Time-lapse Seismic Data Research Articles

Analysis of Time-Lapse Seismic and Production Data for Systematic Reservoir Model Classification and Assessment

The heterogeneous distribution of reservoir properties is one of the most important uncertainties in static and dynamic reservoir modelling. Petrophysical properties are usually interpolated within reservoir models from sparse well-log data, which can lead to highly uncertain estimates at inter-well locations that directly affect the reliability of fluid-flow model predictions of reservoir behavior. To address this issue, we build an ensemble of equiprobable models that combine different geostatistical realizations of reservoir properties to span the range of potential outcomes. While this process captures the impact of reservoir property distributions on the model response, a major challenge is classifying the subset of models in the ensemble best representing reservoir fluid-flow behavior. Thus, we introduce a methodology combining 4D seismic amplitude attributes and reservoir production data to classify fluid-flow models. This classification is based on applying thresholds for independent seismic and production objective functions. We test our methodology on the benchmark case UNISIM-I developed from observations from the Namorado Field, Campos Basin, Brazil. By comparing injection and production rates in relation to 4D seismic amplitude trends, we identify nine models out of an ensemble of 100 that judged optimal via the required seismic and production objective function thresholds and obtain an improved quantitative evaluation of the impact of reservoir production on the 4D seismic signal. Ultimately, combining seismic and production data offers interpretation scenarios that automatically identify realistic fluid-flow models that can assist the update of permeability and porosity distributions within the reservoir.

Qualitative time-lapse seismic interpretation of Norne Field to assess challenges of 4D seismic attributes

Interpretation of time-lapse (or 4D) seismic data in terms of reservoir changes due to production posed many challenges in the Norne Field as the field experienced intense production activity from 1997 to 2006. For some segments within the field, fluid movement and pressure changes have approximately the same degree of impact and possibly opposite effects on the seismic data. Moreover, hardening anomalies could be caused by the increase in water saturation or gas going back to solution, while softening anomalies could be related to the increase in pore pressure or the decrease in fluid bulk modulus following the injection of gas. Therefore, for time-lapse seismic analysis to be most effective and less erroneous, different seismic attributes must be addressed to infer reservoir changes caused by production activity such as seismic amplitude and impedance derived by seismic inversion. In the present work, we analyze the challenges of 4D seismic interpretation in the Norne benchmark case. Our study indicates that acoustic impedance differences derived by a 4D model-based inversion provide an increase in vertical resolution compared to standard seismic amplitude differences. We also present a comparison between results of 4D model-based and colored inversions to evaluate the confidence of inversion anomalies. As this is a benchmark case, this study can be considered to enrich the discussions over qualitative and quantitative time-lapse seismic interpretation and to improve reservoir characterization.

3D Hydraulic-Fracture Simulation Integrated With 4D Time-Lapse Multicomponent Seismic and Microseismic Interpretations, Wattenberg Field, Colorado

Summary The 3D hydraulic-fracture-simulation modeling was integrated with 4D time-lapse seismic and microseismic data to evaluate the efficiency of hydraulic-fracture treatments within a 1 sq mile well-spacing test of Wattenberg Field, Colorado. Eleven wells were drilled, stimulated, and produced from the Niobrara and Codell unconventional reservoirs. Seismic monitoring through 4D time-lapse multicomponent seismic data was acquired by prehydraulic fracturing, post-hydraulic fracturing, and after 2 years of production. The results from the simulation modeling and seismic monitoring show the significant effect of reservoir heterogeneity on hydraulic-fracture stimulation and hydrocarbon production. A hydraulic-fracture-simulation model using a 3D numerical simulator was generated and analyzed for hydraulic-fracturing efficiency and interwell fracture interference between the 11 wells. The 3D hydraulic-fracture simulation is validated using observations from microseismic and 4D multicomponent [compressional-wave (P-wave) and shear-wave (S-wave)] seismic interpretations. The validated 3D simulation results reveal that variations in reservoir properties (faults, rock-strength parameters, and in-situ stress conditions) influence and control hydraulic-fracturing geometry and stimulation efficiency. The integrated results are used to optimize the development of the Niobrara Formation within Wattenberg Field. The valuable insight obtained from the integration is used to optimize well spacing, increase reserves recovery, and improve production performance by highlighting intervals with bypassed potential within the Niobrara. The methods used within the case study can be applied to any unconventional reservoir.

Gradient-based Pareto optimal history matching for noisy data of multiple types

The advantages of the simultaneous integration of production and time-lapse seismic data for history matching have been demonstrated in a number of previous studies. Production data provide accurate observations at particular spatial locations (wells), while seismic data enable global, though filtered/noisy, estimates of state variables. In this work, we present an efficient computational tool for bi-objective history matching, in which data misfits for both production and seismic measurements are minimized using an adjoint-gradient approach. This enables us to obtain a set of Pareto optimal solutions defining the optimal trade-off between production and seismic data misfits (which are, to some extent, conflicting). The impact of noise structure and noise level on Pareto optimal solutions is investigated in detail. We discuss the existence of the “best” trade-off solution, or least-conflicting posterior model, which corresponds to the history-matched model that is expected to provide the least-conflicting forecast of future reservoir performance. The overall framework is successfully applied in 2D and 3D compositional simulation problems to provide a single least-conflicting posterior model and, for the 2D case, multiple samples from the posterior distribution using the randomized maximum likelihood method.

Assimilating spatially dense data for subsurface applications—balancing information and degrees of freedom

The degrees of freedom (DOF) in standard ensemble-based data assimilation is limited by the ensemble size. Successful assimilation of a data set with large information content (IC) therefore requires that the DOF is sufficiently large. A too small number of DOF with respect to the IC may result in ensemble collapse, or at least in unwarranted uncertainty reduction in the estimation results. In this situation, one has two options to restore a proper balance between the DOF and the IC: to increase the DOF or to decrease the IC. Spatially dense data sets typically have a large IC. Within subsurface applications, inverted time-lapse seismic data used for reservoir history matching is an example of a spatially dense data set. Such data are considered to have great potential due to their large IC, but they also contain errors that are challenging to characterize properly. The computational cost of running the forward simulations for reservoir history matching with any kind of data is large for field cases, such that a moderately large ensemble size is standard. Realization of the potential in seismic data for ensemble-based reservoir history matching is therefore not straightforward, not only because of the unknown character of the associated data errors, but also due to the imbalance between a large IC and a too small number of DOF. Distance-based localization is often applied to increase the DOF but is example specific and involves cumbersome implementation work. We consider methods to obtain a proper balance between the IC and the DOF when assimilating inverted seismic data for reservoir history matching. To decrease the IC, we consider three ways to reduce the influence of the data space; subspace pseudo inversion, data coarsening, and a novel way of performing front extraction. To increase the DOF, we consider coarse-scale simulation, which allows for an increase in the DOF by increasing the ensemble size without increasing the total computational cost. We also consider a combination of decreasing the IC and increasing the DOF by proposing a novel method consisting of a combination of data coarsening and coarse-scale simulation. The methods were compared on one small and one moderately large example with seismic bulk-velocity fields at four assimilation times as data. The size of the examples allows for calculation of a reference solution obtained with standard ensemble-based data assimilation methodology and an unrealistically large ensemble size. With the reference solution as the yardstick with which the quality of other methods are measured, we find that the novel method combining data coarsening and coarse-scale simulations gave the best results. With very restricted computational resources available, this was the only method that gave satisfactory results.

Assisted seismic history matching of the Nelson field: Managing large numbers of unknowns by divide and conquer

Automatic history matching may be used to condition reservoir simulation models with time-lapse seismic data. Stochastic optimization algorithms are used to perform a good search of the parameter space to ensure effective determination of the best models. These approaches can require many thousands of simulations for large dimensional problems. Divide and conquer is an assisted history matching approach that enables deconvolution of the parameters so that they can be searched more efficiently and also leads to better uncertainty analysis.We present an application of this approach on the Nelson field. Nine years of production history data are used along with baseline and monitor seismic surveys. Localised variations were made to permeability and net-to-gross ratio in the model. The reservoir was divided into separate parameter regions by combining experimental design and proxy model analysis. The former enabled insignificant parameters to be discarded while the latter showed that each region could be treated as a separate history matching sub-problem. Each sub-problem was then solved simultaneously using an adapted stochastic neighbourhood algorithm.The results show that a forty-two dimensional problem could be reduced to a combination of three 9D problems and a 3D problem due to the spatial deconvolution of parameters and misfits. An improved match was obtained for the production and seismic data. Compared to a full stochastic search of the parameter space, the number of required models was several orders of magnitude smaller. Improved uncertainty analysis was made possible resulting in better understanding of the future behaviour of the reservoir.An improved match to reservoir models leads to better confidence in their prediction and thus they can be used more effectively in reservoir management. The method presented here to improve the match retains the benefits of stochastic searching without the penalty of requiring an impractical number of simulations.

Modeling of time-lapse seismic monitoring using CO2 leakage simulations for a model CO2 storage site with realistic geology: Application in assessment of early leak-detection capabilities

Time-lapse surface seismic surveys have been widely used at carbon sequestration sites for site characterization, monitoring subsurface CO2 plume migration, and detecting potential CO2 leakage from a storage reservoir. Monitoring in the first permeable unit directly above the primary seal is important for early detection of CO2 leakage. Forward modeling of time-lapse seismic data can be used to assess the utility of the seismic method for CO2 leakage detection. We develop a workflow for forward modeling of time-lapse seismic data, including constructing seismic velocity models using flow simulation outputs, modeling of pre-stack and post-stack synthetic seismic data following seismic data processing sequence and analysis of processed synthetic time-lapse seismic data. We apply the forward modeling and analysis workflow to assessing the detectability and the earliest detection time of seismic monitoring using the hypothetical CO2 leakage scenarios for a model geologic storage site with realistic geology. We derive the detection thresholds using the simulated normalized root-mean-square (NRMS) differences for the no-leakage case at a range of signal-to-noise ratios, representing the background noise levels in seismic data. We then compare NRMS differences triggered by the CO2 leakage to the detection thresholds at each time step to quantify the detectability and the earliest detection time of seismic monitoring. We analyze the effects of the acquisition parameters and elastic parameters on the produced synthetic seismic data and earliest detection time. Our modeling results indicate that high signal-to-noise ratio is needed to detect the CO2 leakage at the model site. Minimizing the background noise in seismic data is crucial for improving the detectability of the seismic method. Increasing the shot density or increasing the dominant frequency of the source wavelet is likely to increase the possibility of the leakage detection and reduce the time needed for the detection. The elastic parameters used in the rock physics modeling have significant effects on the resultant seismic velocity models and synthetic seismic data, highlighting their critical roles in understanding and interpreting time-lapse seismic reflection data associated with CO2 monitoring, verification and accounting activities.

Correction of seismic time-lapse data with different geometries

ABSTRACTIn the interpretation of time-lapse seismic data, we first assume that basal and monitor seismic data have been gathered and processed under equal condition. Basically having two sets of seismic data (basal and monitor data) does not confirm the possibility of 4D seismic data analysis and repeatability term commands that data should have equal data gathering and process condition. This is due to the low vertical resolution of seismic data which makes the changes in amplitude of seismic in basal and monitoring operations to occur finitely. Therefore, differences in amplitudes in two seismic surveys that have a source other than variations in reserval fluid saturation cause errors in 4D interpretations. In this paper, we represent a procedure to unify different geometries and also study post-stack processing methods for seismic time-lapse data and execute them on existing data at the studied field. In the, first step geometrical conception of basal and monitoring data should be equalized. This section has been implemented using a new methodology, developed in this paper and is called “similarity table”. Then, data will be analyzed with spectra point of view and by executing shaping filters and by using cross equalization approach, basal and monitor seismic information will be closer as far as possible. Finally, analyzes were performed to validate the obtained results and evaluate the quality of time -lapse seismic analyzes.

Common-focus point-based target-oriented imaging approach for continuous seismic reservoir monitoring

The ideal approach for continuous reservoir monitoring allows generation of fast and accurate images to cope with the massive data sets acquired for such a task. Conventionally, rigorous depth-oriented velocity-estimation methods are performed to produce sufficiently accurate velocity models. Unlike the traditional way, the target-oriented imaging technology based on the common-focus point (CFP) theory can be an alternative for continuous reservoir monitoring. The solution is based on a robust data-driven iterative operator updating strategy without deriving a detailed velocity model. The same focusing operator is applied on successive 3D seismic data sets for the first time to generate efficient and accurate 4D target-oriented seismic stacked images from time-lapse field seismic data sets acquired in a [Formula: see text] injection project in Saudi Arabia. Using the focusing operator, target-oriented prestack angle domain common-image gathers (ADCIGs) could be derived to perform amplitude-versus-angle analysis. To preserve the amplitude information in the ADCIGs, an amplitude-balancing factor is applied by embedding a synthetic data set using the real acquisition geometry to remove the geometry imprint artifact. Applying the CFP-based target-oriented imaging to time-lapse data sets revealed changes at the reservoir level in the poststack and prestack time-lapse signals, which is consistent with the [Formula: see text] injection history and rock physics.

Analysis of time-lapse seismic and production data for reservoir model classification and assessment

Analysis of time-lapse seismic and production data for reservoir model classification and assessment

Deterministic ensemble smoother with multiple data assimilation as an alternative for history-matching seismic data

This paper reports the results of an investigation on the use of a deterministic analysis scheme combined with the method ensemble smoother with multiple data assimilation (ES-MDA) for the problem of assimilating a large number of correlated data points. This is the typical case when history-matching time-lapse seismic data in petroleum reservoir models. The motivation for the use of the deterministic analysis is twofold. First, it tends to result in a smaller underestimation of the ensemble variance after data assimilation. This is particularly important for problems with a large number of measurements. Second, the deterministic analysis avoids the factorization of a large covariance matrix required in the standard implementation of ES-MDA with the perturbed observations scheme. The deterministic analysis is tested in a synthetic history-matching problem to assimilate production and seismic data.

Real-time microseismic overburden surveillance at the Grane PRM field offshore Norway

Real-time microseismic detection at offshore hydrocarbon fields is on its way to becoming a standard monitoring tool. Recently, increased focus on injection and overburden surveillance for an improved health, safety and environment (HSE) and cost saving has led to this development. Several hydrocarbon fields are already equipped with permanent reservoir monitoring (PRM) systems with seismic sensors permanently installed at the seafloor (Caldwell et al., 2015), and similar installations are planned or under consideration for some other offshore fields. PRM systems are in principle designed for acquiring active time-lapse seismic data 1-2 times per years, and as such, they are not used during most of their lifetime. But apart from active seismic, PRM systems can also be used for recording passive seismic data. With appropriate processing and analysis methods, such as microseismic event detection, the continuous stream of passive data can be converted into useful real-time subsurface information. This results in improved HSE, and therefore a more valuable PRM system. In 2014, a mini-PRM system with 172 multi-component sensors was installed at the Oseberg field, offshore Norway. The mini-PRM system indeed demonstrated the feasibility of injection and overburden surveillance using real-time passive seismic (Bussat et al., 2016). Despite high installation costs, a cost/benefit evaluation shows net benefits for the Oseberg system owing to better control on waste injection rates. The next step, and topic of the current paper, is to scale up and transfer the learnings from the small Oseberg system to the large Grane PRM system, so as to enable processing and analysis of large amounts of passive data and allow for real-time injection monitoring at Grane. Compared to the Oseberg case, the microseismic data processing is distributed and optimized to be able to use many more sensors and monitor larger subsurface volumes with increased resolution. Moreover, the detection method is improved from an originally strict semblance-based method to also include signal-to-noise (S/N) analysis of the semblance-weighted stack. Crucial noise filtering is integrated into the real-time processing flow, enhancing the sensitivity of the system and ensuring the best possible detection/localization at any time. Key personnel receive an alert immediately after an event detection. This makes the monitoring fully integrated into the follow-up of the daily operation.

A multiobjective Markov chain Monte Carlo approach for history matching and uncertainty quantification

We present a probabilistic approach for integrating multiple data types into subsurface flow models. Our approach is based on a Bayesian framework whereby we exhaustively sample the multi-dimensional posterior distribution to define a Pareto front which represents the trade-off between multiple objectives during history matching. These objectives can be matching of water-cut, GOR, BHP and time-lapse seismic data. For field applications, these objectives do not necessarily move in tandem because of measurement errors and also interpretative nature of the seismic data.Our proposed method is built on a Differential Evolution Markov Chain Monte Carlo (DEMC) algorithm in which multiple Markov Chains are run in parallel. First, a dominance relationship is established amongst multiple models. This is followed by construction of the posterior distribution based on a hypervolume measure. A unique aspect of our method is in the parameter proposal generation which is based on a random walk on two arbitrarily selected chains. This promotes effective mixing of the chains resulting in improved convergence.We illustrate the algorithm using a nine-spot waterflood model whereby we use water-cut and bottomhole flowing pressure data to calibrate the permeability field. The permeability field is re-parameterized using a previously proposed Grid Connectivity Transform (GCT) which is a model order reduction technique defined based only on the decomposition of the grid Laplacian. The compression power of GCT allows us to reconstruct the permeability field with few parameters, thus significantly improving the computational efficiency of the McMC approach. Next, we applied the method to the Brugge benchmark case involving 10 water injectors and 20 producers. For both cases, the algorithm provides an ensemble of models all constrained to the history data and defines a probabilistic Pareto front in the objective space. Several experimental runs were conducted to compare the effectiveness of the algorithm with Non-Dominated Sorting Genetic Algorithms (NSGA-II). Higher hypervolume was constantly measured using our algorithm which indicates that more optimal solutions were sampled. Our method provides a novel approach for subsurface model calibration and uncertainty quantification using McMC in which the communication between parallel Markov chains enhances adequate mixing. This significantly improves the convergence without loss in sampling quality.

A new technology for estimating time shifts in seismic monitoring of the exploitation of oil and gas fields and underground gas storage sites

The process of exploitation of oil and gas fields and underground natural gas and CO 2 storage facilities is accompanied by time-dependent changes in the physical properties of both the reservoir itself and the overburden. The study of these changes via time lapse (4D) seismic allows controlling the efficiency of operation of oil and gas fields and underground gas storage facilities. A wide class of methods uses, as intermediate information, time shifts arising in time lapse seismic data when studying the changes in the geomechanical properties of a reservoir. In this paper, conditions are formulated under which the values of the reflection coefficients of boundaries when changing the properties of a medium are preserved, but shifted to a new position along the two-way traveltime axis. To assess the time shifts that arise in this way, a new technology is developed. It is based on the statistical properties of the cross-correlation function of two time-limited random processes one of which is a shifted and stretched or compressed in time variant of the other. The proposed technology allows the constant and linear components of the time shifts to be determined simultaneously when the number of accumulated cross-correlation functions of such processes is sufficient. The validity of the theoretical foundations of the method is confirmed by two numerical experiments. As a source of input data required for the application of this technology in practice, it is suggested to use a random component of seismic images generated by chaotic fluctuations in the acoustic impedance in the lower half-space. Some methods for approximating the regular component of seismic records are described. Subtracting this component from the record allows its random component, which is necessary for the implementation of the proposed technology in practice, to be obtained.

A multimethod Global Sensitivity Analysis to aid the calibration of geomechanical models via time-lapse seismic data

Time-lapse seismic attributes are used extensively in the history matching of production simulator models. However, although proven to contain information regarding production induced stress change, it is typically only loosely (i.e. qualitatively) used to calibrate geomechanical models. In this study we conduct a multimethod Global Sensitivity Analysis (GSA) to assess the feasibility and aid the quantitative calibration of geomechanical models via near-offset time-lapse seismic data. Specifically, the calibration of mechanical properties of the overburden. Via the GSA, we analyse the near-offset overburden seismic traveltimes from over 4000 perturbations of a Finite Element (FE) geomechanical model of a typical High Pressure High Temperature (HPHT) reservoir in the North Sea. We find that, out of an initially large set of material properties, the near-offset overburden traveltimes are primarily affected by Young's modulus and the effective stress (i.e. Biot) coefficient. The unexpected significance of the Biot coefficient highlights the importance of modelling fluid flow and pore pressure outside of the reservoir. The FE model is complex and highly nonlinear. Multiple combinations of model parameters can yield equally possible model realizations. Consequently, numerical calibration via a large number of random model perturbations is unfeasible. However, the significant differences in traveltime results suggest that more sophisticated calibration methods could potentially be feasible for finding numerous suitable solutions. The results of the time-varying GSA demonstrate how acquiring multiple vintages of time-lapse seismic data can be advantageous. However, they also suggest that significant overburden near-offset seismic time-shifts, useful for model calibration, may take up to 3 yrs after the start of production to manifest. Due to the nonlinearity of the model behaviour, similar uncertainty in the reservoir mechanical properties appears to influence overburden traveltime to a much greater extent. Therefore, reservoir properties must be known to a suitable degree of accuracy before the calibration of the overburden can be considered.

Using simulation and production data to resolve ambiguity in interpreting 4D seismic inverted impedance in the Norne Field

The Norne Field started production in 1997 and up to 2006 the field experienced intense production activity, making the Norne benchmark case an ideal candidate to explore the challenges in interpreting complex time-lapse seismic data. Seismic amplitude changes and time-shifts are used as the first level approach to interpret the time-lapse differences and to update reservoir models. A common alternative is to invert the seismic data and obtain acoustic impedance variations caused by production activity, and to evaluate their possible interpretations. For this case study, we use a 4D inversion approach to invert the base (2001) and monitor (2006) seismic surveys in order to provide field-wide insights for the Norne benchmark case. We extensively interpret the observed 4D inversion anomalies and decouple, as much as possible, the effects of fluid and pressure variations, supported by production and reservoir engineering data. Moreover, we compare the inversion results with the simulation model from the Norne benchmark case to suggest areas of future modification to the simulation model. This research is intended as a resource to improve the quality of history matching or other 4D inversion methods applied to the Norne benchmark case, and to demonstrate a detailed time-lapse seismic interpretation within the reservoir segments of the Norne Field. Supplementary material: Well-history data of six producer and injector wells is available at https://doi.org/10.6084/m9.figshare.c.3890251

Time-lapse Seismic Analysis for Gao89 Area of CO2-EOR Project in SINOPEC Shengli Oilfield, China

Based on the time-lapse seismic data of CO2-EOR project in Gao89 area of Shengli Oilfield in China, this paper carries out the calibration of time-lapse seismic data and the analysis of amplitude differences before and during CO2 injection. From well-log based forward model, we applied Hertz-Mindlin formula and combined it with Gassmann's equation to predict the P-wave velocity, S-wave velocity and density logs at different effective pressure and CO2 fluid saturation. Then we made time-lapse synthetic seismogram to calibrate time lapse seismic data and analyzed amplitude differences from forward model. Our study shows that the effective pressure is the dominant factor for the changes of elastic parameters and seismic amplitudes at the early time of CO2 injection because the reservoir pressure was much lower than that of in-situ pressure. The deficit of reservoir pressure was caused by oil producing. In addition, CO2 saturation also affects the elastic parameters of reservoir and seismic amplitude. Finally, we calibrated the RMS amplitude of time-lapse seismic data at CO2 injection layers and caprocks in Gao89 CO2 injection area. The difference of time-lapse seismic amplitudes reflects low pressure zone of reservoir which is also the migration path and the distribution of CO2.

Stage 2C of the CO2CRC Otway Project: Seismic Monitoring Operations and Preliminary Results

The CO2CRC's “Otway Stage 2C project” is a test injection of 15,000 tons of supercritical gas mixture (80 mole% CO2 & 20 mole% CH4) at the CO2CRC Otway site in the Australian state of Victoria. The objective of this test is to examine the limits of surface seismic detection and to conduct detailed pressure monitoring of the injection. A key design feature of the project is injection near the bottom of a highly permeable formation, thereby allowing for buoyancy driven flow to thicken the plume and enhance seismic response. The project is specifically targeting observation of the development of the gas plume through a combination of multi-vintage 4D seismic surveys acquired with a buried seismic receiver array, 4D Vertical Seismic Profiling (VSP) and pressure measurements. Using both time-lapse seismic data and reservoir simulations, we aim to not only detect the plume but also demonstrate its eventual stabilisation. In this paper we discuss the technical aspects of the Otway Stage 2C seismic monitoring program and the initial results.

CO2 Plume Migration and Fate at Sleipner, Norway: Calibration of Numerical Models, Uncertainty Analysis, and Reactive Transport Modelling of CO2 Trapping to 10,000 Years

The Sleipner Project in Norway is the world's first industrial-scale geological carbon dioxide storage project. Time-lapse seismic monitoring data have been collected, tracing CO2 plume development from 1996 to 2010. Therefore, the Sleipner Project provides a somewhat unique opportunity to simulate the dynamics of CO2 in a real geological system. The purpose of this study is to simulate CO2 plume migration dynamics and assess the impact of uncertain factors on short and long term migration and fate of CO2 for the uppermost layer (Layer 9) of the Utsira Sand.First, we applied a multi-phase compositional simulator to the Sleipner Benchmark model for Layer 9 and calibrated our model against the time-lapsed seismic monitoring data at the site from 1999 to 2008. By adjusting lateral permeability anisotropy, CH4 in the CO2 stream, and reservoir temperature, approximate match with the observed plume was achieved. Model-predicted gas saturation, thickness of the CO2 accumulation, and CO2 solubility in brine (none of them used as calibration metrics) were all comparable with interpretations of the seismic data in the literature.Second, hundreds of simulations of parameter sensitivity (pressure, temperature, feeders, spill rates, relative permeability curves, and CH4 content) were conducted for the plume migration, based on the calibrated model. The results showed that simulated plume extents are sensitive to permeability anisotropy, temperature, and CH4 content, but not sensitive to the other parameters. However, adjusting a single parameter within the reported range of values in the literature would not reproduce the north-south trending CO2 plume; it took a combination of permeability, CH4, and temperature adjustments to match simulated CO2 plume with seismic monitoring data. Although there is a range of uncertain parameters, the predicted fate of CO2 fell within a narrow band, ∼ 93±2% structural trapping and ∼ 7±2% solubility trapping. The calibrated model is not unique. Many combinations of permeability anisotropy, temperature, and CH4 would produce similar matches. Other possibilities that would have improved the development of an N–S elongated CO2 plume, such as a slight tilting of the surface of Utsira top to the south, were not experimented in this study, but are worthy of exploration for future studies.Finally, we used coupled reactive mass transport model to investigate the effects of rate laws and regional groundwater flow on long-term CO2 fate in Layer 9. The mineral composition and brine chemistry for the Utsira sand were adopted from the literature, and we modelled 100 year injection and continued water-rock interaction to 10,000 years. The results indicated that: (1) The predicted fraction of CO2 mineral trapping when using the linear rate law for feldspar dissolution is twice as much as when using the non-linear rate law. (2) Mineral trapping is more significant when regional groundwater flow is taken into consideration. Under the influence of regional groundwater flow, the replenishment of fresh brine from upstream continuously dissolves CO2 at the tail of CO2 plume, generating a larger acidified area where mineral trapping takes place. In a Sleipner like aquifer, the upstream replenishment of groundwater results in ∼ 22% mineral trapping at year 10,000, compared to the ∼ 4% when the effects of regional groundwater are ignored.

CO2 Storage: Setting a Simple Bound on Potential Leakage through the Overburden in the North Sea Basin

So-called ‘gas chimneys’ are likely to provide the main geological risk for out-of-reservoir CO2 migration in thick post-rift overburden successions such as typify the central and northern North Sea. Here we postulate that, in the North Sea, such chimneys formed in the geological past, with a likely peak activity at the end of the ice-age, and are currently rather dormant. With this postulate we set a bound on possible bulk migration rates considering both advective and diffusive flow and based on a hypothetical CO2 storage site at 800 m depth. Calculated migration velocities into the overburden, by either advection or diffusion, are very low, at less than one metre per thousand years. Consequently flux rates are also very low, several orders of magnitude below the leakage thresholds that have been suggested as ensuring effective mitigation performance. Time-lapse seismic reflection data from the Sleipner storage site, which is located beneath some small chimney features, show no evidence of CO2 migration into the overburden. This cannot prove the postulate, because the time interval spanned by the seismic surveys is just a few years, but it is nevertheless consistent with it.