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In this paper we describe new and innovative flow diagnostics tools for dual porosity models for naturally fractured reservoirs. Our new diagnostic tools allow us to compare and rank large numbers of geological models based on their approximate dynamic response in almost negligible time. Fast ranking methods allow us to select a representative ensemble of models that quantify geological uncertainty for robust production forecasting via full physics reservoir simulation. Reliable production forecasting for fractured carbonate reservoirs is a challenge. Natural fractures, adverse wettability and complex matrix heterogeneity are all highly uncertain and can all negatively impact upon recovery. Ideally we should consider a large and diverse ensemble of reservoir models to quantify the impact of geological uncertainty on reservoir performance. However, the computational cost can be significant, especially for dual porosity/permeability models. A brute force approach using powerful workstations, clusters or cloud computing can be taken to reduce the time investment. But this is not always possible, rendering robust uncertainty quantification impractical for many asset teams. Often only a small subset of scenarios is considered which may collapse into a single base case, from which development decisions are made. Base cases often fail to predict future production, need frequent modifications, lack geological realism and provide incomplete risk assessments, often causing asset teams to miss economic opportunities. Flow diagnostics can provide dynamic reservoir information in a fraction of the time for full physics simulation. We propose a workflow where we utilise flow diagnostics as a ranking tool to complement forecasting using reservoir simulation throughout. Our approach addresses the model run time, allowing us to use standard hardware. Flow diagnostics solve simplified physics to approximate the dynamic response of the reservoir, from this we can calculate and visualize key dynamic properties (e.g., time-of-flight, drained and swept reservoir volumes, time-to-breakthrough, decline rates, sweet spots, well-allocation factors). Flow diagnostics provide robust indicators of dynamic heterogeneity that allow us to select a diverse ensemble of models that captures the range of uncertainty. In this work, novel diagnostics utilising physically based transfer models have been developed to account for the fracture-matrix exchange, which otherwise could only be obtained from lengthy simulation. A new Damköhler number based metric DaDP links the advective time-of-flight in the fractures to the transfer from the matrix. DaDP identifies fast and slow draining regions of the matrix, stagnant regions within the fracture network and wells at risk of water breakthrough. This information can subsequently be used to optimise well placement and rates to maximise production and delay water breakthrough.

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Reliable production forecasting for fractured carbonate reservoirs is a challenge. Natural fractures, adverse wettability and complex matrix heterogeneity are all uncertain and can all negatively impact upon recovery. Ideally, we should consider different reservoir concepts encapsulated in a large ensemble of reservoir models to quantify the impact of these and other geological uncertainties on reservoir performance. However, the computational cost of considering many scenarios can be significant, especially for dual porosity/permeability models, rendering robust uncertainty quantification impractical for most asset teams. Flow diagnostics provide a complement to full-physics simulations for comparing models. Flow diagnostics approximate the dynamic response of the reservoir in seconds. In this paper we describe the extension of flow diagnostics to dual porosity models for naturally fractured reservoirs. Our new diagnostic tools link the advective time of flight in the fractures to the transfer from the matrix, identifying regions where transfer and flux are not in balance leading to poor matrix oil sweep and early breakthrough. Our new diagnostics tools have been applied to a real field case and are shown to compare well with full-physics simulation results. Thematic collection: This article is part of the Naturally Fractured Reservoirs collection available at: https://www.lyellcollection.org/cc/naturally-fractured-reservoirs

Natural fractures are ubiquitous in the subsurface and can be the fundamental controls on fluid flow in geological reservoirs; however, their multi-scale properties are notoriously difficult to characterize, quantify, and model (e.g., Berkowitz, 2002;Kazemi & Gilman, 1993;Neuman, 2005). Hydraulically well-connected fractures form high-permeability networks that provide the essential pathways for fluid flow in a geological formation while isolated or poorly connected fractures tend to enhance the permeability of the formation. Both scenarios usually lead to enhanced spreading of groundwater contaminants, early breakthrough of injected fluids (e.g., cold water in a geothermal reservoir or gas/water in a hydrocarbon reservoir), or rapid migration and potential leakage of CO 2 during subsurface CO 2 storage.When two fluid phases coexist in a fractured geological formation, for example, during CO 2 injection into a saline aquifer or during oil production from a hydrocarbon reservoir, the wettability of the rock matrix is also a key factor that impacts the migration of the fluids because the balance between capillary, viscous, and gravitational forces controls how readily fluids are exchanged between fractures and rock matrix (e.g.,