In this paper we carry out a full field Reservoir calibration and optimisation scenario, coupling molecular interactions and ensemble based optimisation techniques. We use the friction theory model to estimate the viscosity, taking into account the molecular interactions and integrating the results in Reservoir simulation using the equation of state. Model calibration is achieved with the Ensemble Smoother with Multiple Data Assimilation (ES-MDA).
Further, we then optimise the calibrated model, focusing on Enhanced Oil recovery technique, with steam injection, utilising the Ensemble based Production Optimisation method (EnOPT). The Hydrocarbons viscosity was estimated using the friction theory, which utilises the attraction and repulsion parameters in a Van Der Waals type equation of state and the concept behind Amontons Coulomb friction laws. The molecular interactions are taken into account in understanding the fluid viscosity behaviour. The link is signified between the molecular interactions and their effect on the velocity between the hydrocarbon fluid layers that are responsible for the resistance to flow. The uncertainty in the estimated viscosity could be narrowed by using Bayesian statistic techniques to match the chosen reservoir parameters with the mean historical data using the Ensemble Smoother with Multiple Data Assimilation (ES-MDA).
The Enhanced Oil Recovery technique was chosen to be steam injection in order to reduce the oil viscosity by raising the reservoir temperature without maximising the overall cost. The Net Present Value (NPV) was maximised by using an ensemble based optimisation technique (EnOPT), where the controls of steam injection temperature and two producers bottom hole pressure were the adjusted parameters.
The viscosity of a heavy oil required additional recovery techniques to increase the driving force for the production. The heavy oil viscosity decreases with increasing temperature due to the increase in kinetic energy of the molecules that weakens the attraction force and the increases in repulsion between them. The initial mean NPV of the generated 100 realisations of the chosen adjusted parameters was found to be approximately $1,500,000.
The mean NPV of the realisations after optimisation was found to be $3,440,056. This increase in NPV was due to the increase in oil production rate, the main parameter influencing the increase in NPV was the cost and amount of oil produced, bearing in mind the water treatment and steam cost. The novelty in this study is a coupling of molecular scale simulation (friction theory) with Reservoir Simulation (by means of the Peng-Robinson Equation of state), which estimates the main physical parameters of reservoir systems and also adequately accounts for the intermolecular forces. We also calibrate the synthetic reservoir model with the ES-MDA infused with EnOPT for realistic model production optimisation.
Fourtakas, Georgios (University of Manchester) | Stansby, Peter K. (University of Manchester) | Rogers, Benedict D. (University of Manchester) | Lind, Steven J. (University of Manchester) | Yan, Shiqiang (City University of London) | Ma, Qingwei (City University of London)
This paper presents a two-dimensional, one-way coupling methodology between the quasi-arbitrary Lagrange–Euler finite element method (QALE-FEM) nonlinear potential flow solver and the incompressible smoothed particle hydrodynamics (ISPH) Navier-Stokes equations solver. Nonlinear potential flow solvers such as the QALE-FEM are highly efficient solvers for propagating waves in large domains; however, when extreme nonlinearity takes place, such as fragmentation, breaking waves, and violent interaction with marine structures, the methodology becomes incapable of dealing with these flow features. The particle method ISPH is known to be accurate for such highly nonlinear fragmentized flows and provides near-noise-free pressures. ISPH is thus ideal for near-field flows involving overturning, splashing, and slamming. Herein, we propose a one-way coupling methodology between QALE-FEM and ISPH where the methods are used for the far-field and inner/local regimes, respectively. To validate the one-way coupling algorithm, two sinusoidal waves have been used with satisfactory results. The intention is to extend this approach to the strong coupling of the potential flow solver with ISPH using a two-phase (air–water) solver. The aim is to reliably predict extreme wave forces and slamming on offshore structures such as decks and platforms for marine renewable energy and the oil and gas industry.
CO2 Sequestration is one of the strategies currently used to decrease the amount of CO2 in the atmosphere. In this work, the modelling of CO2 sequestration involves the simulation of CO2 capture from flue gases and the CO2 storage in the subsurface considering a sustainability approach. The main focus of the CO2 sequestration is to reduce the greenhouse emission but in many cases, the models do not consider the carbon footprint associated with the process. We present an integrated approach where the CO2 sequestration model involves the power plant simulation of the CO2 capture, the numerical simulation of CO2 storage, economics and the life cycle assessment for the minimisation of the carbon footprint. This study provides an insight for future development of integrated approaches considering oxycombustion carbon capture focussed on the air separation unit and the simulation and monitoring of the subsurface storage sites.
Our work considers the CO2 capture process using Cryogenic and Membrane Air Separation Units for Oxi-Combustion because it is associated with a reduced carbon footprint when compared to other processes as post-combustion and pre-combustion. Our CO2 storage approach includes the compositional simulation of fluid flow in porous media and the characterisation of the sealing rock above realistic heterogeneous storage models by using an Ensemble Kalman Filter approach on a long term simulation of 100 years. Initial realisations of the subsurface model were generated using stochastic modelling and considering the uncertainty on the petrophysical properties of the rock, in particular permeability and porosity. In this work, one of the main purposes of the CO2storage simulation is to avoid the vertical leakage of the CO2 and for this, the fluid saturation in every cell is monitored during the simulation approach.
From the results associated with the oxy-combustion application, the Cryogenic model and membrane model reduce the carbon footprint by 78.34% and 66.84% respectively compared to the power plant model without carbon capture. It is also observed that electricity consumption produces the biggest carbon footprint portion for both models, hence future improvement should be focused in reducing process energy requirement. In terms of energy production, carbon footprint, and economic, oxy-combustion power plant with cryogenic air separation demonstrates better performance. However, the results of this study indicate that the membrane O2/N2 needs produce lower net power production and oxygen purity compared to the cryogenic model. Hence, further development of membrane material is still needed before it can be considered as a competitive option for air separation unit. An economic evaluation is also performed and the results show that cryogenic air separation is still a more economical option compared to membrane. The design of the well locations is dependent of the heterogeneity of the model and the correct characterisation of the sealing rock. The performance, environmental, and economic considerations are taken into account, resulting in an integrated and broader understanding of CO2 sequestration.
Hollis, C (University of Manchester) | Lawrence, D (Al Hosn Gas) | Darmaki, Fatima Al (Al Hosn Gas) | Perriere, Matthieu Deville de (Badley Ashton and Associates Ltd) | Foote, Alexander (Badley Ashton and Associates Ltd) | Kostic, Boris (Badley Ashton and Associates Ltd)
This paper summarises the results of an intense reservoir appraisal programme that was conducted within a sour gas reservoir, onshore UAE, in order to determine the controls on porosity presence, distribution and effectiveness. This multiwell study was conducted over less than 5 years in order to define and predict porosity sweet-spots, and prepare for first gas, which was achieved in 2015. Focus is on the Arab D Member of the Arab Formation, the thickest and volumetrically most significant reservoir interval. It comprises an upward-cleaning succession of lime mudstone, peloidal and skeletal packstone and oolitic grainstone, culminating in a clay-rich, brecciated emergent surface. The entire succession shallows upwards from very low energy, basinal mudstones into cross-bedded oolitic grainstones that were deposited in a shoal complex that protected a gently agitated lagoon. Low skeletal diversity and the abundance of ooids are indicative of slightly elevated salinities; the abundance of anhydrite within the overalying Arab A/B/C and Hith Formation is indicative of basin dessication.
The lowermost Arab D Member is dominated by lime mudstones and is highly microporous. A very low matrix permeability is locally enhanced by short, partially cemented, vertical fractures formed perpendicular to stylolites, usually cutting thin skeletal floatstone beds with abundant biomoulds. The main reservoir interval is the overlying upper Arab D Member. Porosity occurs principally as intraparticle micorporosity in ooids but in the uppermost upper Arab D Member, interparticle cement volumes are lower and macropores are preserved. The best reservoir properties occur within this bioturbated oolitic grainstone facies, and in cross-bedded oolitic grainstone near the palaeo-crest of the field, probably because early oil emplacement inhibited cementation. There is good evidence that the base of the upper Arab D Member and the lower Arab D member are in communication. Although there is evidence of thermochemical sulphate reduction in the Arab D Member, it is volumetrically minor and unlikely to have generated the high volumes of H2S that are known to occur in the field.
Numerical Weather Prediction models (NWPM) such as Weather Research and Forecasting (WRF) are increasingly used for assessment of offshore wind farms. Prior studies have typically focused on either hub height wind speed over the range relevant to power production or on energy yield from exemplar farms. For design optimisation of wind turbines it is also important to establish peak loading conditions and this requires accurate prediction of both wind shear and turbulent characteristics across the swept area. This is evaluated by comparison to published data at locations near Askervein Hill, Scotland and three met-masts located in the North West of the Indian subcontinent. In regions of flat-terrain the wind speed profile was generally in good agreement with met-mast data, to altitudes of 50 m. At higher altitudes there was greater disparity between predicted and measured velocity with over-prediction of 10% and 9.37% at the flat- and hill-top locations over the range 50 to 300 m respectively. This assessment against multiple met-masts within the same region provides confidence in the prediction of hub height velocity but indicates limitations to the use of such models for characterizing the onset profiles of velocity and turbulence to assess loading of large diameter offshore turbines. The paper discusses implications for turbine loading considering conditions at several potential deployment sites across the Gujarat region, India.
The substantial planned increase in offshore wind energy development gives rise to many challenges. One of the main challenges is to assess wind conditions at planned deployment sites to a sufficient accuracy. This study addresses the suitability of the numerical weather prediction model, weather research and forecasting (WRF) for prediction of offshore wind farm design conditions with a particular focus on Northern India. Within India the installed capacity of wind turbines onshore is more than 20 GW. India has a coastline of over 7600 km and preliminary assessment has shown that there is potential for installation of around 250 GW of offshore wind turbines. (Baldock et al., 2015).
This work focuses on the improvement of an integrated methodology for the automatic history matching of compartmentalised reservoirs using 4D seismic results, stochastic initialization and the Ensemble Kalman Filter method. We show the comparison of two different history matching approaches using the Ensemble Kalman Filter (EnKF) to update the Fault Transmissibility Multipliers (FTM) initially estimated with and without considering the 4D seismic results. In this study, the parameters updated during the history matching are two-phase fault transmissibility multipliers (FTM), absolute permeability and effective porosity of a synthetic realistic 3D reservoir. The true impedance map and the changes in reservoir pressure and saturation were previously computed from 4D seismic results. The systematic estimation of two-phase fault transmissibility multipliers is based on the integration of the collected 4D seismic results and an established method validated in our previous work based on a deterministic model, using the gradient-based History Matching, Levenberg Marquardt method (LM). We present the history matching of a synthetic reservoir using the Ensemble Kalman Filter (EnKF) considering the 4D seismic results to update the models and geostatistical techniques to produce the initial geological models. The stochastic method used is the Sequential Gaussian Simulation (SGS) technique to generate 100 initial models. During history matching using the EnKF, the saturation distributions are computed from the forward modelling of a two-phase system (oil-water). The impedance maps are then estimated using the Gassmann equation and compared with the true impedance map as part of the History Matching process. To validate the results, the cost function consisting of two components is calculated, the first is the structural similarity index of the two reconstructed impedance images to the real impedance image and the second is the RMS cost function value,
Oil and gas drilling schemes are inherently complex systems comprising different technical disciplines and multiple interconnected, globally diverse stakeholders, operating within a dynamic environmental and legislative environment. This presents numerous challenges to traditional project management which assumes a very'reductionist lens' and which fails to account for the impact of dynamic internal and external forces on the'soft' boundaries of the project domain. Oil and gas projects are characterized by extreme difficulty in predicting outcomes and system behaviors and, at the tails of the distribution of events, 'black-swans' do occur. This increases project and business risk for stakeholders and affects value creation and appropriation opportunities. The paper argues that a holistic understanding of oil and gas drilling projects is necessary to account for the experiences, politics, human interactions, emergence and complex behavior of individuals and teams, both internal and external to the project environment. Experience and case studies will be discussed and challenged to uncover if this complexity is one of the reasons why projects sometimes fail to deliver sustainable value outcomes to clients. Then, through exploring complexity theory, we will attempt to understand the importance of understanding and coping with the emergent behavior of systems, using the theoretical'edge of chaos' as a metaphor for'highly complex projects'. By understanding complexity (as distinct from attempting to quantify it), the authors suggest that our existing'bodies of knowledge' in project management may require a significant renovation to improve project outcomes, the value expectations that clients have and to contribute to long term sustainable and competitive growth for the industry..
Coseglio, Mario S. D. R. (University of Birmingham Edgbaston) | Connolly, Brian J. (University of Manchester) | Li, Xiao-Ying (University of Birmingham) | Dong, Hanshan (University of Birmingham) | Dent, Phil (Exova Corrosion Centre) | Fowler, Chris (Exova Corrosion Centre)
ABSTRACTThe selection of corrosion-resistant alloys for oilfield components has been a challenge for the oil and gas industry due to its complex interactions with environments containing hydrogen sulfide (H2S) and carbon dioxide (CO2). Field failures have been frequently attributed to sulfide stress cracking (SSC), which can occur due to the applied stress in the presence of H2S. The precipitation-hardening stainless steel 17-4 PH (H1150D) is a cost-effective alloy for some oilfield components due to its favourable combination of properties such as high strength, relatively high toughness, and good corrosion resistance. However, recent reports of failures at stress levels lower than the accepted limits poses a challenge for its application. Plasma nitriding is known to improve the surface strength of the 17-4 PH and the results from the present work suggests that the nitrided layer formed at low temperature can successfully increase the resistance to SSC for this material.INTRODUCTIONThe oil and gas industry has been facing a major challenge in selecting materials for oilfield components as operations are migrating to ultra-deep water fields where significant amounts of hydrogen sulfide (H2S), carbon dioxide (CO2), and elemental sulfur can lead to premature failures.1 Field failures have been frequently attributed to sulfide stress cracking (SSC), a type of hydrogen damage that occurs due to the combined action of tensile stress and the presence of H2S. The main environmental parameters governing the SSC susceptibility are the H2S partial pressure, the solution pH, and the temperature.2 The chloride content,3 the level of applied stress, and the microstructure of the material are also essential factors. Numerous laboratory tests have been conducted for corrosion resistant alloys under different conditions and there are still failures by SSC detected within the currently acceptable limits of application determined for certain combinations of material and environment. Additionally, there are no mechanisms capable to fully describe the phenomenological aspects of SSC,4,5 although it is commonly accepted to be a form of hydrogen embrittlement. Hence, this phenomenon is still a challenge for materials selection in the oil and gas industry.
Reservoir heterogeneity can be detrimental to the success of surfactant/polymer enhanced-oil-recovery (EOR) processes. Therefore, it is important to evaluate the effect of uncertainty in reservoir heterogeneity on the performance of surfactant/polymer EOR. Usually, a Monte Carlo sampling approach is used, in which a number of stochastic reservoir-model realizations are generated and then numerical simulation is performed to obtain a certain objective function, such as the recovery factor. However, Monte Carlo simulation (MCS) has a slow convergence rate and requires a large number of samples to produce accurate results. This can be computationally expensive when using large complex reservoir models. This study applies a multiscale approach to improve the efficiency of uncertainty quantification. This method is known as the multilevel Monte Carlo (MLMC) method.
This method comprises performing a small number of expensive simulations on the fine-scale model and a large number of less-expensive simulations on coarser upscaled models, and then combining the results to produce the quantities of interest. The purpose of this method is to reduce computational cost while maintaining the accuracy of the fine-scale model. The results of this approach are compared with a reference MCS, assuming a large number of simulations on the fine-scale model. Other advantages of the MLMC method are its nonintrusiveness and its scalability to incorporate an increasing number of uncertainties.
This study uses the MLMC method to efficiently quantify the effect of uncertainty in heterogeneity on the recovery factor of a chemical EOR process, specifically surfactant/polymer flooding. The permeability field is assumed to be the random input. This method is first demonstrated by use of a Gaussian 3D reservoir model. Different coarsening algorithms are used and compared, such as the renormalization method and the pressure-solver method (PSM). The results are compared with running Monte Carlo for the fine-scale model while equating the computational cost for the MLMC method. Both of these results are then compared with the reference case, which uses a large number of runs of the fine-scale model. The method is then extended to a channelized non-Gaussian generated 3D reservoir model incorporating multiphase upscaling.
The results show that it is possible to robustly quantify spatial uncertainty for a surfactant/polymer EOR process while greatly reducing the computational requirement, up to two orders of magnitude compared with traditional Monte Carlo for both the Gaussian and non-Gaussian reservoir models. The method can be easily extended to other EOR processes to quantify spatial uncertainty, such as carbon dioxide (CO2) EOR. Other possible extensions of this method are also discussed.
The petrophysical properties of reservoirs represent several factors such as reservoir quality and volume of oil saturation (PHI, PERM and SW). The relationship between these factors is complementary; migration and trapping of oil is critical to reservoir quality preservation and it is often compromised by closure of the structure, quality of the seal and tectonic activity. In Kuwait, the Mauddud Formation in Bahra Field (BAMA) does not show a sustainable oil production, unlike the Mauddud Formation in Sabriyah Field (SAMA), although both fields are neighboring and separated only by a saddle. Well data reveals a considerable reservoir complexity that distinguishes BAMA from SAMA, which cannot be easily ascribed to facies variability. Geological data (seismic, wireline logs, core and thin sections) indicates four main differences in BAMA compare to SAMA. First, general stratigraphic thinning of carbonate sequences due to its palaeo-proximal position that made it more susceptible to erosion and increased clastic supply and, secondly, a sandier seal rock. Thirdly, there is a degradation of reservoir quality where the average oil saturation and the porosity are 50% and 15% respectively, compared to 90% and 20% In SAMA. Finally, three fault orientations occur in BAMA including a distinct E-W trend, that does not observed in SAMA. Three main possible hypotheses postulated in this study are based on early results. Cementation by meteoric phreatic cements occluded the porosity in BAMA before the arrival of oil. The fresh water penetrations was facilitated by the sandier seal and proximal paleo- environment in BAMA. Onset and partial growth of the trapping structure in SAMA, allowed an earlier oil expulsion to become trapped, retaining secondary porosity, whilst oil bypassed BAMA traps due to later structural growth. The E-W faults in BAMA were responsible for oil migration vertically by breaching the seal rock. The leakage was followed by an influx burial fluids which re-activated cementation in BAMA that was arrested for a short period by the arrival of oil.
Cementation by meteoric phreatic cements occluded the porosity in BAMA before the arrival of oil. The fresh water penetrations was facilitated by the sandier seal and proximal paleo- environment in BAMA.
Onset and partial growth of the trapping structure in SAMA, allowed an earlier oil expulsion to become trapped, retaining secondary porosity, whilst oil bypassed BAMA traps due to later structural growth.
The E-W faults in BAMA were responsible for oil migration vertically by breaching the seal rock. The leakage was followed by an influx burial fluids which re-activated cementation in BAMA that was arrested for a short period by the arrival of oil.