Sleipner Field Research Articles

Tuning effect in time-lapse seismic inversion for CO2 plume monitoring at Sleipner field

Over 20 million tons of CO2‌ have been injected into the sandy Utsira formation of the Sleipner field in the North Sea basin. The thin layering of sands, CO2-saturated sands, and intra-formation thin shales cause interference effects in the seismic response of the monitor surveys. Initial analysis of the amplitude change suggests over 60 % change in the relative acoustic impedance of the reservoir between the 1996 and 2010 surveys. This study follows a multi-stage inversion scheme applied to time-lapse seismic monitoring of the Sleipner field. At each stage, the errors and uncertainties caused by noise and tuning are deeply analyzed. Time-shift estimation from seismic data shows spurious features caused by tuning, specifically using the window-based methods. The time-strain inversion builds a low-frequency initial model for the subsequent model-based inversion but is contaminated by remnants of noise and interference. The synthetic wedge modelling and analysis provides the origins and severity of the tuning error in time-shift and time-strain estimations at the Sleipner field. The model-based inversion removes noise and injects high-frequency components into the results, improving the outcome of time-strain inversion. However, it fails to fully eliminate the tuning imprints and leaves strong traces of error on the results. Afterward, the time-lapse Bayesian seismic inversion slightly adjusts the outcome and shows how deep the influence of interference effect on the time-lapse inversion is. In addition, the complementary discussion on rock physical models in estimating the saturation changes highlights how the tuning error can lead to flawed quantitative interpretation.

Enhancement of CO2 monitoring in the sleipner field (north sea) using seismic inversion based on simulated annealing of time-lapse seismic data

The primary aim of this research is to enhance seismic data interpretation and CO2 monitoring by utilizing seismic inversion techniques based on the simulated annealing method. Simulated annealing is a global optimization technique employed for inverting seismic data and provides better results as compared with local optimization-based inversion. This methodology is implemented in the Utsira Formation, located at a depth of 1000 m within the Sleipner Field, Norway. The study encompasses the analysis of three sets of time-lapse seismic data, first from 1994 (pre-injection), followed by surveys in 1999 and 2001, corresponding to the injection of 2.35 million tonnes and 4.26 million tonnes of CO2, respectively. Firstly, synthetic data is used to check the reliability of the algorithm followed by real data application. This process starts by performing the inversion analysis on the synthetic data which shows a decrease in the impedance values observed at the injection site whereas the seismic amplitude increases. The qualitative as well as quantitative analysis depicts that the algorithm works satisfactorily. The same process is applied to the real data from the Sleipner field. Acoustic impedances are calculated using a simulated annealing-based inversion scheme for the pre-injection case in 1994 and post-injection scenarios in 1999 and 2001. Because of the presence of injected CO2 in the years 1999 and 2001, a low impedance zone that ranged from 2000 m/s*g/cc to 2400 m/s*g/cc appeared at the time interval of 0.85–1.10sec. The interpretation of the inverted impedance section and seismic attribute analysis show no signature of CO2 leakage. The results indicated that the inverted section which is derived from the SA optimization technique shows very clear CO2 information offering a more realistic representation with enhanced resolution of the CO2 plume and its migratory paths.

Implementing 4D seismic inversion based on Linear Programming techniques for CO2 monitoring at the Sleipner field CCS site in the North Sea, Norway

Implementing 4D seismic inversion based on Linear Programming techniques for CO2 monitoring at the Sleipner field CCS site in the North Sea, Norway

CO2 Injection Monitoring: Enhancing Time-Lapse Seismic Inversion for Injected Volume Estimation in the Utsira Formation, Sleipner Field, North Sea

This article presents an in-depth study of CO2 injection monitoring in the Sleipner Field, focusing on the Utsira Formation. The research leverages advanced time-lapse inversion techniques and 4D seismic data analysis to enhance the accuracy of volume estimations and provide a comprehensive understanding of the dynamic behavior of the injected CO2 plume. The analysis encompasses cross correlation, time shift, predictability, and other key elements to yield robust insights into the reservoir’s response to CO2 injection. Cross-correlation analysis results of 60% to 100% outside the injection zone and less than 50% within the injection zone reveal a distinct dissimilarity between the injection and non-injection zones, emphasizing phase, time, and frequency content changes due to CO2 injection. Time shifts are meticulously calibrated globally on a trace-by-trace basis, to account for shallow statics and velocity changes, improving the overall alignment of seismic data. Predictability analysis results of 0 to 0.34 within the injection zone and 0.45 to 0.96 at the background further reinforce the findings, highlighting high predictability values in areas untouched by production and markedly lower values within the injection zone. These results provide a measure of the reliability of the seismic data and its ability to reflect the subtle changes occurring in the reservoir. Crucially, the time-lapse inversion process excels in capturing the evolving state of the CO2 plume within the Utsira Formation. The seismic data reveals the migration and expansion of the plume over time and the dynamic nature of the reservoir’s response to CO2 injection. Integrating various data facets reduces non-uniqueness in inversion results, allowing for more precise volume estimations.

4D Seismic Inversion and Rock Physic Modeling to Monitor CO2 Injection at Carbon Capture and Storage Project in The Utsira Formation, Sleipner Field, North Sea, Norway

Carbon Capture and Storage (CCS) is used at Sleipner Field due to the implementation of a carbon emission tax off the coast of Norway. This project causes the fluid at the Utsira Formation as a reservoir to be replaced by CO2, so the elastic property of the reservoir rock will change. Because of that, the 3D seismic survey was carried out in 1994 (baseline) and re-acquisition in 2001 (monitor) to observe CO2 distribution and changes in rock properties. This study aims to monitor the distribution of CO2 as well as changes in reservoir rock's acoustic and elastic parameters. This research performed the cross-equalization, 4D Seismic Inversion model-based, and rock physics modeling process. From data processing, obtained information that CO2 spreads laterally, then moves to the northeast and does not penetrate the overburden. Also, we get the NRMS value of 0.443068 and the cross-correlation value of 0.907426. 4D Inversion results reveal a change in the reflector at the reservoir zone, as indicated by the velocity pushdown caused for a decrease in seismic velocity owing to CO2. In addition, rock physics modeling provides that changes occur in bulk modulus, Vp, Vs, density, and AI. From the process, there are differences in AI values where the Inversion results show a decrease in AI values of 2.9%, while rock physics modeling shows a 12% reduction.

4-dimensional seismic interpretation to monitor CO2 injection in carbon capture & storage project of Sleipner field, North Sea, Norway using inversion method

Sleipner is the world's first commercial Carbon Capture and Storage (CCS) project, located off the coast of Norway, with the goal of reducing carbon emissions by capturing CO2 and storing it in a utsira saline aquifer sandstone reservoir capable of storing up to 600 billion tonnes of CO2. The CO2 injection in these projects increases year after year, so the CO2 development must be monitored to see the distribution pattern and its implications for the reservoir zone. The purpose of this research is to calculate and model the CO2 distribution resulting from acoustic impedance inversion using 4-dimensional inversion, to calculate the repeatability from seismic data between baseline and monitor using the Normalized Root Mean Square attribute. In the processing, baseline and monitor data must be matched in the overburden zone using a cross-equalization process so that the inversion process. The results revealed a correlation between the two seismic data sets (baseline and monitor) with the classification of Reasonable Repeatability, and CO2 distribution in a securely stored reservoir that spreads laterally and does not leak.

Capillary pressure equilibrium theory mapping of 4D seismic inversion results to predict saturation in a gas-water system

Understanding the effect of fluid concentration in rocks is crucial to characterize a hydrocarbon reservoir. Monitoring of fluid concentration specifically becomes challenging during a sequestration/enhanced oil recovery program because the objective is to understand the amount of initial fluid replaced by liquid/gas injection and identify the probability of leakage with time. The prior assumption of uniform or patchy type of distribution of gas in a rock-physics theory leads to large uncertainty in the prediction of saturation. As a result, we have used the capillary pressure equilibrium theory (CPET) for creating a reservoir model that matches the physics of capillary-induced fluid invasion and avoids the uncertainty related to the type of distribution of gas in pores. We create a CPET model using the reservoir parameters of the clean and unconsolidated sandstone formation of the Sleipner field, North Sea, which is the world’s first industrial-scale CO2-injection project, assuming that there is no significant change in the rock frame throughout the field. The model is then used to analyze the fluid content from the time-lapse seismic inversion results of the Sleipner field. CO2 at higher quantities, according to our research, is analogous to a uniform distribution, whereas CO2 at lower concentrations is mostly in between patchy and uniform distribution or slightly patchy type. We predict maximum CO2 saturation from a quantitative interpretation of six time-lapse seismic data from 1999 to 2010 using the CPET as 75% of the pore space, and the footprint of the CO2 plume in the topmost layer is spreading from zero in 2001 to 7 × 105 m2 in 2010. Our model finds that injected CO2 from all layers below will migrate to the top layer approximately 50 years after the commencement of the injection.

Integrated machine learning and physics-based workflows for rapid qualitative and quantitative insights on monitoring carbon capture and sequestration

With the onset of extensive development and focus on clean and sustainable sources of energy, our subsurface geoscience tools and technologies can be effectively repurposed and evolved to support the energy transition. These sustainable energy sources are easily replenishable and low carbon. Some of the emerging sectors are geothermal energy, carbon capture and sequestration (CCS), energy storage, offshore wind energy, sustainable battery-grade lithium extraction, and hydrogen production. These sectors can benefit immensely from economically viable geophysical tools that are available at our disposal to deliver better and faster business outcomes. In this paper we will discuss the integrated machine learning (ML) and physics-based workflows that can be used for enabling effective and rapid energy transition solutions. In our study we will focus on CCS subsurface monitoring workflows, but the same methods have been applied to many other energy transition areas (for example, offshore wind and geothermal energy). The integrated workflows mentioned above were applied on the Sleipner gas field in the North Sea, where CCS operations have been ongoing since 1996. Rapid qualitative workflows like amplitude analysis and seismic blending were used to build an initial understanding of the carbon dioxide (CO2) plume and its spread. Geoscientist-driven ML-assisted horizon mapping facilitated rapid interpretation of structure across different time vintages. Then, advanced techniques like amplitude vs. offset (AVO) analysis and time-lapse seismic inversion were used for quantitative analysis. These analyses gave comprehensive information on CO2 spread in each subformation, as well as an estimate of the changing CO2 volume through time. These workflows can be applied in CCS operations to successfully monitor CO2 in the subsurface and quickly detect and assess the risk of leaks.

Seismic low-frequency shadows and their application to detect CO2 anomalies on time-lapse seismic data: A case study from the Sleipner Field, North Sea

The detection and underlying mechanism of prospect-scale seismic low-frequency shadows (LFSs) has been an issue of debate. Even though the concept of LFS is widely accepted, the practical applicability of the method remains limited due to few real field case studies and little understanding of the underlying attenuation mechanism. To characterize the attenuation phenomenon responsible for the occurrence of LFS in CO2-saturated formations, we use the diffusivity and viscosity of the fluid-saturated medium to derive a complex velocity function that characterizes a high-frequency attenuation phenomenon responsible for the occurrence of LFS in a CO2-saturated formation. Synthetic seismic data sets representing pre- and post-CO2 injection scenarios are generated using 2D diffusive-viscous equations to model the LFS and understand its occurrence mechanism. Furthermore, to demonstrate the applicability of LFS in a real field, a spectral decomposition analysis of time-lapse 3D seismic data of the Sleipner Field, North Sea, is carried out using the continuous wavelet transform. The LFSs are clearly detected below the reservoir base at frequencies lower than 30 Hz in the post-CO2 injection surveys. It is shown that the seismic low-frequency shadows are not artifacts but occur due to attenuation of the high-frequency components of the propagating seismic waves in the CO2-saturated Utsira Formation. The attenuation of these frequencies is a result of the diffusivity and viscosity of the fluid-saturated medium. The LFSs are localized anomalies at the base of the formation; hence, with the present approach, these anomalies cannot be related to the migration of the CO2 plume in the Utsira Formation.

Bayesian rock-physics inversion: Application to CO2 storage monitoring

Risk assessment of [Formula: see text] storage requires the use of geophysical monitoring techniques to quantify changes in selected reservoir properties such as [Formula: see text] saturation, pore pressure, and porosity. Conformance monitoring and the associated decision making rest upon the quantified properties derived from geophysical data, with uncertainty assessment. We have developed a general framework combining seismic and controlled-source electromagnetic (CSEM) inversions with rock-physics inversion with fully Bayesian formulations for proper quantification of uncertainty. The Bayesian rock-physics inversion rests upon two stages. First, a search stage consists of exploring the model space and deriving models with the associated probability density function (PDF). Second, an appraisal or importance sampling stage is used as a “correction” step to ensure that the full model space is explored and that the estimated posterior PDF can be used to derive quantities such as marginal probability densities. Both steps are based on the neighborhood algorithm. The approach does not require any linearization of the rock-physics model or assumption about the model parameters’ distribution. After describing the [Formula: see text] storage context, the available data at the Sleipner field before and after [Formula: see text] injection (baseline and monitor), and the rock-physics models, we perform an extended sensitivity study. We find that prior information is crucial, especially in the monitor case. We determine that joint inversion of seismic and CSEM data is also key to properly quantifying [Formula: see text] saturations. Finally, we apply the full inversion strategy to real data from Sleipner. We obtain rock frame moduli, porosity, saturation, and patchiness exponent distributions and the associated uncertainties along a 1D profile before and after injection. The results are consistent with geology knowledge and reservoir simulations, i.e., that the [Formula: see text] saturations are larger under the caprock confirming the [Formula: see text] upward migration by buoyancy effect. The estimates of the patchiness exponent have a larger uncertainty, suggesting semipatchy mixing behavior.

Influence of reservoir-scale heterogeneities on the growth, evolution and migration of a CO2 plume at the Sleipner Field, Norwegian North Sea

New analysis of the baseline (pre-injection) seismic data at Sleipner has revealed large-scale, roughly north-trending, channelled ‘fairways’ at a range of stratigraphical levels in the Utsira Sand. The baseline data also reveal localised stratigraphical ‘point discontinuities’ within the reservoir, some of which show evidence of having provided vertical conduits for earlier natural gas flow. The repeat time-lapse seismic datasets, where finer details of reservoir geology are illuminated by the reflective CO2, show smaller-scale, north-trending and sometimes sinuous channels within the larger channel fairways. They also show a number of vertical CO2 pathways within the CO2 plume, corresponding to the point discontinuities seen on the baseline data.Reservoir flow models were set up with flow properties constrained only by the observed levels of CO2 accumulation in the reservoir and the arrival time of CO2 at the reservoir top just prior to the first repeat seismic survey in 1999. The initial model with laterally homogeneous sand units separated by thin semi-permeable mudstones achieved only a moderate match to the observed time-lapse seismic data. Subsequent flow models, progressively incorporating higher permeability vertical CO2 pathways through the mudstones and large-scale channel fairways within the reservoir sands, yielded a progressive and marked improvement in the history-match of key CO2 layers within the plume. Crucially, no layer-specific model calibration was employed to achieve this improvement.New geophysical measurements from Utsira Sand core have recently become available. These measurements provide important constraints on rock physics models of CO2 and brine mixtures in the Utsira Sand. An empirical Brie fluid mixing law for intermediate fluid saturations provides a good fit to the new laboratory data, allowing measurements of CO2 saturation to be converted into seismic velocity. This rock physics model was used to convert CO2 saturation distributions predicted by the most realistic reservoir model into a seismic velocity model of the CO2 plume. Synthetic seismic reflectivity profiles generated using this velocity model show a striking resemblance to the observed time-lapse seismic data, both in terms of plume layer reflectivity and also of time-shifts within and beneath the CO2 plume. This provides confidence in the fidelity of the preferred reservoir model solution.These results represent a significant breakthrough in the understanding and modelling of CO2 plume development at Sleipner. We emphasise that the improvements were brought about not by fine tuning reservoir properties to fit the observed time-lapse data, but simply by incorporating geological permeability features that can reasonably be inferred from the baseline seismic data.

Prediction of Elastic Properties Within CO2 Plume at Sleipner Field Using AVS Inversion Modified for Thin‐Layer Reflections Guided by Uncertainty Estimation

AbstractExisting amplitude variation with offset (AVO) and slowness (AVS) theories fail to interpret observed amplitudes in terms of actual elastic properties of the media for a reflection event resulting from a stack of thin layers. We propose a method to replace the stack of thin layers with an equivalent medium of elastic properties using the Backus averaging theory. Numerical examples show considerable deviation in intercept calculated from the modified AVO and AVS theories from the conventional methods. AVS theory is preferred as it can be applied irrespective of impedance contrast in both precritical and postcritical reflections, and no spherical divergence correction is required. P and S wave velocities, density, and thickness of thin layers are determined using the inversion scheme of very fast simulated annealing (VFSA). Uncertainty in prediction is evaluated using an approximate marginal posterior probability density function and a parameter correlation matrix. We demonstrate our methodology on synthetic and real seismic data from the Sleipner field, which is a good example of enhanced seismic amplitudes due to interference among reflections from thin layers. We select 11 common depth point (CDP) gathers for amplitude analysis of four identified reflectors along a line of 3‐D seismic data acquired in 2008. Predicted mean models of CO2‐saturated sand layers at all locations show that the thickness, density, and P and S wave velocities vary from 5–7 m, 1.8–2.0 g/cm3, and 1,460–1,490 and 630–650 m/s, respectively. Our analysis suggests that the model parameters are well constrained and independent except at a few locations.

Analysing the role of caprock morphology on history matching of Sleipner CO2 plume using an optimisation method

AbstractGeological carbon storage is a promising solution to reduce the CO2 concentration in the atmosphere to ameliorate the effects of global warming from the greenhouse effect. Among feasible storage options, deep saline aquifers are believed to have the largest storage capacity for the gas collected from industrial processes. The first CO2 storage project at a commercial scale in a saline aquifer is in the Sleipner field of the Utsira storage formation in Norway. The long ongoing storage operation in the Sleipner field has been the subject of several past studies attempting to recreate the observed injected CO2 plume migration behaviour. History matching is a method to adjust the input parameters of the model in a way to minimise the mismatch between the simulated and the actual production data in reservoir engineering and applicable to carbon sequestration. Typical parameters adjusted in history matching are porosity, absolute and relative permeability data. In this study, we used an adjoint‐based optimisation tool and showed the importance of caprock morphology in finding an accurate plume match. Using a set of synthetic models, we initially minimised the mismatch between the observed and simulated CO2 plume outline by modifying the caprock topographical details. After testing the optimisation tool on the synthetic models, we applied the methodology to the Sleipner benchmark 2019 model and improved the plume match by locally adjusting caprock elevation within seismic detection limits. We subsequently improved the match by calibrating porosity, permeability, CO2 density and injection rate together in an experiment in which we calibrated all the parameters, including the caprock morphology, to find a better match. The results showed an improvement of around 8% (compared with the original model) in the plume match resulting from an average absolute elevation change of 3.23 m in the model while keeping the other parameters constant. Calibrating the porosity, permeability, CO2 density and injection rate resulted in a 5% improvement in the match, and once caprock morphology was included in the optimisation process, the match improvement increased by 16%. We changed the caprock elevation within a range lower than the seismic detection limit, and results showed that even a few metres variations in the elevation have significant impacts on the plume migration and trapping mechanism in the Sleipner model. The method presented in this work results in a better match than the original seismic data for the Sleipner model. © 2020 The Authors. Greenhouse Gases: Science and Technology published by Society of Chemical Industry and John Wiley & Sons, Ltd.

Assessing the impact of relative permeability and capillary heterogeneity on Darcy flow modelling of CO2 storage in Utsira Formation

AbstractPredicting CO2 plume migration is an important aspect for the geological sequestration of CO2. In the absence of experimental data, the storage performance of CO2 geo‐storage can be assessed through the dynamic modelling of the fluid flow and transport properties of the rock‐fluid system using empirical formulations. Using the van Genuchten empirical model, this study documents a Darcy flow modelling approach to investigate different aspects of CO2 drainage in a sandstone formation with interbedded argillaceous (i.e. mudstone) units. The numerical simulation is based on the Sleipner gas field storage unit where several thin argillite layers occur within the sandstone of the Utsira Formation. With respect to forward modelling simulations that have used Sleipner Formation as a case study, it is noted that previous attempts to numerically calibrate the CO2 plume migration to time‐lapse seismic dataset using software governed by Darcy flow physics achieved poor results. In this study, CO2‐brine buoyant displacement pattern is simulated using the ECLIPSE ‘black oil’ simulator within a two‐dimensional axisymmetric geometry and a three‐dimensional Cartesian coordinate system. This investigation focussed on two key parameters affecting CO2 migration mobility, namely relative permeability and capillary forces. Examination of these parameters indicate that for the gravity current of CO2 transiting through a heterogeneous siliciclastic formation, the local capillary forces in geologic units, such as mudstone and sandstones, and the relative permeability to the invading fluid control the mass of CO2 that breaches and percolates through each unit, respectively. In numerical analysis, these processes influence the evaluation of structural and residual trapping mechanisms. Consequently, the inclusion of heterogeneities in capillary pressure and relative permeability functions, where and when applicable, advances a Darcy modelling approach to history matching and forecasting of reservoir performance. Results indicate that there is a scope for a revision of the basic premise for modelling flow properties in the interbedded mudstones and the top sand wedge at the Sleipner Field when using Darcy flow simulators. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd.

Effect of temperature and concentration of impurities in the fluid stream on CO2 migration in the Utsira formation

A satisfying history match of CO2 plume migration in the Sleipner field of the Utsira formation has been difficult to achieve using multiphase flow simulations. Poor modeling of plume or reservoir temperature and impurities in the CO2 stream have been cited as a source of uncertainty in model predictions. Both of these aspects can have a large impact on the simulation results of plume migration in the Sleipner field where the injected fluid is close to the critical point of CO2. We have performed multiphase flow simulations in the uppermost sand layer of the Sleipner field (Layer 9) over a range of temperatures and fluid compositions in order to clarify these uncertainties. The results reveal that an increase in temperature by a few degrees and simultaneously accounting for impurities from the separation process lead to significantly improved comparison with seismic data. Between temperature and fluid composition, temperature was the most important predictor for success. The results of this study imply that the impact of temperature on model predictions has previously been underestimated. Implementation of a realistic temperature and fluid composition will lead to better prediction of plume mobility and storage capacity, which is important for screening and planning of optimal storage sites.

Perspectives of Geological CO2 Storage in South Korea to Cope with Climate Change

Rapid industrialization and urbanization in the 20th century have led to increasing volumes of carbon dioxide being released into the atmosphere[...]

Benchmarking of vertically-integrated CO2 flow simulations at the Sleipner Field, North Sea

Numerical modeling plays an essential role in both identifying and assessing sub-surface reservoirs that might be suitable for future carbon capture and storage projects. Accuracy of flow simulations is tested by benchmarking against historic observations from on-going CO2 injection sites. At the Sleipner project located in the North Sea, a suite of time-lapse seismic reflection surveys enables the three-dimensional distribution of CO2 at the top of the reservoir to be determined as a function of time. Previous attempts have used Darcy flow simulators to model CO2 migration throughout this layer, given the volume of injection with time and the location of the injection point. Due primarily to computational limitations preventing adequate exploration of model parameter space, these simulations usually fail to match the observed distribution of CO2 as a function of space and time. To circumvent these limitations, we develop a vertically-integrated fluid flow simulator that is based upon the theory of topographically controlled, porous gravity currents. This computationally efficient scheme can be used to invert for the spatial distribution of reservoir permeability required to minimize differences between the observed and calculated CO2 distributions. When a uniform reservoir permeability is assumed, inverse modeling is unable to adequately match the migration of CO2 at the top of the reservoir. If, however, the width and permeability of a mapped channel deposit are allowed to independently vary, a satisfactory match between the observed and calculated CO2 distributions is obtained. Finally, the ability of this algorithm to forecast the flow of CO2 at the top of the reservoir is assessed. By dividing the complete set of seismic reflection surveys into training and validation subsets, we find that the spatial pattern of permeability required to match the training subset can successfully predict CO2 migration for the validation subset. This ability suggests that it might be feasible to forecast migration patterns into the future with a degree of confidence. Nevertheless, our analysis highlights the difficulty in estimating reservoir parameters away from the region swept by CO2 without additional observational constraints.

Alternative Routes to Hydrate Formation during Processing and Transport of Natural Gas with a Significant Amount of CO2: Sleipner Gas as a Case Study

Carbon dioxide from the Sleipner gas field in the North Sea has now been injected into the Utsira Formation for more than 20 years. A million tons of carbon dioxide per year is transported and injected. Conditions of temperatures and pressures in the injection pipeline as well as inside the reservoir are outside hydrate-forming conditions. Transport pipelines, on the other hand, are subject to low temperatures and high pressures, which can potentially lead to hydrate formation. In this work, we examine some possible routes to hydrate formation and the consequences for maximum amounts of water that can be permitted to follow the gas. A conventional hydrate risk evaluation involves calculation of water dew point concentrations in the gas as an upper tolerance limit for preventing liquid water to drop out from the gas and eventually form hydrates. Pipelines are rusty even from the moment they are placed on the seafloor in the North Sea. Initially this rust consists of various forms of iron oxides. Hematite (...

Uncertainty Quantification in Waveform-based Imaging Methods - a Sleipner CO2 Monitoring Study

Full Waveform Inversion (FWI) and Controlled Source Electro-Magnetic (CSEM) inversion can provide quantitative estimates of selected subsurface properties. In the context of CO2 monitoring, FWI has the capability to locate and image a CO2 plume, seen as velocity changes caused by the injected CO2, while CSEM can be useful to determine the CO2 saturation. Quantifying the uncertainty of the reconstructed parameters is however challenging. In this study, preliminary work has been performed to assess the reliability of the results obtained using CSEM and FWI when monitoring CO2 storage at the Sleipner field offshore Norway. This paper begins with a brief review of the imaging techniques used. Then the uncertainty quantification methodology is described. Finally, preliminary results of uncertainty quantification for two CO2 monitoring examples, one synthetic case using CSEM and one real data case using FWI, are presented. For the synthetic CSEM case, the inversion of the EM data has a very positive effect on the uncertainty, clearly reducing the covariance of the probability distribution for possible conductivity models as compared to the prior knowledge of these models. For the real, rather large-scale FWI case, computationally efficient strategies had to be used. The covariance in this case is not reduced to the same extent as for the CSEM case, but an improvement is observed. In both cases, the quantification approach works as expected providing a means to assess the quality of obtained subsurface models. For future studies, a more formal way of providing prior model knowledge and a stricter formulation of the Bayesian inverse problem will be employed.

A model for CO2 storage and seismic monitoring combining multiphase fluid flow and wave propagation simulators. The Sleipner-field case

The main objective of this paper is to use a flow simulator to represent the CO2 storage and combine it with a wave propagation simulator in order to obtain synthetic seismograms qualitatively matching time-lapse real field data. The procedure is applied to the Utsira formation at Sleipner field. The field data at the site available to us is a collection of seismic sections (time-lapse seismics) used to monitor the CO2 storage. An estimate of the CO2 injection rate and the location of the injection point are known. Using these data, we build a geological model, including intramudstone layers with openings, whose coordinates are defined by performing a qualitative match of the field seismic data. The flow simulator parameters and the petrophysical properties are updated to obtain CO2 saturation maps, including CO2 plumes, so that the synthetic seismic images resemble the real data. The geological model is based on a porous-media constitutive equation. It considers a poroelastic description of the Utsira formation (a shaly sandstone), based on porosity and clay content, and takes into account the variation of the properties with pore pressure and fluid saturation. Moreover, the model considers the geometrical features of the formations, including the presence of shale seals and fractures. We also assume fractal variations of the petrophysical properties. The numerical simulation of the CO2-brine flow is based on the Black-Oil formulation, which uses the pressure-volume-temperature (PVT) behavior as a simplified thermodynamic model. The corresponding equations are solved using a finite difference IMPES formulation. Using the resulting saturation and pore-pressure maps, we determine an equivalent viscoelastic medium at the macroscale, formulated in the space-frequency domain. Wave attenuation and velocity dispersion, caused by heterogeneities formed of gas patches, are described with White’s mesoscopic model. The viscoelastic wave equation is solved in the space-frequency domain for a collection of frequencies of interest using a finite-element iterative domain decomposition algorithm. The space-time solution is recovered by a discrete inverse Fourier transform, allowing us to obtain our synthetic seismograms. In the numerical examples, we determine a set of flow and petrophysical parameters allowing us to obtain synthetic seismograms resembling actual field data. In particular, this approach yields CO2 accumulations below the mudstone layers and synthetic seismograms which successfully reproduce the typical pushdown effect.