to the geochemical solver (for which the open source code PHREEQC is used) is explicit, but by extracting suitable parameters after every timestep, the partitioning of components between the aqueous phase and gas/oil phase(s), including evaporation of H2O, can be handled fully implicitly within the flow solver. The simulator runs in Equation of State mode for gas and oil components that can transfer between the gas/oil and the brine. Chemical components that can only reside in the brine (or the reservoir rock) are transported explicitly. In this way the number of components that need to be solved fully implicitly during one timestep is kept low. The approach is applicable not only to gas-water systems but also to oil-water (and gas-oil-water) systems. We show how the phase partitioning results compare favourably against experimental data, and illustrate the dynamic modelling approach on a case example.
The potential application area of this new methodology is very broad, and includes modelling of EOR methods (e.g. water-oil-rock partitioning of chemicals); CO2 and sour gas sequestration (e.g. solubility and mineral trapping; dry out problems); screening the unexpected scenario of leakage of gas components into groundwater (e.g. in the context of shale gas development); and some aspects of water flooding (e.g. reservoir souring; water flooding in a sour oil reservoir).
Prior to any EOR application, quantifying the remaining oil saturation (ROS) after water flood is critical in order to establish the target oil for a potential EOR scheme. The most widely available datasets for quantifying ROS are from the saturation logs such as resistivity logs from infill wells and pulsed neutron capture (PNC) logs from cased wells. However, the interpretation of these logs generally requires prior knowledge of water salinity. In most water flood projects, the injected water is different from the formation water, and the salinity is unknown in the water flooded zones. Logging tools for saturations without prior knowledge of salinity, such as the C/O log, also have limitations.
The current practice to overcome this problem is to apply one or more of the following techniques:
• Chemical tracer
• Sponge coring, pressurized coring, etc.
However, these techniques are relatively expensive and time-consuming. They cannot be used routinely field wide as a reservoir surveillance tool.
In this paper, we present a methodology to reduce the uncertainties in saturation logs within the context of reservoir model history-matching. In addition to matching pressure and water cut, the new methodology seeks to match the produced water chemistry too (with formation water and injection water chemistry as inputs). This is due to the recent advance of reservoir simulations that can model reservoir water composition changes by considering geochemical reactions of injection waters, formation brine, and reservoir minerals. With this new simulation capability, resistivity and sigma values per grid block are computed as part of the simulation, thus pseudo-logs of total resistivity and neutron capture cross section (S) can be generated as part of the simulation. This enables direct history-matching of the measured log signals.
For an EOR project, the implication of this new simulation methodology is to encourage the frequent sampling and analysis of injection and produced water as part of the reservoir surveillance, and run resistivity and/or S logs to monitor saturation changes even when injection water is significantly different from formation water.
Masalmeh, Shehadeh K. (Shell Technology Oman) | Wei, Lingli (Shell International Exploration & Production B.V.) | Hillgartner, Heiko (Petroleum Development Oman) | Al-Mjeni, Rifaat (Shell) | Blom, Carl P.A. (Shell Intl E&P)
Enhanced oil recovery (EOR) has become increasingly important to maintain and extend the production plateaus of existing oil reservoirs. Simulation models for EOR studies require the right level of spatial resolution to capture reservoir heterogeneity. Data acquired from the dedicated observation wells are essential in defining the required resolution to capture reservoir heterogeneity. For giant reservoirs with long production history, their full field models usually have grid block sizes that are of similar scale as the distance between injectors and observation wells, with the consequence of losing the value of the time lapse saturation logs from dedicated observation wells. Therefore, using high resolution sector models, especially from the part of the reservoir where static and dynamic data sets are rich, is a must.
The objective of this paper is to present an improved and integrated reservoir characterization, modelling and water and gas injection history matching procedure of a giant Cretaceous carbonate reservoir in the Middle East. The applied workflow integrates geological, petrophysical, and dynamic data in order to understand the production history and the remaining oil saturation distribution in the reservoir. Large amounts of field data, including time lapse saturation logs from observation wells, have been collected over the last decades to provide insight into the sweep efficiency and flow paths of the injected water.
Iterative simulations were performed to investigate different scenarios and various sensitivities with each iteration involving an update of the static model to honor both the dynamic and core/log data. While applying this iterative process it was also acknowledged that conventional core data (e.g. 1 plug per foot) may not capture the high permeability streaks in these heterogeneous reservoirs that control much of the reservoir flow behaviour, hence much denser plugging and core examination is required. In addition, permeability upscaling procedures need to take into account the fact that core plugs may not represent the effective permeability of the larger connected vuggy pore systems.
The improved understanding of reservoir heterogeneity, the more robust reservoir characterization, and the improved history matching demonstrates that a better representation of reservoir dynamics is achieved. This provides a solid platform for designing and planning future EOR schemes.
Carbonate reservoirs contain more than 50% of world's remaining conventional hydrocarbon reserves and on average have relatively low recovery factors. With the insight that the era of "easy oil?? (conventional oil and natural gas that are relatively easy to extract) is phasing out, enhanced oil recovery (EOR) becomes increasingly important to maintain and extend the production plateaus from existing oil reservoirs. EOR technologies, however, require a refined understanding of reservoir heterogeneities and dynamic field performance. Simulation models for EOR studies need to have the right level of resolution and details. Often, we find that for a giant reservoir with a long waterflood history, working with full field models with coarse simulation grids is not adequate to understand the reservoir performance and calibrate the static model. Therefore, using high resolution sector models, especially from the part of the reservoir where static and dynamic data sets are rich, is a must.
Lingli Wei, Shell (China) Innovation and R&D Centre Summary Many waterflood projects now experience significant amounts of water cut, with more water than hydrocarbon flowing between the injectors and producers. In addition to the impact on water viscosity and density that results from using different injection-water sources during a field's life, water chemistry itself may impact oil recovery, as demonstrated by recent research on low-salinity water-injection schemes. It is also known that water chemistry has a profound impact on various chemical enhanced-oil-recovery (EOR) processes. Moreover, the effectiveness and viability of such EOR schemes is strongly dependent on reservoir-brine and injectionwater compositions. For waterflood-performance assessment, the new modeling capability makes possible a more-optimum evaluation of petrophysical logs for well intervals where injection-water invasion is suspected. By modeling transport of individual species in the aqueous phase from injectors to producers, reservoir characterization can also be improved through the use of these natural tracers, provided that the compositions of the actual produced water are used in the history matching. The simulated water compositions in producers can also be used by production chemists to assess scaling and corrosion risks. Alkaline-flood-induced water chemical changes and calcite precipitation are also presented to illustrate applicability for chemical EOR with the new simulation capability. Introduction As more fields mature, water management for oil recovery is increasingly becoming a challenge in terms of high volumes of water going through a reservoir and being produced (Khatib 2007). Water chemistry plays a major role in tackling this challenge, providing a basis for injection-water sourcing and produced-water treatment, and for evaluating scaling and corrosion risks. Recently, a significant amount of research in the laboratory and field has focused on the impact of water chemistry on oil recovery in the context of low-salinity waterflood in sandstone reservoirs [see, for example, Lager et al. (2007) and Vledder et al. (2010) and references therein].
Many waterflood projects now experience significant amount of water cut, with more water than hydrocarbon flowing between the injectors and producers. In addition to the impact on water viscosity and density from using different injection water sources during a field's life, water chemistry itself may impact oil recovery as demonstrated by recent research on low salinity water injection schemes. It is also known that water chemistry has profound impact on various chemical EOR processes. Moreover, the effectiveness and viability of such EOR schemes is strongly dependent on reservoir brine and injection water compositions. In particular, the presence of divalent cations such as Ca+2 and Mg+2 has a significant adverse effect for chemical EORs. Utilising new developments in reservoir simulation, this paper outlines a method to account rigorously for water chemistry with only a small incremental computational cost compared to the same simulation model without geochemical reactions. The new modelling capability considers chemical reactions triggered by injection water and/or injected reactive gases such as CO2 and H2S, including mineral dissolution and precipitation, cation exchange and surface complexation.
For waterflood performance assessment, this paper demonstrates that rigorous modelling of water chemistry can significantly impact simulation results. In addition, interpretation of saturation logs requires inputs about brine composition. Thus, the new modelling capability makes possible a more optimum evaluation of petrophysical logs for well intervals where injection water invasion is suspected. By modelling transport of individual species in the aqueous phase from injector to producers, reservoir characterization can also be improved through the use of these natural tracers, provided the compositions of the actual produced water are used in the history matching. The simulated water compositions in producers can also be used by production chemists to assess scaling and corrosion risks. For CO2 EOR studies, we illustrate chemical changes inside a reservoir and in the produced water before and after CO2 breakthrough, and discuss geochemical monitoring as a potential surveillance tool. Alkaline flood induced water chemical changes and calcite precipitation is presented to illustrate applicability for chemical EOR with the new simulation capability.
As more fields mature, water management for oil recovery is increasingly becoming a challenge, in terms of high volumes of water going through a reservoir and being produced (Khatib, 2007). Water chemistry plays a major role in tackling this challenge, providing a basis for injection water sourcing and produced water treatment, and for evaluating scaling and corrosion risks. Recently, large amount of research in the laboratory and field focused on the impact of water chemistry on oil recovery in the context of low salinity waterflood in sandstone reservoirs (see for example, Lager et al, 2007 and Vledder et al. 2010, and references therein). This effort started by Morrow and co-workers (e.g., Tang & Morrow, 1997) who systematically investigated the relationships between water compositions, reservoir wettability and oil recovery. The impact of water chemistry on oil recovery in carbonates (especially chalk) has also been observed (see, for example, RezaeiDoust et al., 2009). Acid and CO2 gas injections cause geochemical changes in reservoir rock and brine (e.g. Obeida et al. 2009), which may pose integrity risks for injection wells, corrosion risks in the producers and surface facilities. It is also well established that the effectiveness of chemical EOR is dependent on brine compositions and pH (see an early systematic work by Healy et al, 1976).