Rock physics modelling and inversion for saturation-pressure changes in time-lapse seismic studies

Time-lapse seismic data are generally used to monitor the changes in dynamic reservoir properties such as fluid saturation and pore or effective pressure. Changes in saturation and pressure due to hydrocarbon production usually cause changes in the seismic velocities and as a consequence changes in seismic amplitudes and travel times. This work proposes a new rock physics model to describe the relation between saturation-pressure changes and seismic changes and a probabilistic workflow to quantify the changes in saturation and pressure from time-lapse seismic changes. In the first part of this work, we propose a new quadratic approximation of the rock physics model. The novelty of the proposed formulation is that the coefficients of the model parameters (i.e. the saturation-pressure changes) are functions of the porosity, initial saturation and initial pressure. The improvements in the results of the forward model are shown through some illustrative examples. In the second part of the work, we present a Bayesian inversion approach for saturation-pressure 4D inversion in which we adopt the new formulation of the rock physics approximation. The inversion results are validated using synthetic pseudo-logs and a 3D reservoir model for CO₂ sequestration.     

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.     

Test of rock physics models for prediction of seismic velocities in shallow unconsolidated sands: a well log data case‡

This paper tests the ability of various rock physics models to predict seismic velocities in shallow unconsolidated sands by comparing the estimates to P and S sonic logs collected in a shallow sand layer and ultrasonic laboratory data of an unconsolidated sand sample. The model fits are also evaluated with respect to the conventional model for unconsolidated sand. Our main approach is to use Hertz‐Mindlin and Walton contact theories, assuming different weight fractions of smooth and rough contact behaviours, to predict the elastic properties of the high porosity point. Using either the Hertz‐Mindlin or Walton theories with rough contact behaviour to define the high porosity endpoint gives an over‐prediction of the velocities. The P‐velocity is overpredicted by a factor of ～1.5 and the S‐velocity by a factor of ～1.8 for highly porous gas‐sand. The degree of misprediction decreases with increasing water saturation and porosity.Using the Hertz‐Mindlin theory with smooth contact behaviour or weighted Walton models gives a better fit to the data, although the data are best described using the Walton smooth model. To predict the properties at the lower porosities, the choice of bounding model attached to the Walton Smooth model controls the degree of fit to the data, where the Reuss bound best captures the porosity variations of dry and wet sands in this case since they are caused by depositional differences. The empirical models based on lab experiments on unconsolidated sand also fit the velocity data measured by sonic logs in situ, which gives improved confidence in using lab‐derived results.     

Monitoring fluid substitution in rock samples from noise correlation

An alternative laboratory technique to measure the elastic constants of solid samples, based on the analysis of the cross‐correlation spectra of the vibratory response of randomly excited short solid cylinders, has been recently proposed. The aim of this paper is to check the ability of the technique called passive ultrasonic interferometry to monitor fluid substitution in different rock samples. Velocity variations due to fluid substitution are easily measured if the wave attenuation in the fluid‐saturated rock is not too large (typically in rocks with few cracks or microfractures). The experimental results are in agreement with the predictions of Biot–Gassmann poroelastic theory. The effect of substituting water with a stiffer saturating fluid, such as ethylene glycol, is to increase the overall bulk modulus of the rock, without any substantial effect on shear modulus. Furthermore, the experimental results compare well with those obtained independently with conventional pulse‐transmission technique using ultrasonic transducers. However, the measured pulse‐transmission bulk moduli are slightly larger than the corresponding measured ultrasonic interferometry moduli, with the deviation increasing with increasing fluid viscosity. This can be explained by dispersion due to wave‐induced flow of the viscous fluid since pulse‐transmission experiments involve higher frequencies than ultrasonic interferometry experiments.     

Rock physics modelling based on depositional and burial history of Barents Sea sandstones

Understanding how physical properties and seismic signatures of present day rocks are related to ancient geological processes is important for enhanced reservoir characterization. In this paper, we have studied this relationship for the Kobbe Formation sandstone in the Barents Sea. These rocks show anomalous low shear velocities and high V_P/V_S ratios, which does not agree well with conventional rock physics models for moderately to well consolidated sandstones. These sandstones have been buried relatively deeply and subsequently uplifted 1–2 km. We compared well log data of the Kobbe sandstone with velocity–depth trends modelled by integrating basin modelling principles and rock physics. We found that more accurate velocity predictions were obtained when first honouring mechanical and chemical compaction during burial, followed by generation of micro-cracks during uplift. We suspect that these micro-cracks are formed as overburden is eroded, leading to changes in the subsurface stress-field. Moreover, the Kobbe Formation is typically heterogeneous and characterized by structural clays and mica that can reduce the rigidity of grain contacts. By accounting for depositional and burial history, our velocity predictions become more consistent with geophysical observables. Our approach yields more robust velocity predictions, which are important in prospect risking and net erosion estimates.     

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.     

Influence of subsurface injection on time‐lapse seismic: laboratory studies at seismic and ultrasonic frequencies

Seismic monitoring of reservoir and overburden performance during subsurface CO₂ storage plays a key role in ensuring efficiency and safety. Proper interpretation of monitoring data requires knowledge about the rock physical phenomena occurring in the subsurface formations. This work focuses on rock stiffness and elastic velocity changes of a shale overburden formation caused by both reservoir inflation induced stress changes and leakage of CO₂ into the overburden. In laboratory experiments, Pierre shale I core plugs were loaded along the stress path representative for the in situ stress changes experienced by caprock during reservoir inflation. Tests were carried out in a triaxial compaction cell combining three measurement techniques and permitting for determination of (i) ultrasonic velocities, (ii) quasistatic rock deformations, and (iii) dynamic elastic stiffness at seismic frequencies within a single test, which allowed to quantify effects of seismic dispersion. In addition, fluid substitution effects connected with possible CO₂ leakage into the caprock formation were modelled by the modified anisotropic Gassmann model. Results of this work indicate that (i) stress sensitivity of Pierre shale I is frequency dependent; (ii) reservoir inflation leads to the increase of the overburden Young's modulus and Poisson's ratio; (iii) in situ stress changes mostly affect the P‐wave velocities; (iv) small leakage of the CO₂ into the overburden may lead to the velocity changes, which are comparable with one associated with geomechanical influence; (v) non‐elastic effects increase stress sensitivity of an acoustic waves; (iv) and both geomechanical and fluid substitution effects would create significant time shifts, which should be detectable by time‐lapse seismic.     

The impact of different clay minerals on the anisotropy of clay matrix in shale

Although clay is composed of disconnected anisotropic clay platelets, many rock physics models treat the clay platelets in shale as interconnected. However, the clay matrix in shales can be modelled as anisotropic clay platelets embedded within a soft isotropic interplatelet region, allowing the influence of disconnected clay platelets on the elastic properties of the clay matrix to be analysed. In this model, properties of the interplatelet region are governed by its effective bulk and shear moduli, whereas the effective properties of the clay platelets are governed by their volume fraction, aspect ratio and elastic stiffness tensor. Together, these parameters implicitly account for variations in clay and fluid properties, as well as fluid saturation. Elastic stiffnesses of clay platelets are obtained from the literature, including both experimental measurements and first-principles calculations of the full anisotropic (monoclinic or triclinic) elastic stiffness tensors of layered silicates. These published elastic stiffness tensors are used to compile a database of equivalent transverse isotropic elastic stiffness tensors, and other physical properties, for eight common varieties of layered silicates. Clay matrix anisotropy is then investigated by examining the influence of these different elastic stiffnesses, and of varying model parameters, upon the effective transverse isotropic elastic stiffness tensor of the clay matrix. The relationship between the different clay minerals and their associated anisotropy parameters is studied, and their impact on the resulting anisotropy of the clay matrix is analysed.     

Marine transient electromagnetic sounding of deep buried hydrocarbon reservoirs: principles,methodologies and limitations

The possibility of a time‐domain electromagnetic sounding method using excitation and measurement of vertical electric fields to search for and identify deeply buried reservoirs of hydrocarbons offshore is investigated. The method operates on source–receiver offsets, which are several times less than the depth of the reservoir. Geoelectric information is obtained from the transient responses recorded in the pauses between the pulses of electric current in the absence of the source field. The basics of the method, as well as its sensitivity, resolution, and the highest accessible depth of soundings for various geological conditions in a wide range of sea depths, are analyzed. For the analysis, 1D and 3D geoelectric models of hydrocarbon reservoirs are used. It is shown that under existing technologies of excitation and measurement of vertical electric fields, the highest accessible depth of soundings can be up to 4 km. Technology for the inversion and interpretation of transient responses is demonstrated on experimental data.     

Effect of pore geometry on Gassmann fluid substitution

Although there is no assumption of pore geometry in derivation of Gassmann's equation, the pore geometry is in close relation with hygroscopic water content and pore fluid communication between the micropores and the macropores. The hygroscopic water content in common reservoir rocks is small, and its effect on elastic properties is ignored in the Gassmann theory. However, the volume of hygroscopic water can be significant in shaly rocks or rocks made of fine particles; therefore, its effect on the elastic properties may be important. If the pore fluids in microspores cannot reach pressure equilibrium with the macropore system, assumption of the Gassmann theory is violated. Therefore, due to pore structure complexity, there may be a significant part of the pore fluids that do not satisfy the assumption of the Gassmann theory. We recommend that this part of pore fluids be accounted for within the solid rock frame and effective porosity be used in Gassmann's equation for fluid substitution. Integrated study of ultrasonic laboratory measurement data, petrographic data, mercury injection capillary pressure data, and nuclear magnetic resonance T₂ data confirms rationality of using effective porosity for Gassmann fluid substitution. The effective porosity for Gassmann's equation should be frequency dependent. Knowing the pore geometry, if an empirical correlation between frequency and the threshold pore‐throat radius or nuclear magnetic resonance T₂ could be set up, Gassmann's equation can be applicable to data measured at different frequencies. Without information of the pore geometry, the irreducible water saturation can be used to estimate the effective porosity.     

A rock physics model to map gross lithology using compaction

Differential compaction has long been used by seismic interpreters to infer subsurface geology using knowledge of the relative compaction of different types of sediments. We outline a method to infer the gross fraction of shale in an interval between two seismic horizons using sandstone and shale compaction laws. A key component of the method involves reconstruction of a smooth depositional horizon by interpolating decompacted thicknesses from well control. We derive analytic formulae for decompaction calculations using known porosity–stress relations and do not employ discrete layer iterative methods; these formulae were found to depend not only upon the gross fraction of shale but also on the clay content of the shales and the thickness of the interval. The relative merits of several interpolation options were explored, and found to depend upon the structural setting. The method was successfully applied to an oil sands project in Alberta, Canada.     

Full waveform inversion in the time lapse mode applied to CO2 storage at Sleipner

Carbon capture and storage is a viable greenhouse gas mitigation technology and the Sleipner CO₂ sequestration site in the North Sea is an excellent example. Storage of CO₂ at the Sleipner site requires monitoring over large areas, which can successfully be accomplished with time lapse seismic imaging. One of the main goals of CO₂ storage monitoring is to be able to estimate the volume of the stored CO₂ in the reservoir. This requires a parametrization of the subsurface as exact as possible. Here we use elastic 2D time‐domain full waveform inversion in a time lapse manner to obtain a P‐wave velocity constrain directly in the depth domain for a base line survey in 1994 and two post‐injection surveys in 1999 and 2006. By relating velocity change to free CO₂ saturation, using a rock physics model, we find that at the considered location the aquifer may have been fully saturated in some places in 1999 and 2006.     

Rock physics model for seismic velocity & fluid substitution in sub-resolution interbedded sand–shale sequences

The measured geophysical response of sand – shale sequences is an average over multiple layers when the tool resolution (seismic or well log) is coarser than the scale of sand – shale mixing. Shale can be found within sand – shale sequences as laminations, dispersed in sand pores, as well as load bearing clasts. We present a rock physics framework to model seismic/sonic properties of sub-resolution interbedded shaly sands using the so-called solid and mineral substitution models. This modelling approach stays consistent with the conceptual model of the Thomas–Stieber approach for estimating volumetric properties of shaly sands; thus, this work connects established well log data-based petrophysical workflows with quantitative interpretation of seismic data for modelling hydrocarbon signature in sand – shale sequences. We present applications of the new model to infer thickness of sand – shale lamination (i.e., net to gross) and other volumetric properties using seismic data. Another application of the new approach is fluid substitution in sub-resolution interbedded sand–shale sequences that operate directly at the measurement scale without the need to downscale; such a procedure has many practical advantages over the approach of “first-downscale-and-then-upscale” as it is not very sensitive to errors in estimated sand fraction and end member sand/shale properties and remains stable at small sand/shale fractions.     

Spatial constrained inverse rock physics modelling

Predicting reservoir parameters, such as porosity, lithology, and saturations, from geophysical parameters is a problem with non‐unique solutions. The variance in solutions can be extensive, especially for saturation and lithology. However, the reservoir parameters will typically vary smoothly within certain zones—in vertical and horizontal directions. In this work, we integrate spatial correlations in the predicted parameters to constrain the range of predicted solutions from a particular type of inverse rock physics modelling method. Our analysis is based on well‐log data from the Glitne field, where vertical correlations with depth are expected. It was found that the reservoir parameters with the shortest depth correlation (lithology and saturation) provided the strongest constraint to the set of solutions. In addition, due to the interdependence between the reservoir parameters, constraining the predictions by the spatial correlation of one parameter also reduced the number of predictions of the other two parameters. Moreover, the use of additional constraints such as measured log data at specific depth locations can further narrow the range of solutions.     

Deep neural network application for 4D seismic inversion to changes in pressure and saturation: Optimizing the use of synthetic training datasets

In this work, we tackle the challenge of quantitative estimation of reservoir dynamic property variations during a period of production, directly from four-dimensional seismic data in the amplitude domain. We employ a deep neural network to invert four-dimensional seismic amplitude maps to the simultaneous changes in pressure, water and gas saturations. The method is applied to a real field data case, where, as is common in such applications, the data measured at the wells are insufficient for properly training deep neural networks, thus, the network is trained on synthetic data. Training on synthetic data offers much freedom in designing a training dataset, therefore, it is important to understand the impact of the data distribution on the inversion results. To define the best way to construct a synthetic training dataset, we perform a study on four different approaches to populating the training set making remarks on data sizes, network generality and the impact of physics-based constraints. Using the results of a reservoir simulation model to populate our training datasets, we demonstrate the benefits of restricting training samples to fluid flow consistent combinations in the dynamic reservoir property domain. With this the network learns the physical correlations present in the training set, incorporating this information into the inference process, which allows it to make inferences on properties to which the seismic data are most uncertain. Additionally, we demonstrate the importance of applying regularization techniques such as adding noise to the synthetic data for training and show a possibility of estimating uncertainties in the inversion results by training multiple networks.     

Gravimetric monitoring of the first field‐wide steam injection in a fractured carbonate field in Oman – a feasibility study

Gas‐Oil Gravity Drainage is to be enhanced by steam injection in a highly fractured, low permeability carbonate field in Oman. Following a successful pilot, field‐wide steam injection is being implemented, first of this type in the world. A dedicated monitoring program has been designed to track changes in the reservoir. Various observations are to be acquired, including, surface deformation, temperature measurements, microseismic, well logs, pressure and saturation measurements to monitor the reservoir. Because significant changes in the reservoir density are expected, time‐lapse gravimetry is also being considered. In this paper we investigate the feasibility of gravimetric monitoring of the thermally enhanced gravity drainage process at the carbonate field in Oman. For this purpose, forward gravity modelling is performed. Based on field groundwater measurements, the estimates of the hydrological signal are considered and it is investigated under what conditions the groundwater influences can be minimized. Using regularized inversion of synthetic gravity data, we analyse the achievable accuracy of heat‐front position estimates. In case of large groundwater variations at the field, the gravity observations can be significantly affected and, consequently, the accuracy of heat‐front monitoring can be deteriorated. We show that, by applying gravity corrections based on local observations of groundwater, the hydrological influences can to a large extent be reduced and the accuracy of estimates can be improved. We conclude that gravimetric monitoring of the heat‐front evolution has a great potential.     

Intra-survey reservoir fluctuations – implications for quantitative 4D seismic analysis

During the time taken for seismic data to be acquired, reservoir pressure may fluctuate as a consequence of field production and operational procedures and fluid fronts may move significantly. These variations prevent accurate quantitative measurement of the reservoir change using 4D seismic data. Modelling studies on the Norne field simulation model using acquisition data from ocean-bottom seismometer and towed streamer systems indicate that the pre-stack intra-survey reservoir fluctuations are important and cannot be neglected. Similarly, the time-lapse seismic image in the post-stack domain does not represent a difference between two states of the reservoir at a unique base and monitor time, but is a mixed version of reality that depends on the sequence and timing of seismic shooting. The outcome is a lack of accuracy in the measurement of reservoir changes using the resulting processed and stacked 4D seismic data. Even for perfect spatial repeatability between surveys, a spatially variant noise floor is still anticipated to remain. For our particular North Sea acquisition data, we find that towed streamer data are more affected than the ocean-bottom seismometer data. We think that this may be typical for towed streamers due to their restricted aperture compared to ocean-bottom seismometer acquisitions, even for a favourable time sequence of shooting and spatial repeatability. Importantly, the pressure signals on the near and far offset stacks commonly used in quantitative 4D seismic inversion are found to be inconsistent due to the acquisition timestamp. Saturation changes at the boundaries of fluid fronts appear to show a similar inconsistency across sub-stacks. We recommend that 4D data are shot in a consistent manner to optimize aerial time coverage, and that additionally, the timestamp of the acquisition should be used to optimize pre-stack quantitative reservoir analysis.     

Feasibility of utilizing wavelet phase to map the CO2 plume at the Ketzin pilot site,Germany

Spectral decomposition is a powerful tool that can provide geological details dependent upon discrete frequencies. Complex spectral decomposition using inversion strategies differs from conventional spectral decomposition methods in that it produces not only frequency information but also wavelet phase information. This method was applied to a time‐lapse three‐dimensional seismic dataset in order to test the feasibility of using wavelet phase changes to detect and map injected carbon dioxide within the reservoir at the Ketzin carbon dioxide storage site, Germany. Simplified zero‐offset forward modelling was used to help verify the effectiveness of this technique and to better understand the wavelet phase response from the highly heterogeneous storage reservoir and carbon dioxide plume. Ambient noise and signal‐to‐noise ratios were calculated from the raw data to determine the extracted wavelet phase. Strong noise caused by rainfall and the assumed spatial distribution of sandstone channels in the reservoir could be correlated with phase anomalies. Qualitative and quantitative results indicate that the wavelet phase extracted by the complex spectral decomposition technique has great potential as a practical and feasible tool for carbon dioxide detection at the Ketzin pilot site.     

Elastic impedance based facies classification using support vector machine and deep learning

Machine learning methods including support-vector-machine and deep learning are applied to facies classification problems using elastic impedances acquired from a Paleocene oil discovery in the UK Central North Sea. Both of the supervised learning approaches showed similar accuracy when predicting facies after the optimization of hyperparameters derived from well data. However, the results obtained by deep learning provided better correlation with available wells and more precise decision boundaries in cross-plot space when compared to the support-vector-machine approach. Results from the support-vector-machine and deep learning classifications are compared against a simplified linear projection based classification and a Bayes-based approach. Differences between the various facies classification methods are connected by not only their methodological differences but also human interactions connected to the selection of machine learning parameters. Despite the observed differences, machine learning applications, such as deep learning, have the potential to become standardized in the industry for the interpretation of amplitude versus offset cross-plot problems, thus providing an automated facies classification approach.     

裂缝型储层流体识别方法

裂缝型储层的描述包括预测裂缝分布特征和识别裂隙充填物.依据等效介质理论计算的纵波速度随裂缝密度的增大而减小.正演地震记录显示,裂缝介质含气时反射振幅最大,且变化程度比含油或含水时大.叠前方位AVO反演所得的各向异性梯度Bani与裂缝密度成正比,可用于描述有效裂缝发育强度.对于不同的裂缝密度,各向异性梯度Bani与各向同性梯度Biso的比值Ifluid(1)近似为常数,且对流体敏感.经裂缝纵横比和背景介质拉梅常数修正后,流体因子Ifluid既不随纵横比变化,又不受背景介质的影响,是裂缝型储层敏感的流体识别因子.在塔里木盆地塔北哈拉哈塘地区热瓦普区块碳酸盐岩储层裂缝发育区域,运用该参数在井点处的流体识别效果与钻井结果一致.