Time-lapse seismic analysis of pressure depletion in the Southern Gas Basin

In the Southern Gas Basin (SGB) of the North Sea there are many mature gas fields where time‐lapse monitoring could be very beneficial in extending production life. However, the conditions are not immediately attractive for time‐lapse seismic assessment. This is primarily because the main production effect to be assessed is a pore pressure reduction and frame stiffening because of gas production in tight sandstone reservoirs that also have no real seismic direct hydrocarbon indicators. Modelling, based on laboratory measurements, has shown that such an effect would be small and difficult to detect in seismic data. This paper makes two main contributions. Firstly, this is, to our knowledge, the first time‐lapse study in the SGB and involves a real‐data assessment of the viability for detecting production in such an environment. Secondly, the feasibility of using markedly different legacies of data in such a study is addressed, including an assessment of the factors influencing the crossmatching. From the latter, it is found that significant, spatially varying time shifts need to be, and are successfully, resolved through 3‐D warping. After the warping, the primary factors limiting the crossmatching appear to be residual local phase variations, possibly induced by the differing migration strategies, structure, reverberations and different coherencies of the volumes, caused by differences in acquisition‐structure azimuth and acquisition fold. Despite these differences, a time‐lapse amplitude signature is observed that is attributable to production. The character of the 4‐D amplitude anomalies may also indicate variations in stress sensitivity, e.g. because of zones of fracturing. Additionally, warping‐derived time attributes have been highlighted as a potential additional avenue for detection of pressure depletion in such reservoirs. Although the effects are subtle, they may indicate changes in stress/pressure in and around the reservoir because of production. However, to fully resolve the subtle time‐lapse effects in such a reservoir, the data differences need to be better addressed, which may be possible by full re‐processing and pre‐stack analysis, but more likely dedicated 4‐D acquisition would be required.     

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.     

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.     

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.     

Influence of pore pressure on velocity in low-porosity sandstone: Implications for time-lapse feasibility and pore-pressure study

As seismic data quality improves, time‐lapse seismic data is increasingly being called upon to interpret and predict changes during reservoir development and production. Since pressure change is a major component of reservoir change during production, a thorough understanding of the influence of pore pressure on seismic velocity is critical. Laboratory measurements show that differential pressure (overburden minus fluid pressure) does not adequately determine the actual reservoir conditions. Changes in fluid pressure are found to have an additional effect on the physical properties of rocks. The effective‐stress coefficient n is used to quantify the effect of pore pressure compared to confining pressure on rock properties. However, the current practice in time‐lapse feasibility studies, reservoir‐pressure inversion and pore‐pressure prediction is to assume that n= 1. Laboratory measurements, reported in both this and previous research show that n can be significantly less than unity for low‐porosity rocks and that it varies with porosity, rock texture and wave type. We report the results of ultrasonic experiments to estimate n for low‐porosity sandstones with and without microcracks. Our results show that, for P‐waves, n is as low as 0.4 at a differential pressure of 20 MPa (about 3000 psi) for a low‐porosity sandstone. Thus, in pore‐pressure inversion, an assumption of n= 1 would lead to a 150% underestimation of the pore pressure. Comparison of the effective‐stress coefficient for fractured and unfractured samples suggests that the presence of microfractures increases the sensitivity of P‐wave velocity to pore pressure, and therefore the effective‐stress coefficient. Our results show that the effective‐stress coefficient decreases with the differential pressure, with a higher differential pressure resulting in a lower effective‐stress coefficient. While the effective‐stress coefficient for P‐wave velocity can be significantly less than unity, it is close to one for S‐waves.     

Asymmetry in the time-lapse seismic response to injection and depletion

Large changes in seismic reflection amplitude have been observed around injectors, and result from the decrease in elastic‐wave velocity due to the increase in pore pressure in the reservoir. In contrast, the velocity change resulting from the decrease in pore pressure in depleting reservoirs is observed to be smaller in magnitude. Elastic‐wave velocities in sandstones vary with stress due to the presence of stress‐sensitive grain boundaries within the rock. Grain‐boundary stiffness increases non‐linearly with increasing compressive stress, due to increased contact between opposing faces of the boundary. This results in a change in velocity due to a decrease in pore pressure that is smaller than the change in velocity caused by an increase in pore pressure, in agreement with time‐lapse seismic observations. The decrease in porosity resulting from depletion is not fully recovered upon re‐pressurization, and this leads to an additional steepening of the velocity vs. effective stress curve for injection relative to depletion. This difference is enhanced by any breakage of cement or weakening of grain contacts that may occur during depletion and by the reopening or formation of fractures or joints and dilation of grain boundaries that may occur during injection.     

Sensitivity of time-lapse seismic to reservoir stress path

The change in reservoir pore pressure due to the production of hydrocarbons leads to anisotropic changes in the stress field acting on the reservoir. Reservoir stress path is defined as the ratio of the change in effective horizontal stress to the change in effective vertical stress from the initial reservoir conditions, and strongly influences the depletion‐induced compaction behaviour of the reservoir. Seismic velocities in sandstones vary with stress due to the presence of stress‐sensitive regions within the rock, such as grain boundaries, microcracks, fractures, etc. Since the response of any microcracks and grain boundaries to a change in stress depends on their orientation relative to the principal stress axes, elastic‐wave velocities are sensitive to reservoir stress path. The vertical P‐ and S‐wave velocities, the small‐offset P‐ and SV‐wave normal‐moveout (NMO) velocities, and the P‐wave amplitude‐versus‐offset (AVO) are sensitive to different combinations of vertical and horizontal stress. The relationships between these quantities and the change in stress can be calibrated using a repeat seismic, sonic log, checkshot or vertical seismic profile (VSP) at the location of a well at which the change in reservoir pressure has been measured. Alternatively, the variation of velocity with azimuth and distance from the borehole, obtained by dipole radial profiling, can be used. Having calibrated these relationships, the theory allows the reservoir stress path to be monitored using time‐lapse seismic by combining changes in the vertical P‐wave impedance, changes in the P‐wave NMO and AVO behaviour, and changes in the S‐wave impedance.     

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.     

The 4D seismic signature of oil–water contact movement due to natural production in a stacked turbidite reservoir

Combined time‐lapse reservoir simulation and seismic modelling has been performed on both 1D and 3D models of a channelized turbidite reservoir. The models have been built using core, log, laboratory and seismic data from the Nelson Field (central North Sea) as a template. Oil and water movement in the main channels, channel margins and interchannel regions is investigated, with a particular focus being the effect of poor net‐to‐gross. The analysis confirms that saturation effects dominate the response whilst stress‐sensitivity effects play a minor role. The trough–peak signature in the seismic difference volumes formed by the sweep of the water can be continued and mapped slightly further than the channel margins. This characteristic 4D signature remains roughly intact, despite the complicated depositional architecture, and accurately delineates the area of moved fluid, but it needs additional calibration to combat the detrimental influence of the low net‐to‐gross. Signal strength is largely dependent on reservoir quality, but is also compromised by the net‐to‐gross, fluid distribution and, more critically, by the exact timing of the seismic survey. For example, a region of bypassed oil zone remains undetected as it forms early during the production. This work demonstrates that to understand fully the 4D signature at a quantitative level requires adequate knowledge of the fluid properties, but also, more critically, the geology.     

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.     

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.     

Observation of azimuthal anisotropy from the seismic reflectivity of a Tertiary turbidite sand

P‐wave data from a time‐lapse 3D OBC survey have been analysed to estimate and interpret azimuthal seismic anisotropy. This is achieved by careful processing to preserve the azimuthal signature. The survey images a major reservoir body in a channelized turbidite field in the Gulf of Mexico. Three distinct and significant anisotropy anomalies are discovered on or around this particular ‘4500‐ft sand’, all of which change intensity but not orientation with hydrocarbon production. These anomalies are distributed along the highest concentration of cumulative sand thickness, with their symmetry axes aligned with the main channel axis. We suspect that this time‐lapse anisotropy could be caused by the alignment of the depositional grain fabric. Theoretical calculation predicts that this mechanism, when combined with fluid‐saturation changes, can generate the observed pattern of behaviour. If further supported by other researchers, this result would indicate that appropriately designed seismic surveys could be a useful tool for palaeo‐direction studies in clastic reservoirs and also a useful constraint for directional permeability in the reservoir flow simulation 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.     

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.     

Repeatability analysis of land time‐lapse seismic data: CO2CRC Otway pilot project case study

Time‐lapse seismics is the methodology of choice for remotely monitoring changes in oil/gas reservoir depletion, reservoir stimulation or CO₂ sequestration, due to good sensitivity and resolving power at depths up to several kilometres. This method is now routinely applied offshore, however, the use of time‐lapse methodology onshore is relatively rare. The main reason for this is the relatively high cost of commercial seismic acquisition on land. A widespread belief of a relatively poor repeatability of land seismic data prevents rapid growth in the number of land time‐lapse surveys. Considering that CO₂ sequestration on land is becoming a necessity, there is a great need to evaluate the feasibility of time‐lapse seismics for monitoring. Therefore, an understanding of the factors influencing repeatability of land seismics and evaluating limitations of the method is crucially important for its application in many CO₂ sequestration projects. We analyse several repeated 2D and 3D surveys acquired within the Otway CO₂ sequestration pilot project (operated by the Cooperative Research Centre for Greenhouse Technologies, CO2CRC) in Australia, in order to determine the principal limitations of land time‐lapse seismic repeatability and investigate the influence of the main factors affecting it. Our findings are that the intrinsic signal‐to‐noise ratio (S/N, signal to coherent and background noise levels) and the normalized‐root‐mean‐square (NRMS) difference are controlled by the source strength and source type. However, the post‐stack S/N ratio and corresponding NRMS residuals are controlled mainly by the data fold. For very high‐fold data, the source strength and source type are less critical.     

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.     

Quasi‐continuous reservoir monitoring with surface seismic data

We present an approach that creates the possibility of reservoir monitoring on a quasi‐continuous basis using surface seismic data. Current strategies and logistics for seismic data acquisition impose restrictions on the calendar‐time temporal resolution obtainable for a given surface‐seismic time‐lapse monitoring program. One factor that restricts the implementation of a quasi‐continuous monitoring program using conventional strategies is the time it takes to acquire a complete survey. Here quasi‐continuous monitoring describes the process of reservoir monitoring at short‐time intervals. Our approach circumvents the restriction by requiring only a subset of complete survey data each time an image of the reservoir is needed using surface seismic data. Ideally, the time interval between survey subset acquisitions should be short so that changes in the reservoir properties are small. The accumulated data acquired are used to estimate the unavailable data at the monitor survey time and the combined recorded and estimated data are used to produce an image of the subsurface for monitoring. We will illustrate the effectiveness of our approach using 2D and 3D synthetic seismic data and 3D field seismic data. We will explain the benefits and drawbacks of the proposed approach.     

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。      

Sub‐sample time shift and horizontal displacement measurements using phase‐correlation method in time‐lapse seismic

Hydrocarbon production and fluid injection affect the level of subsurface stress and physical properties of the subsurface, and can cause reservoir‐related issues, such as compaction and subsidence. Monitoring of oil and gas reservoirs is therefore crucial. Time‐lapse seismic is used to monitor reservoirs and provide evidence of saturation and pressure changes within the reservoir. However, relative to background velocities and reflector depths, the time‐lapse changes in velocity and geomechanical properties are typically small between consecutive surveys. These changes can be measured by using apparent displacement between migrated images obtained from recorded data of multiple time‐lapse surveys. Apparent displacement measurements by using the classical cross‐correlation method are poorly resolved. Here, we propose the use of a phase‐correlation method, which has been developed in satellite imaging for sub‐pixel registration of the images, to overcome the limitations of cross‐correlation. Phase correlation provides both vertical and horizontal displacements with a much better resolution. After testing the method on synthetic data, we apply it to a real dataset from the Norne oil field and show that the phase‐correlation method can indeed provide better resolution.