Rapid Reservoir Modelling: Sketch-Based Geological Modelling with Fast Flow Diagnostics

Rapid Reservoir Modelling (RRM) is a software tool that combines geological operators and a flow diagnostics module with sketch-based interface and modelling technology. The geological operators account for all interactions of stratigraphic surfaces and ensure that the resulting 3D models are stratigraphically valid. The geological operators allow users to sketch in any order, from oldest to youngest, from large to small, or free of any prescribed order, depending on data-driven or concept-driven uncertainty in interpretation. Flow diagnostics assessment of the sketched models enforces the link between geological interpretation and flow behaviour without using time-consuming and computationally expensive workflows. Output of RRM models includes static measures of facies architecture, flow diagnostics and model elements that can be exported to industry-standard software. A deep-water case is presented to show how assessing the impact of different scenarios at a prototyping stage allows users to make informed decisions about subsequent modelling efforts and approaches. Furthermore, RRM provides a valuable method for training or to develop geological interpretation skills, in front of an outcrop or directly on subsurface data.

Efficient adjoint-based well-placement optimization using flow diagnostics proxies

Model-based optimization of placement and trajectories of wells in petroleum reservoirs by the means of reservoir simulation forecasts is computationally demanding due to the high number of simulations typically required to achieve a local optimum. In this work, we develop an efficient flow-diagnostics proxy for net-present-value (NPV) with adjoint capabilities for efficient computation of well control gradients and approximate sensitivities with respect to placement/trajectory parameters. The suggested flow-diagnostic proxy consists of numerically solving a single pressure equation for the given scenario and the solution of a few inter-well time-of-flight and steady-state tracer equations, typically achieved in a few seconds for a reservoir model of medium size. Although the proxy may not be a particularly good approximation for the full reservoir simulation response, we find that for the cases considered, the correlation is very good and hence the proxy is suitable for use in an optimization loop. The adjoint simulation for the proxy model which provides control gradients and placement sensitivities is of similar computational complexity as the forward proxy model (a few seconds). We employ a version of the generalized reduced gradient for handling individual well constraints (e.g., bottom-hole-pressures and rates). As a result, the individual well constraints are enforced within the flow-diagnostics computations, and hence every parameter update becomes feasible without sacrificing gradient information. We present two numerical experiments illustrating the efficiency and performance of the approach for well placement problems involving trajectories and simulation models of realistic complexity. The suggested placements are evaluated using full simulations. We conclude by discussing limitations and possible enhancements of the methodology.

A Fast Screening Tool for Assessing the Impact of Poro-Mechanics on Fractured Reservoirs Using Dual-Porosity Flow Diagnostics

Accounting for poro-mechanical effects in full-field reservoir simulation studies and uncertainty quantification workflows is still limited, mainly because of their high computational cost. We introduce a new approach that couples hydrodynamics and poro-mechanics with dual-porosity flow diagnostics to analyse how poro-mechanics could impact reservoir dynamics in naturally fractured reservoirs without significantly increasing computational overhead. Our new poro-mechanical informed dual-porosity flow diagnostics account for steady-state and singlephase flow conditions in the fractured medium while the fracture-matrix fluid exchange is approximated using a physics-based transfer rate constant which models two-phase flow using an analytical solution for spontaneous imbibition or gravity drainage. The deformation of the system is described by the dualporosity poro-elastic theory, which is based on mixture theory and micromechanics to compute the effective stresses and strains of the rock matrix and fractures. The solutions to the fluid flow and rock deformation equations are coupled sequentially. The governing equations for fluid flow are discretised using a finite volume method with two-point flux-approximation while the governing equations for poro- mechanics are discretised using the virtual element method. The solution of the coupled system considers stress-dependent permeabilities for fractures and matrix. Our framework is implemented in the open source MATLAB Reservoir Simulation Toolbox (MRST). We present a case study using a fractured carbonate reservoir analogue to illustrate the integration of poro-mechanics within the dual-porosity flow diagnostics framework. The extended flow diagnostics calculations enable us to quickly screen how the dynamics in fractured reservoirs (e.g. reservoir connectivity, sweep efficiency, fracture-matrix transfer rates) are affected by the complex interactions between poro-mechanics and fluid flow where changes in pore pressure and effective stress modify petrophysical properties and hence impact reservoir dynamics. Due to the steady-state nature of the calculations and the effective coupling strategy, these calculations do not incur significant computational overheads. They hence provide an efficient complement to traditional reservoir simulation and uncertainty quantification workflows as they enable us to assess a broader range of reservoir uncertainties (e.g. geological, petrophysical and hydro-mechanical uncertainties). The capability of studying a much broader range of uncertainties allows the comparison and ranking from a large ensemble of reservoir models and select individual candidates for more detailed full-physics reservoir simulation studies without compromising on assessing the range of uncertainties inherent to fractured reservoirs.

The use of flow diagnostics to rank model ensembles

Ensembles of geomodels provide an opportunity to investigate a range of parameters and possible operational outcomes for a reservoir. Full-featured dynamic modelling of all ensemble members is often computationally unfeasible, however some form of modelling, allowing us to discriminate between ensemble members based on their flow characteristics, is required. Flow diagnostics (based on a single-phase, steady-state simulation) can provide tools for analysing flow patterns in reservoir models but can be calculated in a much shorter time than a full-physics simulation. Heterogeneity measures derived from flow diagnostics can be used as proxies for oil recovery. More advanced flow diagnostic techniques can also be used to estimate recovery. With these tools we can rank ensemble members and choose a subset of models, representing a range of possible outcomes, which can then be simulated further. We demonstrate two types of flow diagnostics. The first are based on volume-averaged travel times, calculated on a cell by cell basis from a given flow field. The second use residence time distributions, which take longer to calculate but are more accurate and allow for direct estimation of recovery volumes. Additionally we have developed new metrics which work better for situations where we have a non-uniform initial saturation, e.g., a reservoir with an oil cap. Three different ensembles are analysed: Egg, Norne, and Brugge. Very good correlation, in terms of model ranking and recovery estimates, is found between flow diagnostics and full simulations for all three ensembles using both the cell-averaged and residence time based diagnostics.