Well testing is a critical part of any evaluation of a carbonate reservoir discovery. Well-test interpretation in carbonate reservoirs poses additional challenges to those normally faced in the interpretation process in clastic reservoirs. The range of different boundary and crossflow relationships that are generated during well testing by the complex porosity systems are often poorly quantified and understood. The volume over which the pressure response is effective is also a source of great uncertainty and could be critical at the exploration/appraisal stage in any project. In this paper, which describes a generic modelling approach, we consider carbonate reservoirs which contain three pore sytems (or porosity types): microporosity (end-member) with low permeability and high porosity; macroporosity (end-member) with high permeability and high porosity; and (3) fracture porosity with high permeability and low porosity. These occur in various nested geometrical distributions and varying contrasts. The observed well-test responses (i.e. fracture flow, fracture-matrix interactions) tend to 'obscure' one of these systems when compared with theoretical models. Micro- (meso-) and macroporosity can merge into a single matrix porosity system where the permeability contrasts are not great and the correlation lengths short (which can often be the case in carbonates). Macroporosity can also appear in well testing to 'merge' with the fracture response, i.e. the contributions of flow in the fractures and (high-permeability) porous matrix are indistinguishable. As a result of the homogenizing attributes of pressure dissipation away from the well, it is not generally possible to see the effects of a 'triple-porosity' response (i.e. where three different pore systems have a separate and identifiable signature on the well-test response) and a classical double-porosity response in the well test, despite three different pore systems being present, is possible. The apparent double-porosity response, which might obscure a triple-porosity system, therefore needs careful interpretation in order to attribute the appropriate properties during reservoir characterization in carbonates. In this work we use 'geological' well testing (i.e. well testing through numerical simulation of hypothetical geological models) to systematically analyse the effects of microporosity, macroporosity and fracture porosity on pressure dissipation and their apparent homogenization. While recent studies have proposed that a triple-porosity system should result in a 'W-shaped' response, we do not observe this behaviour in our simulations, although we specifically designed our geological models with a triple-porosity system. Instead we observe how macroporosity merges with the fractures or micro-and macroporosity merge, creating a 'sub-dominant' matrix or a 'dominant' fracture system, respectively and follow a traditional 'V-shaped' double-porosity response.@en

Fractures can be first-order controls on fluid flow in hydrocarbon reservoirs. Understanding the characteristics of fractures such as their aperture, density, distribution, conductivity, connectivity, etc, is key for reservoir engineering and production analysis. Well testing plays a key role in the the characterisation of fractured reservoirs, especially. New advances in the Pressure Transient Analysis (PTA) have enabled the interpretation of production data in a way where the resulting geological scenarios are in better agreement with fracture patterns observed in outcrop analogues. Traditionally, Drill Stem Test (DST) data have been the primay source of information for well testing. However, we hypothesise that wireline conveyed tools designed for Interval Pressure Transient Testing (IPTT) could yield a more throrough description of the near-wellbore heterogeneities, including fractures. Hence, we investigate the applicability of IPTT for characterising fractured reservoirs using detailed numerical simulations models with accurate wellbore representation to generate synthetic IPTT responses that can obtained through a next-generation wireline testing tool called SATURN. We particularly focus on cases where fractures are present in the near-wellbore region but do not intersect the wellbore. The study included parameters such as fracture densities and conductivities, distance between fractures and wellbore and the vertical extension of the fractures across geological beds. The impact of the different fracture scenarios on the pressure transient tests was recorded as characteristic signatures on diagnostic plots (pressure derivative curves). We have called these curves "IPTT-Geotypes"; they can be used to assist the interpretation process of IPTT responses. To the best of our knowledge, this is the first time pressure derivative type curves for IPTT in fractured reservoirs are presented in the literature. A field example of an IPTT case was analysed using the concept of geological well testing. We integrated the information from petrophysical logs and the IPTT-Geotypes to assist the calibration of a reservoir model developed to represent the geological setting of the tested reservoir interval. The results provided a sound interpretation of the reservoir geology and quantitative estimation of the matrix and fracture parameters.@en

Understanding the impact of fractures on fluid flow is fundamental for developing geoenergy reservoirs. Pressure transient analysis could play a key role for fracture characterization purposes if better links can be established between the pressure derivative responses (p′) and the fracture properties. However, pressure transient analysis is particularly challenging in the presence of fractures because they can manifest themselves in many different p′ curves. In this work, we aim to provide a proof-of-concept machine learning approach that allows us to effectively handle the diversity in fracture-related p′ curves by automatically classifying them and identifying the characteristic fracture patterns. We created a synthetic dataset from numerical simulation that comprised 2560 p′ curves that represent a wide range of fracture network properties. We developed an unsupervised machine learning approach that can distinguish the temporal variations in the p′ curves by combining dynamic time warping with k-medoids clustering. Our results suggest that the approach is effective at recognizing similar shapes in the p′ curves if the second pressure derivatives are used as the classification variable. Our analysis indicated that 12 clusters were appropriate to describe the full collection of p′ curves in this particular dataset. The classification exercise also allowed us to identify the key geological features that influence the p′ curves in this particular dataset, namely (1) the distance from the wellbore to the closest fracture(s), (2) the local/global fracture connectivity, and (3) the local/global fracture intensity. With additional training data to account for a broader range of fracture network properties, the proposed classification method could be expanded to other naturally fractured reservoirs and eventually serve as an interpretation framework for understanding how complex fracture network properties impact pressure transient behaviour.@en

Obtaining a fit-for-purpose rock-type classification that adequately incorporates the key depositional and diagenetic heterogeneities is a prime challenge for carbonate reservoirs. Another prevailing issue is to integrate the static and dynamic data consistently with the rock-typing scheme in order to correctly initialise the reservoir flow simulation model. This paper describes a novel near-wellbore rock-typing and upscaling approach adopted to address the crucial challenges of integrating reservoir rock-typing and simulation in carbonate reservoirs. We demonstrate this workflow through a case study for a highly heterogeneous Eocene-Oligocene limestone reservoir, Field X. Geological studies carried out in Field X suggested that the key permeability pathways are strongly related to the mechanism of reservoir porosity and permeability evolution during late-burial corrosion. The rock-typing and upscaling methodology described in this paper involves the geological-petrophysical classification of the key reservoir heterogeneities through systematic evaluation of the main paragenetic events. Associations between the depositional and late-burial corrosion features, and their impact on reservoir flow properties, were accounted for in our workflow. Employing near-wellbore rock-typing and upscaling workflow yielded consistent initialisation of the Field X reservoir simulation model and therefore improved the accuracy of fluids-in-place calculation. Subsequently, the cumulative production curves computed by the reservoir simulation model of Field X showed closer agreement to the historic production data. The revised Field X simulation model is now much better constrained to the reservoir geology and provides an improved geological-prior for history matching.@en

Benchmark problems have been generated to test a number of issues related to predicting reservoir behaviour (e.g. Floris et al., 2001, Christie and Blunt, 2001, Peters et al., 2010). However, such cases are usually focused on a particular aspect of the reservoir model (e.g. upscaling, property distribution, history matching, uncertainty prediction, etc.) and the other decisions in constructing the model are fixed by log values that are related to the distribution of cell properties away from the wells, fixed grids and structural features and fixed fluid properties. This is because all these features require an element of interpretation, from indirect measurements of the reservoir, noisy and incomplete data and judgments based on domain knowledge.Therefore, there is a need for a case study that would consider interpretational uncertainty integrated throughout the reservoir modelling workflow. In this benchmark study we require the modeller to make interpretational choices as well as to select the techniques applied to the case study, namely the geomodelling approach, history matching algorithm and/or uncertainty quantification technique. The interpretational choices will be around the following areas: (1)Top structure interpretation from seismic and well picks.(2)Fault location, dimensions and the connectivity of the network uncertainty.(3)Facies modelling approach.(4)Facies interpretations from well logs cutoffs.(5)Petrophysical property prediction from the available well data.(6)Grid resolution-choice between number of iterations and model resolution to capture the reservoir features adequately.A semi-synthetic study is based on real field data provided: production data, seismic sections to interpret the faults and top structures, wireline logs to identify facies correlations and saturation profile and porosity and permeability data and a host of other data. To make this problem useable in a manageable time period multiple hierarchically related gridded models were produced for a range of different interpretational choices.@en

Naturally fractured reservoirs (NFRs) account for a significant amount of the world conventional reserves but suffer from low recovery factors. Multiple techniques are, often in combination, used to detect the presence and extent of fractures in a reservoir. Of particular interest to this work is the use of dual-porosity model for analysis of well test data in order to identify and interpret the behaviour of fluid flow in NFR. This model, originally developed by Warren & Root (1963), has since been the industry standard for modelling NFRs and interpreting well-test data from NFRs. However, several studies have shown that the dual-porosity responses expected for naturally fractured reservoirs are not always observed where the wellbore intersect fractures, even for heavily and well-connected fractured network reservoirs. Our research aims to examine the reservoir features that cause the dual-porosity response to absent in some naturally fractured reservoirs and to be present in others. We demonstrate when dual porosity models are valid for well-test interpretation and can capture the key reservoirs features that characterise flow behaviours in NFRs. These features include the effect of fracture skin, network connectivity, and network size. The findings allow us to interpret well-tests in NFR more reliably.@en

Geological well testing is a valuable tool that allows us to improve understanding of pressure transient behaviour in a fractured reservoir. However, not all wells in a fractured reservoir will show pressure transients that are expected for NFRs. Our findings demonstrate that high resolution models with proper grid refinement around the wells and fractures are required to model pressure transient behaviour adequately and produce a physically meaningful wellbore response for a fractured reservoir. The key concept for interpreting well test data from fractured reservoirs is the dual-porosity model. This model, originally developed by Warren and Root (1963) has been the industry standard for modelling NFRs and interpreting well-test data from NFRs for more than 50 years. Although there are a number of factors impacting the exact shape of the pressure transients, our results suggest that observing the classical “V-shape” in the pressure derivative, as expected from a dual-porosity model may be an exception, rather than a rule in NFR, even for well-connected fracture networks. Our work quantifies when and why the assumptions inherent to the dual-porosity model break down when interpreting well-test data from NFR. @en

Interpreting well-tests in (fractured) carbonate reservoirs poses significant challenges because these reservoirs often demonstrate triple porosity system (fracture-matrix-vugs) characteristics. However, there is no "unique" triple porosity system: The matrix can behave as a double porosity/dual permeability system whilst the fractures provide the third system; there may be two fracture systems and a single matrix; there may be vugs (macropores), mesopores and micropores to provide very large contrasts in matrix permeabilities. Modelling these systems is challenging because of the need to include heterogeneity for the matrix (or multiple matrices) and fracture(s) and determine the correct coupling between these systems. The typical well test response in fractured systems - the classic double porosity "V" - can provide factors such as ω and λ as a description of fracture-matrix interaction (storativity ratio and the interporosity flow coefficient, respectively). Understanding how these two parameters relate to the description of matrix and fracture properties in triple porosity systems requires exploration of new scenarios in numerical well test modelling (sometimes called "geological well testing"). In this paper, we set out some of the reservoir description, modelling and simulation challenges to provide guidance on how to set up systematic models and determine the appropriate family of geotype (families of closely related pressure derivative response) curves for fractured carbonate systems in order to understand the interpretation of co and X.@en

New reservoir characterisation methods are needed to integrate multi-scale exploration and development data, particularly at the interface between well and field models. In this paper we illustrate a novel workflow involving high resolution Near Wellbore Modeling (NWM), which allows us to accurately include seismic, wire-line data, FMI, and well core logs from multi-porosity reservoirs in field-scale reservoir simulations. We demonstrate that NWM improves reservoir characterization and production management. The workflow was applied to a realistic clastic reservoir with high variance at small scale and can also be extended for carbonate reservoirs. We have performed a number of sensitivities comparing conventional local grid refinement in the near wellbore region with that involving NWM and obtained a significant increase in the accuracy of reservoir characterization and the calibration of dynamic models. Centimetre-scale models, containing several million cells, representing the fine geological details of the near-wellbore region were constructed using available data from seismic, core, open-hole and production well-log suits. Sensitivities were performed using these high-resolution models to obtain regular grids with the best possible up-scaling. The resulting well models were imported into a field-scale simulation model to evaluate the dynamic behavior of the reservoir employing numerical well testing. Our results show that using NWM tools for reservoir modeling yields more precise flow calculations and improves our fundamental understanding of the interactions between the reservoir and the wellbore.@en

Carbonate reservoirs host a major portion of the world's remaining conventional and unconventional hydrocarbon reserves, typically containing multi-scale geological heterogeneities varying over many orders of magnitude in size. Characterizing and representing them robustly in reservoir models is a prime challenge in carbonate reservoir simulation. One of the key aims of this paper is, hence, to present a novel near wellbore upscaling (NWU) workflow that addresses the challenges associated with conventional carbonate modelling workflows. The NWU workflow provides a systematic geostatistical approach to obtain more realistic representation of multi-scale geological-petrophysical heterogeneities in complex carbonate reservoir simulation models. Using well log and core data, near wellbore regions were recreated to represent the core scale heterogeneities via high resolution geostatistical models. These core/centimeter scale permeability models were then upscaled into wireline/decametre scale using flow-based upscaling. The results, coupled with wireline data were used to generate global porosity-permeability and vertical-horizontal permeability relationships for reservoir simulation. Importantly, the workflow mitigates sample bias, which is frequently observed in the core data for carbonate reservoirs. We have applied our approach to a mature carbonate field, to model and upscale crucial multi-scale heterogeneities ubiquitous in the reservoir. These heterogeneities, such as mechanically weak zones of enhanced micro- and macro-porosity, leached stylolites and associated tension gashes, were caused by diagenetic corrosion. Core plugs representivity is always an issue in carbonates and these highly corroded features were very difficult, if not impossible, to sample due to their fragility. As a result, the field suffers from inherent sample biasing and insufficiency of Routine Core Analysis (RCA) data, consequently underestimating the permeability in the simulation model. The workflow presented here has enabled the authors to re-evaluate the reservoir permeability model by accounting for as yet under-sampled geological heterogeneities. The paper represents a focused individual study addressing this specific issue and doesn't necessarily reflect the operator's full understanding of this multifaceted field. Our new permeability model has addressed the need for artificial permeability multipliers and provided insight on the potential causes of the original mismatch. As a result, a new alternative model scenario has been built to help guide the on-going development plans and forecasting incremental oil recovery.@en

We have investigated the role of high-frequency cycles (HFCs) in carbonates during water flooding. These are normally sub-seismic and therefore below grid resolution and must be upscaled, both in terms of single- and multiphase flow behaviour, to predict time to water breakthrough, recovery factors, and the habitat of remaining oil properly. Particularly the latter could be important when designing appropriate enhanced oil recovery schemes that target the remaining oil. The importance of selecting a high vertical resolution grid has been demonstrated for HFCs with continuous petrophysical log gradients and discontinuities, and the consequence these high permeability ranges have on waterflood velocity has been presented: capturing all of a continuous gradient requires increasing the vertical resolution so as to predict a fast enough water front, and a realistic distribution of the residual oil within the HFCs. In addition, the importance of selective diagenesis has been investigated by considering the effect of early-stage diagenesis at the top of HFCs in end-member Greenhouse and Icehouse climates. HFCs are very common in carbonates, even if they are nested within larger-scale heterogeneous geobodies, and the value of this investigation is in its application to real reservoir models.@en

Porosity and permeability of carbonate sediments evolve markedly with burial depth, reflecting the combined effects of mechanical compaction, chemical compaction, dissolution and cementation. While trends in porosity change with depth can be qualified, the evolution of permeability remains problematic. Here, we create a theoretical series of 2D images of major pore-occluding and pore enhancing diagenetic processes linked to their depth of occurrence. These images were then used to create 3D pore architecture models using Markov Chain Monte Carlo simulation, from which pore network were extracted to obtain multiphase fluid flow properties. The modelled porosity and permeability evolution from three different diagenetic pathways display several tipping points where the decrease in permeability is significantly larger than the associated drop in porosity. Such diagenetic pathway models can provide constraints on the predicted behaviour of carbonates during burial and/or uplift scenarios.@en

We apply a new and geologically consistent workflow to re-evaluate the saturation distribution in a giant and complex carbonate reservoir from the Middle East that comprises a thick transition zone. The workflow makes use of all the available capillary pressure, porosity, and permeability, data, irreducible water saturations, Archie exponents and cementation exponents. By using these data, the new workflow enables us to model hydrocarbon distributions more robustly. Hence the resulting 3D saturation model honours saturation logs at the wells exactly and allowed us to identify new reservoir compartments, leading to improved estimates of hydrocarbon reserves, and an estimated change in reserves of over 20%. The workflow is embedded in the Geo2Flow software and can be run conveniently from Petrel. The new saturation distribution needs to be considered as a new model scenario for any subsequent dynamic reservoir simulations.@en

We apply, evaluate and compare several reservoir rock typing (RRT) approaches for a giant carbonate reservoir in the Middle East that is characterized by poor rock quality and a thick transition zone. These workflows are used to define RRTs by comparing several approaches, namely pseudo clouds from porosity and permeability data for each subzone, global hydraulic elements, petrophysical grouping using MICP data and Lucia classes. Then, the permeability models obtained from each RRT approach are used as input data for building the water saturation models using two different approaches, Leverett J-functions and the Geo2Flow software. The application of this workflow leads to a significantly change of the saturation distribution and subsequently revised the oil-in-place estimation for the field, especially because the reservoir has a thick transition zone. The variations in saturation distributions and oil-in-place arising from the different RRT approaches are likely larger than the uncertainty in the geological data itself. The saturation distributions do not only impact oil-in-place estimates but also predictions for the subsequent reservoir simulation models.@en

This paper successfully applied the geoengineering workflow for integrated well-test analysis to characterize fluid flow in a newly discovered fractured reservoir in the Barents Sea. A reservoir model containing fractures and matrix was built and calibrated using this workflow to match complex pressure transients measured in the field. We outline different geological scenarios that could potentially reproduce the pressure response observed in the field, highlighting the challenge of non-uniqueness when analysing well-test data. However, integrating other field data into the analysis allowed us to narrow the range of uncertainty, enabling the most plausible geological scenario to be taken forward for more detailed reservoir characterization and history matching. The results provide new insights into the reservoir geology and the key flow processes that generate the pressure response observed in the field. This paper demonstrates that the geoengineering workflow used here can be applied to better characterize naturally fractured reservoirs. We also provide reference solutions for interpreting well tests in fractured reservoirs where troughs in the pressure derivative are recognizable in the data.@en

We demonstrate how modelling decisions for a giant carbonate reservoir with a thick transition zone in the Middle East, most notably the approach to reservoir rock typing and modelling the initial fluid saturations, impact the hydrocarbon distributions and oil-in-place estimates in the reservoir. Rather than anchoring our model around a single base case with an upside and downside, we apply a comprehensive 3D multiple deterministic scenario workflow to compare-and-contrast how modelling decisions and geological uncertainties influence the volumetric estimates. We carry out a detailed analysis which shows that the variations in STOIIP estimates can be as high as 28% depending on the preferred modelling decision, which could potentially mask the impact of other geological uncertainties. These models were validated through repeated and randomised blind tests. We hence present a quantitative approach that helps us to assess if the static models are consistent in terms of the integration of geological and petrophysical data. Ultimately, the decision which of the different modelling options should be applied does not only influence STOIIP estimates, but also subsequent history matching & forecasts.@en

A geological well testing model containing fractures and matrix was built to match an observed complex well test response in a reservoir that was known to be fractured. The resulting match of a well intersecting minor fractures near a major fracture was considered a good match in consideration of alternative geological scenarios. This match leads to a better understanding of the key reservoir features to reliably support development decisions@en

New reservoir characterization methods are needed to integrate multiscale exploration and development data, particularly at the interface between well and field models. In this paper, we illustrate a novel workflow involving high-resolution near-wellbore modeling (NWM), which allows us to accurately include seismic, wireline data, image logs, and well core logs from highly heterogeneous reservoirs in field-scale reservoir simulations. We demonstrate that an NWM-enhanced geoengineering workflow has the potential to improve reservoir characterization by applying it to a realistic clastic reservoir with high variance at small scale. We have performed a number of sensitivities comparing conventional local grid refinement (LGR) in the near-wellbore region with that involving NWM, and we obtained a significant increase in the accuracy of reservoir characterization and the calibration of dynamic models. Centimeter-scale models, containing several million cells, representing the fine geological details of the nearwellbore region, were constructed with available data from core and openhole well-log suits. The resulting well models were upscaled into regular grids with the highest resolution possible through the NWM software and incorporated into a field-scale simulation model to evaluate the dynamic behavior of the reservoir with a static-model transient test. Our results show that the use of NWM tools for reservoir modeling yields more precise flow calculations and improves our fundamental understanding of the interactions between the reservoir and the wellbore.@en

In water driven gas reservoirs, aquifer encroachment has major implications on development decisions and production management. Water encroachment patterns depend on several static and dynamic parameters spanning numerous spatial scales, from pore to basin scale. This research focuses on improving the characterization of aquifer encroachment patterns, utilizing a large offshore, water driven, gas reservoir as a case study. An experimental design workflow applied to a numerical simulation sector-model is used to evaluate and quantify key parameters. Results of this research provide insight to improved understanding of water encroachment patterns and methods that improve the ability to model aquifer dynamics.@en

Performance prediction for diatomite reservoirs is very challenging because these reservoirs have a low permeability, contain fractures, and are very compactible. Therefore it has been suggested that reservoir simulation is not suitable for forecasting future hydrocarbon production or identifying production drivers because it is very difficult to obtain a good history match, particularly during waterflooding. In this study we describe how it is possible to effectively model a low permeability, highly compactible waterflooded diatomite reservoir. The impact of pressure dependent permeability on production and cumulative oil recovery in diatomaceous reservoirs was also analyzed. The pressure dependent permeability term accounts for the effect of rock mechanical properties on recovery. This important aspect has been neglected so far and we believe it to be one of the reasons causing the difficulties in matching production history. As a key result of our work we present a new numerical simulation model to effectively predict waterflood performance and guide reservoir management in a diatomaceous reservoir. Incorporating an adequate understanding of the geology in the numerical model proved important to be able to predict performance from wells. We hence used the geopseudo approach, a multi-phase flow upscaling methodology, which accurately models small-scale flow and structure interaction at the lamina level. Hydraulic fractures, dual porosity and dual porosity features were also incorporated in the model. The model was validated by history matching and compared to field performance. Predictions have been confirmed by the ongoing waterflood response.@en