Estimation of pore‐pressure change in a compacting reservoir from time‐lapse seismic data

An approach is developed to estimate pore‐pressure changes in a compacting chalk reservoir directly from time‐lapse seismic attributes. It is applied to data from the south‐east flank of the Valhall field. The time‐lapse seismic signal of the reservoir in this area is complex, despite the fact that saturation changes do not have an influence. This complexity reflects a combination of pressure depletion, compaction and stress re‐distribution throughout the reservoir and into the surrounding rocks. A simple relation is found to link the time‐lapse amplitude and time‐shift attributes to variations in the key controlling parameter of initial porosity. This relation is sufficient for an accurate estimation of pore‐pressure change in the inter‐well space. Although the time‐lapse seismic estimates mostly agree with reservoir simulation, unexplained mismatches are apparent at a small number of locations with lower porosities (less than 38%). The areas of difference between the observations and predictions suggest possibilities for simulation model updating or a better understanding of the physics of the reservoir.     

Analysis of time‐lapse travel‐time and amplitude changes to assess reservoir compartmentalization

Fluid depletion within a compacting reservoir can lead to significant stress and strain changes and potentially severe geomechanical issues, both inside and outside the reservoir. We extend previous research of time‐lapse seismic interpretation by incorporating synthetic near‐offset and full‐offset common‐midpoint reflection data using anisotropic ray tracing to investigate uncertainties in time‐lapse seismic observations. The time‐lapse seismic simulations use dynamic elasticity models built from hydro‐geomechanical simulation output and a stress‐dependent rock physics model. The reservoir model is a conceptual two‐fault graben reservoir, where we allow the fault fluid‐flow transmissibility to vary from high to low to simulate non‐compartmentalized and compartmentalized reservoirs, respectively. The results indicate time‐lapse seismic amplitude changes and travel‐time shifts can be used to qualitatively identify reservoir compartmentalization. Due to the high repeatability and good quality of the time‐lapse synthetic dataset, the estimated travel‐time shifts and amplitude changes for near‐offset data match the true model subsurface changes with minimal errors. A 1D velocity–strain relation was used to estimate the vertical velocity change for the reservoir bottom interface by applying zero‐offset time shifts from both the near‐offset and full‐offset measurements. For near‐offset data, the estimated P‐wave velocity changes were within 10% of the true value. However, for full‐offset data, time‐lapse attributes are quantitatively reliable using standard time‐lapse seismic methods when an updated velocity model is used rather than the baseline model.     

Bayesian inversion of time‐lapse seismic data for the estimation of static reservoir properties and dynamic property changes

Seismic conditioning of static reservoir model properties such as porosity and lithology has traditionally been faced as a solution of an inverse problem. Dynamic reservoir model properties have been constrained by time‐lapse seismic data. Here, we propose a methodology to jointly estimate rock properties (such as porosity) and dynamic property changes (such as pressure and saturation changes) from time‐lapse seismic data. The methodology is based on a full Bayesian approach to seismic inversion and can be divided into two steps. First we estimate the conditional probability of elastic properties and their relative changes; then we estimate the posterior probability of rock properties and dynamic property changes. We apply the proposed methodology to a synthetic reservoir study where we have created a synthetic seismic survey for a real dynamic reservoir model including pre‐production and production scenarios. The final result is a set of point‐wise probability distributions that allow us to predict the most probable reservoir models at each time step and to evaluate the associated uncertainty. Finally we also show an application to real field data from the Norwegian Sea, where we estimate changes in gas saturation and pressure from time‐lapse seismic amplitude differences. The inverted results show the hydrocarbon displacement at the times of two repeated seismic surveys.     

Seismic driven probabilistic classification of reservoir facies for static reservoir modelling: a case history in the Barents Sea

In this paper we present a case history of seismic reservoir characterization where we estimate the probability of facies from seismic data and simulate a set of reservoir models honouring seismically‐derived probabilistic information. In appraisal and development phases, seismic data have a key role in reservoir characterization and static reservoir modelling, as in most of the cases seismic data are the only information available far away from the wells. However seismic data do not provide any direct measurements of reservoir properties, which have then to be estimated as a solution of a joint inverse problem. For this reason, we show the application of a complete workflow for static reservoir modelling where seismic data are integrated to derive probability volumes of facies and reservoir properties to condition reservoir geostatistical simulations. The studied case is a clastic reservoir in the Barents Sea, where a complete data set of well logs from five wells and a set of partial‐stacked seismic data are available. The multi‐property workflow is based on seismic inversion, petrophysics and rock physics modelling. In particular, log‐facies are defined on the basis of sedimentological information, petrophysical properties and also their elastic response. The link between petrophysical and elastic attributes is preserved by introducing a rock‐physics model in the inversion methodology. Finally, the uncertainty in the reservoir model is represented by multiple geostatistical realizations. The main result of this workflow is a set of facies realizations and associated rock properties that honour, within a fixed tolerance, seismic and well log data and assess the uncertainty associated with reservoir modelling.     

Improved normalization of time‐lapse seismic data using normalized root mean square repeatability data to improve automatic production and seismic history matching in the Nelson field

Updating of reservoir models by history matching of 4D seismic data along with production data gives us a better understanding of changes to the reservoir, reduces risk in forecasting and leads to better management decisions. This process of seismic history matching requires an accurate representation of predicted and observed data so that they can be compared quantitatively when using automated inversion. Observed seismic data is often obtained as a relative measure of the reservoir state or its change, however. The data, usually attribute maps, need to be calibrated to be compared to predictions. In this paper we describe an alternative approach where we normalize the data by scaling to the model data in regions where predictions are good. To remove measurements of high uncertainty and make normalization more effective, we use a measure of repeatability of the monitor surveys to filter the observed time‐lapse data. We apply this approach to the Nelson field. We normalize the 4D signature based on deriving a least squares regression equation between the observed and synthetic data which consist of attributes representing measured acoustic impedances and predictions from the model. Two regression equations are derived as part of the analysis. For one, the whole 4D signature map of the reservoir is used while in the second, 4D seismic data is used from the vicinity of wells with a good production match. The repeatability of time‐lapse seismic data is assessed using the normalized root mean square of measurements outside of the reservoir. Where normalized root mean square is high, observations and predictions are ignored. Net: gross and permeability are modified to improve the match. The best results are obtained by using the normalized root mean square filtered maps of the 4D signature which better constrain normalization. The misfit of the first six years of history data is reduced by 55 per cent while the forecast of the following three years is reduced by 29 per cent. The well based normalization uses fewer data when repeatability is used as a filter and the result is poorer. The value of seismic data is demonstrated from production matching only where the history and forecast misfit reductions are 45% and 20% respectively while the seismic misfit increases by 5%. In the best case using seismic data, it dropped by 6%. We conclude that normalization with repeatability based filtering is a useful approach in the absence of full calibration and improves the reliability of seismic data.     

Cross-matching with interpreted warping of 3D streamer and 3D ocean-bottom-cable data at Valhall for time-lapse assessment

Legacy streamer data and newer 3D ocean‐bottom‐cable data are cross‐matched and analysed for time‐lapse analysis of geomechanical changes due to production in the Valhall Field. The issues relating to time‐lapse analysis using two such distinctly different data sets are addressed to provide an optimal cross‐matching workflow that includes 3D warping. Additionally an assessment of the differences between the imaging using single‐azimuth streamer and multi‐azimuth ocean‐bottom‐cable data is provided. The 3D warping utilized in the cross‐matching procedure is sensitive to acquisition and processing differences but is also found to provide valuable insight into the geometrical changes that occur in the subsurface due to production. As such, this work also provides a demonstration of the use of high‐resolution 3D interpreted warping to resolve the 3D heterogeneity of the compaction and subsidence. This is an important tool for Valhall, and possibly other fields, where compaction and subsidence (and monitoring thereof) are key factors in the reservoir management since the predominant observed production‐induced changes are compaction of the soft, high‐porosity chalk reservoir, due to pore‐pressure reduction, and the resultant overburden subsidence. Such reservoir compaction could have significant implications for production by changing permeabilities and production rates. Furthermore the subsidence effects could impact upon subsea installations and well‐bore stability. Geomechanical studies that have previously been used to model such subsidence and compaction are only constrained by observed surface displacements and measured reservoir pressure changes, with the geological overburden being largely neglected. The approaches suggested herein provide the potential for monitoring and assessment in three dimensions, including the probable heterogeneity and shearing, that is needed for full understanding of reservoir compaction and the resultant effects on the overburden to, for example, mitigate well‐bore failures.     

Stochastic inversion of pressure and saturation changes from time-lapse multi component data

Knowledge about saturation and pressure distributions in a reservoir can help in determining an optimal drainage pattern, and in deciding on optimal well designs to reduce risks of blow‐outs and damage to production equipment. By analyzing time‐lapse PP AVO or time‐lapse multicomponent seismic data, it is possible to separate the effects of production related saturation and pressure changes on seismic data. To be able to utilize information about saturation and pressure distributions in reservoir model building and simulation, information about uncertainty in the estimates is useful. In this paper we present a method to estimate changes in saturation and pressure from time‐lapse multicomponent seismic data using a Bayesian estimation technique. Results of the estimations will be probability density functions (pdfs), giving immediate information about both parameter values and uncertainties. Linearized rock physical models are linked to the changes in saturation and pressure in the prior probability distribution. The relationship between the elastic parameters and the measured seismic data is described in the likelihood model. By assuming Gaussian distributed prior uncertainties the posterior distribution of the saturation and pressure changes can be calculated analytically. Results from tests on synthetic seismic data show that this method produces more precise estimates of changes in effective pressure than a similar methodology based on only PP AVO time‐lapse seismic data. This indicates that additional information about S‐waves obtained from converted‐wave seismic data is useful for obtaining reliable information about the pressure change distribution.     

Quantitative detection of fluid distribution using time-lapse seismic

Although previous seismic monitoring studies have revealed several relationships between seismic responses and changes in reservoir rock properties, the quantitative evaluation of time‐lapse seismic data remains a challenge. In most cases of time‐lapse seismic analysis, fluid and/or pressure changes are detected qualitatively by changes in amplitude strength, traveltime and/or Poisson's ratio. We present the steps for time‐lapse seismic analysis, considering the pressure effect and the saturation scale of fluids. We then demonstrate a deterministic workflow for computing the fluid saturation in a reservoir in order to evaluate time‐lapse seismic data. In this approach, we derive the physical properties of the water‐saturated sandstone reservoir, based on the following inputs: V_P, V_S, ρ and the shale volume from seismic analysis, the average properties of sand grains, and formation‐water properties. Next, by comparing the in‐situ fluid‐saturated properties with the 100% formation‐water‐saturated reservoir properties, we determine the bulk modulus and density of the in‐situ fluid. Solving three simultaneous equations (relating the saturations of water, oil and gas in terms of the bulk modulus, density and the total saturation), we compute the saturation of each fluid. We use a real time‐lapse seismic data set from an oilfield in the North Sea for a case study.     

Quantitative estimation of water storage and residence time in the epikarst with time‐lapse refraction seismic

The hydrodynamic characterization of the epikarst, the shallow part of the unsaturated zone in karstic systems, has always been challenging for geophysical methods. This work investigates the feasibility of coupling time‐lapse refraction seismic data with petrophysical and hydrologic models for the quantitative determination of water storage and residence time at shallow depth in carbonate rocks. The Biot–Gassmann fluid substitution model describing the seismic velocity variations with water saturation at low frequencies needs to be modified for this lithology. I propose to include a saturation‐dependent rock‐frame weakening to take into account water–rock interactions. A Bayesian inversion workflow is presented to estimate the water content from seismic velocities measured at variable saturations. The procedure is tested first with already published laboratory measurements on core samples, and the results show that it is possible to estimate the water content and its uncertainty. The validated procedure is then applied to a time‐lapse seismic study to locate and quantify seasonal water storage at shallow depth along a seismic profile. The residence time of the water in the shallow layers is estimated by coupling the time‐lapse seismic measurements with rainfall chronicles, simple flow equations, and the petrophysical model. The daily water input computed from the chronicles is used to constraint the inversion of seismic velocities for the daily saturation state and the hydrodynamic parameters of the flow model. The workflow is applied to a real monitoring case, and the results show that the average residence time of the water in the epikarst is generally around three months, but it is only 18 days near an infiltration pathway. During the winter season, the residence times are three times shorter in response to the increase in the effective rainfall.     

Scale effects on modelling the seismic signature of gas: results from an outcrop analogue

Numerous examples of reservoir fields from continental and marine environments involve thin‐bedded geology, yet, the inter‐relationship between thin‐bedded geology, fluid flow and seismic wave propagation is poorly understood. In this paper, we explore the 4D seismic signature due to saturation changes of gas within thin layers, and address the challenge of identifying the relevant scales and properties, which correctly define the geology, fluid flow and seismic wave propagation in the field. Based on the study of an outcrop analogue for a thin‐bedded turbidite, we model the time‐lapse seismic response to fluid saturation changes for different levels of model scale, and explore discrepancies in quantitative seismic attributes caused by upscaling. Our model reflects the geological complexity associated with thin‐bedded turbidites, and its coupling to fluid flow, which in turn affects the gas saturation distribution in space, and its time‐lapse seismic imprint. Rock matrix and fluid properties are modelled after selected fields to reproduce representative field models with realistic impedance contrasts. In addition, seismic modelling includes multiples, in order to assess their contribution in seismic propagation through thin gas layers. Our results show that multiples could contribute significantly to the measured amplitudes in the case of thin‐bedded geology. This suggests that forward/inverse modelling involving the flow simulation and seismic domains used in time‐lapse seismic interpretation should account for thin layers, when these are present in the geological setting.     

Direct correlation of 4D seismic with well activity for a clarified dynamic reservoir interpretation

A method to provide an improved time‐lapse seismic attribute for dynamic interpretation is presented. This is based on the causal link between the time‐lapse seismic response and well production activity taken over time. The resultant image is obtained by computing correlation coefficients between sequences of time‐lapse seismic changes extracted over different time intervals from multiply repeated seismic and identical time sequences of cumulative fluid volumes produced or injected from the wells. Maps of these cross‐correlations show localized, spatially contiguous signals surrounding individual wells or a specific well group. These may be associated with connected regions around the selected well or well group. Application firstly to a synthetic data set reveals that hydraulic compartments may be delineated using this method. A second application to a field data set provides empirical evidence that a connected well‐centric fault block and active geobody can be detected. It is concluded that uniting well data and time‐lapse seismic using our proposed method delivers a new attribute for dynamic interpretation and potential updating of the model for the producing reservoir.     

Error in shear-wave polarization and time splitting

Shear‐wave polarization and time delay are attributes commonly used for fracture detection and characterization. In time‐lapse analysis these parameters can be used as indicators of changes in the fracture orientation and density. Indeed, changes in fracture characteristics provide key information for increased reservoir characterization and exploitation. However, relative to the data uncertainty, is the comparison of these parameters over time statistically meaningful? We present the uncertainty in shear‐wave polarization and time delay as a function of acquisition uncertainties, such as receiver and source misorientation, miscoupling and band‐limited random noise. This study is applied to a time‐lapse borehole seismic survey, recorded in Vacuum Field, New Mexico. From the estimated uncertainties for each survey, the uncertainty in the difference between the two surveys is 31° for the shear‐wave polarization angle and 4 ms for the shear‐wave time delay. Any changes in these parameters greater than these error estimates can be interpreted with confidence. This analysis can be applied to any time‐lapse measurement to provide an interval of confidence in the interpretation of shear‐wave polarization angles and time splitting.     

Post‐stack stratigraphic inversion workflow applied to carbon dioxide storage: application to the saline aquifer of Sleipner field‡

In the Norwegian North Sea, the Sleipner field produces gas with a high CO₂ content. For environmental reasons, since 1996, more than 11 Mt of this carbon dioxide (CO₂) have been injected in the Utsira Sand saline aquifer located above the hydrocarbon reservoir. A series of seven 3D seismic surveys were recorded to monitor the CO₂ plume evolution. With this case study, time‐lapse seismics have been shown to be successful in mapping the spread of CO₂ over the past decade and to ensure the integrity of the overburden. Stratigraphic inversion of seismic data is currently used in the petroleum industry for quantitative reservoir characterization and enhanced oil recovery. Now it may also be used to evaluate the expansion of a CO₂ plume in an underground reservoir. The aim of this study is to estimate the P‐wave impedances via a Bayesian model‐based stratigraphic inversion. We have focused our study on the 1994 vintage before CO₂ injection and the 2006 vintage carried out after a CO₂ injection of 8.4 Mt. In spite of some difficulties due to the lack of time‐lapse well log data on the interest area, the full application of our inversion workflow allowed us to obtain, for the first time to our knowledge, 3D impedance cubes including the Utsira Sand. These results can be used to better characterize the spreading of CO₂ in a reservoir. With the post‐stack inversion workflow applied to CO₂ storage, we point out the importance of the a priori model and the issue to obtain coherent results between sequential inversions of different seismic vintages. The stacking velocity workflow that yields the migration model and the a priori model, specific to each vintage, can induce a slight inconsistency in the results.     

Time‐lapse seismic modelling of CO2 fluid substitution in the Devonian Redwater Reef,Alberta, Canada

Common shot ray tracing and finite difference seismic modelling experiments were undertaken to evaluate variations in the seismic response of the Devonian Redwater reef in the Alberta Basin, Canada after replacement of native pore waters in the upper rim of the reef with CO₂. This part of the reef is being evaluated for a CO₂ storage project. The input geological model was based on well data and the interpretation of depth‐converted, reprocessed 2D seismic data in the area. Pre‐stack depth migration of the ray traced and finite difference synthetic data demonstrate similar seismic attributes for the Mannville, Nisku, Ireton, Cooking Lake, and Beaverhill Lake formations and clear terminations of the Upper Leduc and Middle Leduc events at the reef margin. Higher amplitudes at the base of Upper‐Leduc member are evident near the reef margin due to the higher porosity of the foreslope facies in the reef rim compared to the tidal flat lagoonal facies within the central region of the reef. Time‐lapse seismic analysis exhibits an amplitude difference of about 14% for Leduc reflections before and after CO₂ saturation and a travel‐time delay through the reservoir of 1.6 ms. Both the ray tracing and finite difference approaches yielded similar results but, for this particular model, the latter provided more precise imaging of the reef margin. From the numerical study we conclude that time‐lapse surface seismic surveys should be effective in monitoring the location of the CO₂ plume in the Upper Leduc Formation of the Redwater reef, although the differences in the results between the two modelling approaches are of similar order to the effects of the CO₂ fluid replacement itself.     

Application of diffracted wave analysis to time‐lapse seismic data for CO2 leakage detection

Time‐lapse seismic analysis is utilized in CO₂ geosequestration to verify the CO₂ containment within a reservoir. A major risk associated with geosequestration is a possible leakage of CO₂ from the storage formation into overlaying formations. To mitigate this risk, the deployment of carbon capture and storage projects requires fast and reliable detection of relatively small volumes of CO₂ outside the storage formation. To do this, it is necessary to predict typical seepage scenarios and improve subsurface seepage detection methods. In this work we present a technique for CO₂ monitoring based on the detection of diffracted waves in time‐lapse seismic data. In the case of CO₂ seepage, the migrating plume might form small secondary accumulations that would produce diffracted, rather than reflected waves. From time‐lapse data analysis, we are able to separate the diffracted waves from the predominant reflections in order to image the small CO₂ plumes. To explore possibilities to detect relatively small amounts of CO₂, we performed synthetic time‐lapse seismic modelling based on the Cooperative Research Centre for Greenhouse Gas Technologies (CO2CRC) Otway project data. The detection method is based on defining the CO₂ location by measuring the coherency of the signal along diffraction offset‐traveltime curves. The technique is applied to a time‐lapse stacked section using a stacking velocity to construct offset‐traveltime curves. Given the amount of noise found in the surface seismic data, the predicted minimum detectable amount of CO₂ is 1000–2000 tonnes. This method was also applied to real data obtained from a time‐lapse seismic physical model. The use of diffractions rather than reflections for monitoring small amounts of CO₂ can enhance the capability of subsurface monitoring in CO₂ geosequestration projects.     

有效压力与饱和度变化的气藏多波时移地震AVO响应

天然气在开发过程中,储层有效压力和含气饱和度均会发生变化,研究有效压力和含气饱和度的变化对地震响应特征的影响,在基于时移地震的剩余气分布预测研究中具有重要意义。天然气和石油的声学性质有着明显的差异,油藏时移地震的研究成果不能直接应用于气藏,因此需要开展气藏的时移地震研究。利用Shapiro模型表征干岩石弹性模量随有效压力的变化,借助Batzle-Wang方程描述流体速度随压力的变化关系,联合Gassmann理论进行流体替代,表征饱和流体岩石速度随含气饱和度的变化,建立了饱和流体岩石速度随有效压力和饱和度变化的岩石物理模型。基于该模型,对不同含气饱和度和不同有效压力下的气藏储层模型进行了多波时移地震叠前振幅变化（AVO）模拟。结果表明多波时移地震AVO技术可以有效地区分有效压力变化和含气饱和度变化,为进一步开展气藏多波时移地震流体监测提供了理论参考依据。      

Exploring seismic inversion methodologies for non‐stationary geological environments: a benchmark study between deterministic and geostatistical seismic inversion

This paper presents a comparison between subsurface impedance models derived from different deterministic and geostatistical seismic inversion methodologies applied to a challenging synthetic dataset. Geostatistical seismic inversion methodologies nowadays are common place in both industry and academia, contrasting with traditional deterministic seismic inversion methodologies that are becoming less used as part of the geo‐modelling workflow. While the first set of techniques allows the simultaneous inference of the best‐fit inverse model along with the spatial uncertainty of the subsurface elastic property of interest, the second family of inverse methodology has proven results in correctly predicting the subsurface elastic properties of interest with comparatively less computational cost. We present herein the results of a benchmark study performed over a realistic three‐dimensional non‐stationary synthetic dataset in order to assess the performance and convergence of different deterministic and geostatistical seismic inverse methodologies. We also compare and discuss the impact of the inversion parameterisation over the exploration of the model parameter space. The results show that the chosen seismic inversion methodology should always be dependent on the type and quantity of the available data, both seismic and well‐log, and the complexity of the geological environment versus the assumptions behind each inversion technique. The assessment of the model parameter space shows that the initial guess of traditional deterministic seismic inversion methodologies is of high importance since it will determine the location of the best‐fit inverse solution.     

Repeatability enhancement in deep-water permanent seismic installations: a dynamic correction for seawater velocity variations

With the increasing use of permanently installed seismic installations, many of the issues in time‐lapse seismic caused by the lack of repeatability can be reduced. However, a number of parameters still influence the degree of reliability of 4D seismic data. In this paper, the specific impact of seawater velocity variations on time‐lapse repeatability is investigated in a synthetic study. A zero‐lag time‐lapse seabed experiment with no change in the subsurface but with velocity changes in the water column is simulated. The velocity model in the water column is constant for the baseline survey while the model for the repeat survey is heterogeneous, designed from sea salinity and temperature measurements in the West of Shetlands. The difference section shows up to 80% of residual amplitude, which highlights the poor repeatability. A new dynamic correction which removes the effect of seawater velocity variations specifically for permanent installations is developed. When applied to the synthetic data, it reduces the difference residual amplitude to about 3%. This technique shows substantial improvement in repeatability beyond conventional time‐lapse cross‐equalization.     

Extraction of permeability from time-lapse seismic data

Two formulae are developed for estimating horizontal permeability directly from maps of 4D seismic signatures. The choice of the formula used depends on whether the seismic is dominated by changes of pressure or saturation. However, pressure derived from time‐lapse seismic, or seismic amplitudes controlled predominantly by pressure are to be preferred for optimal ‘illumination’ of the reservoir. The permeability is predicted to be dependent on porosity but weighted by a 4D term related to the magnitude and spatial gradient of the 4D signature. Tests performed on model‐based synthetic seismic data affirm the validity and accuracy of this approach. Application to field data from the UK continental shelf reveals a large‐scale permeability variation similar to the existing simulation model, but with additional fine‐scale detail. The technique thus has the potential of providing extra information with which to update the simulation model. The resultant permeability estimates have been successfully ground‐truthed against the results of two well tests. As non‐repeatable noise in the time‐lapse seismic data diminishes with improved 4D‐related acquisition, it will become increasingly possible to make robust permeability estimates using this approach.     

When 4D seismic is not applicable: Alternative monitoring scenarios for the Arab-D reservoir in the Ghawar Field

Ghawar, the largest oilfield in the world, produces oil from the Upper Jurassic Arab‐D carbonate reservoir. The high rigidity of the limestone–dolomite reservoir rock matrix and the small contrast between the elastic properties of the pore fluids, i.e. oil and water, are responsible for the weak 4D seismic effect due to oil production. A feasibility study was recently completed to quantify the 4D seismic response of reservoir saturation changes as brine replaced oil. The study consisted of analysing reservoir rock physics, petro‐acoustic data and seismic modelling. A seismic model of flow simulation using fluid substitution concluded that time‐lapse surface seismic or conventional 4D seismic is unlikely to detect the floodfront within the repeatability of surface seismic measurements. Thus, an alternative approach to 4D seismic for reservoir fluid monitoring is proposed. Permanent seismic sensors could be installed in a borehole and on the surface for passive monitoring of microseismic activity from reservoir pore‐pressure perturbations. Reservoir production and injection operations create these pressure or stress perturbations. Reservoir heterogeneities affecting the fluid flow could be mapped by recording the distribution of epicentre locations of these microseisms or small earthquakes. The permanent borehole sensors could also record repeated offset vertical seismic profiling surveys using a surface source at a fixed location to ensure repeatability. The repeated vertical seismic profiling could image the change in reservoir properties with production.