Daniel Arnold

Heriot-Watt University · Institute of Geoenergy Engineering

Geological subsurface storage is a promising strategy for large-scale, cost-efficient energy storage systems. Stress sensitivity has notably influence on the long-term stability and serviceability of subsurface reservoirs set for energy storage use. The evolution of the field stress of stress-sensitive reservoirs and the associated structural defor...

This study investigates generative adversarial networks (GANs)’ capacity to model multi-facies distributions of meandering systems. Earlier works showed that GANs outperform geostatistical methods in reproducing complex geometry, like the shapes of fluvial channels. However, the reproduction of geological complexity and geological realism remains a...

The COSTA model is a new open-source carbonate reservoir benchmarking case study, that uniquely considers major uncertainties inherent to carbonate reservoirs, providing a challenging and realistic benchmarking test for a range of geo-energy applications. The COSTA model is large (1,600 km2), with many wells (447) and large associated hydrocarbon v...

The GAN River-I data set is designed to provide a stern test for machine learning and geostatistical tools that wish to recreate the complex geometries of realistic facies distributions in subsurface reservoirs. It provides more complex, non-stationary facies distributions than previous open data sets, some of which have modelled channels but do no...

This abstract introduces a novel approach to construct reservoir models and estimate uncertainty of depositional and structural properties with Variational Autoencoders (VAE) based on Graph Convolutions. The work demonstrates how to parameterize depositional and structural scenarios with Generative Deep Learning to provide more efficient ways for g...

This study evaluates the potential of recycling carbon dioxide (CO2) in the associated gas in ultra-deepwater pre-salt carbonate reservoirs for Carbon Capture Utilization and Storage (CCUS). We performed compositional subsurface modeling of a hypothetical field for multi-objective optimization, aiming at minimizing carbon emissions whilst maximizin...

https://researchportal.hw.ac.uk/en/datasets/costa-model-hierarchical-carbonate-reservoir-benchmarking-case-st <------- The COSTA is a semi-synthetic but geologically realistic suite of carbonate reservoir models that capture a wide range of geological, petrophysical, and geomodelling uncertainties that can be history-matched against our undisclose...

Generative deep learning is becoming a widely used approach in geological modelling, especially in problems that involve optimization processes under uncertainty like history matching. The basic idea of reservoir modelling and history matching by generative deep learning is to train some kind of reservoir generator and provide optimization under di...

This work presents a new open-source carbonate reservoir case study, the COSTA model, that uniquely considers significant uncertainties inherent to carbonate reservoirs, providing a far more challenging and realistic benchmarking test for a range of geo-energy applications. The COSTA field is large, with many wells and large associated volumes. The...

Understanding subsurface hydrocarbon migration is a crucial task for petroleum geoscientists. Hydrocarbons are released from deeply buried and heated source rocks, such as shales with a high organic content. They then migrate upwards through the overlying lithologies. Some hydrocarbon becomes trapped in suitable geological structures that, over a g...

We extend single‐porosity flow diagnostics to dual‐porosity systems using a novel retardation factor R to account for the effect of fracture‐matrix transfer on breakthrough times and displacement efficiency during two‐phase flow in fractured reservoirs. R is based on an analytical solution for capillary‐driven fluid exchange between the fractures a...

This work presents a new open access carbonate reservoir case study that uniquely considers the major uncertainties inherent to carbonate reservoirs using one of the most prolific aggradational parasequence carbonate formation sets in the U.A.E., the Upper Kharaib Member (Early Cretaceous), as an analogue. The ensemble considers a range of interpre...

Polymer flooding offers the potential to recover more oil from reservoirs but requires significant investments which necessitate a robust analysis of economic upsides and downsides. Key uncertainties in designing a polymer flood are often reservoir geology and polymer degradation. The objective of this study is to understand the impact of geologica...

Polymer flooding offers the potential to recover more oil from reservoirs but requires significant investments, which necessitate a robust analysis of economic upsides and downsides. Key uncertainties in designing a polymer flood are often reservoir geology and polymer degradation. The objective of this study is to understand the impact of geologic...

How to estimate operational controls so as to optimize economic returns in CO2-WAG projects and reduce calcite scale risk? The reactivity and heterogeneity intrinsic to carbonate reservoirs make CO2-WAG (Water Alternating Gas) injection a big challenge. While miscibility effects greatly increase oil recovered, the presence of CO2 can cause severe f...

Geothermal energy has a high potential to contribute to a more sustainable energy system if the associated economic risks can be overcome in the design process. The development planning of deep geothermal reservoirs (over 1000 m depth) relies on computer models to forecast and then optimize system design. Optimization is easy where all the objectiv...

CO2-WAG (Water-Alternating-Gas) has been applied in offshore Brazilian oilfields to improve recovery rates and mitigate the environmental impact that venting produced CO2 would bring. Although CO2 is highly miscible in oil under these reservoirs conditions, this gas is also extremely mobile, and its speciation in the aqueous phase drives reactions...

This work presents a new open access carbonate reservoir case study that uniquely considers the major uncertainties inherent to carbonate reservoirs using one of the most prolific aggradational parasequence carbonate formation set in the U.A.E; the Late Barremian Upper Kharaib Mb. as an analogue. The ensemble considers a range of interpretational s...

Science and mathematics are currently under-represented in the computational creativity (CC) community. We discuss why the CC community should apply their work to mathematical and scientific domains, and argue that this would be mutually beneficial for the domains in question. We identify a key challenge in Automated Reasoning-that it has not achie...

River deposits are rich in sedimentological patterns that determine their petrophysical properties and industrial value (e.g. hydrocarbon reservoirs and aquifers), as well as providing each deposit with individual characteristics. Great variability in characteristics exists in modern river systems; their behaviour is expected to further diverge und...

There are a number of benchmark studies for clastic reservoirs (e.g. the PUNQ, SPE10, Brugge Field, Watt Field, or Norne Field models) for challenges such as EOR, testing new numerical algorithms for reservoir simulation and uncertainty quantification. To date, the only carbonate benchmark reservoir is the UNISIM-11 suite which focuses on the Brazi...

WAG (Water-Alternating-Gas) schemes have been applied in Brazilian carbonate reservoirs aiming to minimize residual oil saturation and gas flaring by recycling CO2 naturally being produced alongside hydrocarbon gas. However, applying WAG injection in highly reactive and heterogeneous carbonate rocks can potentially create severe scaling problems. T...

This paper describes the application and testing of innovative dual porosity flow diagnostics to quantitatively rank large ensembles of fractured reservoir models. Flow diagnostics can approximate the dynamic response of multi-million cell models in seconds on standard hardware. The need for new faster screening methods stems from the challenge of...

Deepwater sedimentology has been a focus of the geoscience community for several decades, with progress driven largely by the needs of the oil and gas industry. In recent years, the focus has moved towards bedforms that have previously gone unrecognised and poorly understood. Sediment waves are an example of this. Sediment waves are large-scale und...

Bayesian uncertainty quantification of reservoir prediction is a significant area of ongoing research, with the major effort focussed on estimating the likelihood. However, the prior definition, which is equally as important in the Bayesian context and is related to the uncertainty in reservoir model description, has received less attention. This p...

The average global recovery factor of a typical oil and gas field is approximately 40% at after secondary recovery processes such as gas lifting and water flooding. The low recovery factor is often a result of by passing a considerable amount of oil in the reservoir due to unknown reservoir heterogeneity and incomplete understanding of the geology....

Models used for reservoir prediction are subject to various types of uncertainty, and interpretational uncertainty is one of the most difficult to quantify due to the subjective nature of creating different scenarios of the geology and due to the difficultly of propagating these scenarios into uncertainty quantification workflows. Non-uniqueness in...

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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 ense...

This study investigates how a polymer flood design can be optimized while considering geological uncertainty in the reservoir models. Polymer flooding can increase oil recovery, reduce water cut, and improve sweep efficiency by diverting flow to low permeable zones. We applied two different history matching approaches (manual and gradient-based) to...

Water alternating gas (WAG) injection is a method of controlling the viscous fingering impact in a miscible flooding processes to improve the volumetric sweep efficiency. The WAG technique is a mix of two conventional techniques: gas injection to improve the microscopic displacement efficiency and water flooding to improve the sweep efficiency. Ove...

When simulating foam floods, uncertainties exist in both the foam and reservoir parameters however the combination of these uncertainties are rarely incorporated in forecasting. Foam flooding is an effective enhanced oil recovery method that controls mobility, reduces gas relative permeability, delays gas breakthrough and helps improve sweep effici...

Assessing the change in uncertainty in reservoir production forecasts over field lifetime is rarely undertaken because of the complexity of joining together the individual workflows. This becomes particularly important in complex fields such as naturally fractured reservoirs. The impact of this problem has been identified in previous and many solut...

We propose a novel approach to evolve the model through the update process based on the ensemble of possible model realisations that are fused together in a data driven way rather than assimilated under certain assumptions. Multiple Kernel Learning (MKL) is a learning-based technique, which provides a way to blend together multiple pattern informat...

Determining an optimal location and configuration of well to be drilled is a critical reservoir development decisions as it can cost millions of dollars and determine the volume of hydrocarbons being produced. This is a very challenging task due to large number of decision variables involved. One important factor to consider in field development is...

The generation of multiple reservoir models that match production data is one of the advantages of automatic history matching. Including facies geometry varia­tions within the AHM process without the modeller control could result in the selection of reservoir models that match production data but lack of sedimentological realism (facies geometry th...

Uncertainty in the distribution of fractures has a high impact on the fluid flow in oil reservoirs. The challenge is to propagate the uncertainty in the fracture distribution patterns into the reservoir flow response. Optimisation reservoir production under this geological uncertainty would result in to more robust operational decisions to maximise...

The generation of multiple reservoir models that match production data is one of the advantages of automatic history matching (AMH). Including facies geometry variations within the AHM process without the modeller control, could result in the selection of reservoir models that match production data but lack of sedimentological realism. These unreal...

This paper presents some novel ideas to ensure that updates to a model remain geologically realistic during the process of history matching reservoir models to production data. The proposed technique

Characterization and modelling of naturally fractured reservoirs (NFR) is usually complicated with very high degree of heterogeneity and uncertainty related to fractures. A commonly used framework for uncertainty estimation such as Monte-Carlo modelling is straightforward but in case of NFR is highly time-consuming as it requires generation of a la...

Produced Water Chemistry data (PWC) is the main source of information to monitor scale precipitation in oil field operations. Chloride concentration is used in order to evaluate the seawater fraction of the total produced water per producing well and is included as an extra history matching constraint to revaluate a good conventionally history matc...

One of the challenges in automatic history matching is to ensure the preservation of the realistic geological features of reservoir models. Realism of the history matched model is vital because of its impact on the flow response and the reliability of the model predictions. The issue is that models with unrealistic geological features can still mat...

Naturally Fractured Reservoirs (NFR) hold a significant fraction of remaining petroleum reserves. Recovery factors from NFR are usually less than in conventional reservoirs due to associated high uncertainty throughout the characterisation and modelling phases. This particularly includes the modelling and upscaling of the fracture domain using Disc...

Inorganic scale precipitation and deposition in production wells can be a significant impediment to effective reservoir management. In extreme cases scale can cause the well to be abandoned as a result of reservoir formation damage in the near wellbore area and the narrowing of the production tubing annulus thus preventing fluid flow. The predictio...

Conventionally, automated history matching methods operated on a single number (the misfit or match quality) which is obtained by summing the least square misfits for all the quantities of interest in a history match. Multi-objective history matching allows the algorithm to be guided by (usually groups of) match quality components, with the overall...

The data are available at https://github.com/cageo/Arnold-2012

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 and 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 predicti...

The AGORA (Advanced Geoscience Organized for Reservoir Applications) mission is to address a series of themes on a tri-annual rotating basis that have, and will continue to have, a long-term interest for the professionals in both societies. The aspiration is that the EAGE/EUROPEC AGORA would provide justice for all attempts at integration. In each...

Produced Water Chemistry (PWC) has been included in the history matching of reservoir simulations. Generally, in conventional history matching, the water chemistry is not considered as an extra constraint. The chemistry of the different types of water in a reservoir, such as aquifer, connate and seawater is very different, and can be traceable. Pro...

Geostatistical models reproduce spatial correlation based on the available on site data and more general concepts about the modelled patters, e.g. training images. One of the problem of modelling natural systems with geostatistics is in maintaining realism spatial features and so they agree with the physical processes in nature. Tuning the model pa...

Automatic history matching reservoir models using geological features is made challenging by the inability of the modeller to avoid selecting unrealistic reservoir models. In the current practice, of modelling fluvial reservoirs, the geometry of sandbodies is based on uninformative, deterministic or two-dimensional geological priors. These priors c...