4D seismic for oil-rim monitoring

In the central North Sea ‘Gannet‐A’ field, a 50 ft oil rim is overlain by a gas cap of variable thickness. Oil is produced from horizontal wells which initially produced dry oil, but as the field became more mature, a significant water cut was seen in several wells. A dedicated 4D seismic monitor survey was acquired in order to assess the remaining distribution of oil reserves. By forward modelling the synthetic seismic response to parameters such as contact movement and residual saturations (using 2D and 3D wedge models), and comparing the results with real seismic data, we are able to decipher the contact movements across the field. It is shown that, in one part of the field, the increased water cut is caused primarily by the vertical displacement of the entire oil rim into the initial gas cap. This oil‐rim displacement produces a very different 4D seismic response from the case of a static gas–oil contact and rising oil–water contact (normal production). As a result of these observations, we are able to optimize field production by both re‐perforation of existing wells and by drilling sidetracks into the displaced rim: a brown‐field development opportunity that might otherwise be missed.     

Multi‐transient electromagnetic repeatability experiment over the North Sea Harding field‡

We present results of synthetic time‐lapse and real repeatability multi‐transient electromagnetic surveys over the North Sea Harding field. Using Archie's law to convert porosity and fluid saturation to resistivity we created 3D isotropic models of the reservoir resistivity at different stages of production from the initial state in 1996 through to complete hydrocarbon production by 2016 and, for each stage, we simulated an east‐west transient electromagnetic survey line across Harding. Unconstrained 1D full‐waveform Occam inversions of these synthetic data show that Harding should be detectable and its lateral extent reasonably well‐defined. Resistivity changes caused by hydrocarbon production from initial pre‐production state to production of the oil rim in 2011 are discernible as are significant changes from 2011–2016 during the modelled gas blowdown phase. The 2D repeatability surveys of 2007 and 2008 tied two wells: one on and the other off the structure. Between the two surveys the segment of the field under investigation produced 3.9 million barrels of oil – not enough to generate an observable time‐lapse electromagnetic anomaly with a signal‐to‐noise ratio of 40 dB. Processing of the 2007 and 2008 data included deconvolution for the measured source current and removal of spatially‐correlated noise, which increased the signal‐to‐noise ratio of the recovered impulse responses by about 20 dB and resulted in a normalized root‐mean‐square difference of 3.9% between the data sets. 1D full‐waveform Occam inversions of the real data showed that Harding was detectable and its lateral extent was also reasonably well‐defined. The results indicate that the multi‐transient electromagnetic method is suitable for exploration, appraisal and monitoring hydrocarbon production.     

Evidence of short-term groundwater recharge signal propagation from the Andes to the central Atacama Desert: a singular spectrum analysis approach

The effect of pressure-driven groundwater recharge signal propagation in the Andean-Atacamenian environment is investigated by assessing a record of 15 years of water table fluctuations of an unconfined–confined aquifer system. Based on a singular spectrum analysis of water table time series, it is shown that, in the given case, groundwater levels in the central Atacama Desert are hydraulically controlled by two distant recharge areas associated with the Andes. The maximum observed range of the pressure signal propagation is ~50 km over an elevation difference of more than 3000 m at a lag of ~25 months. Several findings indicate that an often-cited study misinterpreted a water level rise at the same site as an in-situ alluvial fan recharge. Thus, the effect’s impact on groundwater dynamics in complex aquifer systems can easily be overlooked. Singular spectrum analysis could be of use to investigate pressure effects at hydrologically comparable sites.     

基于奇异谱分析的重磁位场分离方法

奇异谱分析是一种近年兴起的时间序列分析方法,它利用降秩原理实现信号分离.该方法将数据空间投影到不同特征的子空间中,并用奇异值来表征这些子空间的性质,最后通过截取奇异值实现数据的重构.重磁位场分离可以看成一种多信号叠加的分离问题.不同特征的重磁异常具有不同特征的奇异谱,这是奇异谱分析用于解决位场分离问题的应用基础.本文通过建立理论模型,分析重磁异常的奇异谱特征,得出适用于重磁位场分离的最优参数选择方法,并与传统方法进行比较.对比发现,无论是横向叠加模型、垂向叠加模型还是斜向叠加模型,奇异谱分析都具有很好的分离效果.最后,将奇异谱分析用于鄂东南某矿区的重力资料处理中,实现弱异常的识别和分离.     

Two-dimensional inversion of magnetotelluric data with consecutive use of conjugate gradient and least-squares solution with singular value decomposition algorithms

I investigated the two‐dimensional magnetotelluric data inversion algorithms in studying two significant aspects within a linearized inversion approach. The first one is the method of minimization and second one is the type of stabilizing functional used in parametric functionals. The results of two well‐known inversion algorithms, namely conjugate gradient and the least‐squares solution with singular value decomposition, were compared in terms of accuracy and CPU time. In addition, magnetotelluric data inversion with various stabilizers, such as L2‐norm, smoothing, minimum support, minimum gradient support and first‐order minimum entropy, were examined. A new inversion algorithm named least‐squares solution with singular value decomposition and conjugate gradient is suggested in seeing the outcomes of the comparisons carried out on least‐squares solutions with singular value decomposition and conjugate gradient algorithms subject to a variety of stabilizers. Inversion results of synthetic data showed that the newly suggested algorithm yields better results than those of the individual implementations of conjugate gradient and least‐squares solution with singular value decomposition algorithms. The suggested algorithm and the above‐mentioned algorithms inversion results for the field data collected along a line crossing the North Anatolian Fault zone were also compared each other and results are discussed.     

Utilizing spectral decomposition to determine the distribution of injected CO2 at the Snøhvit Field

Time‐lapse 3D seismic reflection data, covering the CO₂ storage operation at the Snøhvit gas field in the Barents Sea, show clear amplitude and time‐delay differences following injection. The nature and extent of these changes suggest that increased pore fluid pressure contributes to the observed seismic response, in addition to a saturation effect. Spectral decomposition using the smoothed pseudo‐Wigner–Ville distribution has been used to derive discrete‐frequency reflection amplitudes from around the base of the CO₂ storage reservoir. These are utilized to determine the lateral variation in peak tuning frequency across the seismic anomaly as this provides a direct proxy for the thickness of the causative feature. Under the assumption that the lateral and vertical extents of the respective saturation and pressure changes following CO₂ injection will be significantly different, discrete spectral amplitudes are used to distinguish between the two effects. A clear spatial separation is observed in the distribution of low‐ and high‐frequency tuning. This is used to discriminate between direct fluid substitution of CO₂, as a thin layer, and pressure changes that are distributed across a greater thickness of the storage reservoir. The results reveal a striking correlation with findings derived from pressure and saturation discrimination algorithms based on amplitude versus offset analysis.     

基于两步SVD变换的零偏VSP资料上下行波场分离方法

垂直地震剖面(Vertical Seismic Profiling,VSP)资料处理中波场分离是关键问题之一.随着属性提取技术的发展,新的属性参数(例如Q值)提取技术对波场分离的保真性要求越来越高.本文改进了传统奇异值分解(Singular Value Decomposition,SVD)法,给出了一种对波场的动力学特征具有更好的保真性,可以作为Q值提取的预处理步骤的零偏VSP资料上下行波场分离方法.该方法通过两步奇异值分解变换实现:第一步,排齐下行波同相轴,利用SVD变换压制部分下行波能量;第二步,在剩余波场中排齐上行波同相轴,使用SVD变换提取上行波场.在该方法的实现过程中,压制部分下行波能量后的剩余波场中仍然存在较强的下行波干扰,使得上行波同相轴的排齐比较困难.本文给出了一种通过极大化多道数据线性相关程度(Maximize Coherence,MC)排齐同相轴的算法,在一定程度上解决了低信噪比下排齐同相轴的问题.将本文提出的方法用于合成数据和实际资料的处理,并与传统SVD法的处理结果进行对比,结果表明本文提出的波场分离方法具有良好的保真性,得到波场的质量明显优于传统SVD法.通过对本文方法和传统SVD法处理合成数据得到的下行波场提取Q值,然后进行对比可知,本文方法可以有效提高所提取Q值的准确性,适合作为Q值提取的预处理步骤.     

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.     

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.     

Imaging Hydrological Processes in Headwater Riparian Seeps with Time‐Lapse Electrical Resistivity

Delineating hydrologic and pedogenic factors influencing groundwater flow in riparian zones is central in understanding pathways of water and nutrient transport. In this study, we combined two‐dimensional time‐lapse electrical resistivity imaging (ERI) (depth of investigation approximately 2 m) with hydrometric monitoring to examine hydrological processes in the riparian area of FD‐36, a small (0.4 km²) agricultural headwater basin in the Valley and Ridge region of east‐central Pennsylvania. We selected two contrasting study sites, including a seep with groundwater discharge and an adjacent area lacking such seepage. Both sites were underlain by a fragipan at 0.6 m. We then monitored changes in electrical resistivity, shallow groundwater, and nitrate‐N concentrations as a series of storms transitioned the landscape from dry to wet conditions. Time‐lapse ERI revealed different resistivity patterns between seep and non‐seep areas during the study period. Notably, the seep displayed strong resistivity reductions (～60%) along a vertically aligned region of the soil profile, which coincided with strong upward hydraulic gradients recorded in a grid of nested piezometers (0.2‐ and 0.6‐m depth). These patterns suggested a hydraulic connection between the seep and the nitrate‐rich shallow groundwater system below the fragipan, which enabled groundwater and associated nitrate‐N to discharge through the fragipan to the surface. In contrast, time‐lapse ERI indicated no such connections in the non‐seep area, with infiltrated rainwater presumably perched above the fragipan. Results highlight the value of pairing time‐lapse ERI with hydrometric and water quality monitoring to illuminate possible groundwater and nutrient flow pathways to seeps in headwater riparian areas.     

Noise suppression for microseismic data by non‐subsampled shearlet transform based on singular value decomposition

The existence of strong random noise in surface microseismic data may decrease the utility of these data. Non‐subsampled shearlet transform can effectively suppress noise by properly setting a threshold to the non‐subsampled shearlet transform coefficients. However, when the signal‐to‐noise ratio of data is low, the coefficients related to the noise are very close to the coefficients associated with signals in the non‐subsampled shearlet transform domain that the coefficients related to the noise will be retained and be treated as signals. Therefore, we need to minimise the overlapping coefficients before thresholding. In this paper, a singular value decomposition algorithm is introduced to the non‐subsampled shearlet transform coefficients, and low‐rank approximation reconstructs each non‐subsampled shearlet transform coefficient matrix in the singular value decomposition domain. The non‐subsampled shearlet transform coefficients of signals have bigger singular values than those of the random noise, which implies that the non‐subsampled shearlet transform coefficients can be well estimated by taking only a few largest singular values. Therefore, those properties of singular value decomposition may significantly help minimise overlapping of noise and signals coefficients in the non‐subsampled shearlet transform domain. Finally, the denoised microseismic data are obtained easily by giving a simple threshold to the reconstructed coefficient matrix. The performance of the proposed method is evaluated on both synthetic and field microseismic data. The experimental results illustrate that the proposed method can eliminate random noise and preserve signals of interest more effectively.     

Time‐lapse seismic imaging using regularized full‐waveform inversion with a prior model: which strategy?

Full‐waveform inversion is an appealing technique for time‐lapse imaging, especially when prior model information is included into the inversion workflow. Once the baseline reconstruction is achieved, several strategies can be used to assess the physical parameter changes, such as parallel difference (two separate inversions of baseline and monitor data sets), sequential difference (inversion of the monitor data set starting from the recovered baseline model) and double‐difference (inversion of the difference data starting from the recovered baseline model) strategies. Using synthetic Marmousi data sets, we investigate which strategy should be adopted to obtain more robust and more accurate time‐lapse velocity changes in noise‐free and noisy environments. This synthetic application demonstrates that the double‐difference strategy provides the more robust time‐lapse result. In addition, we propose a target‐oriented time‐lapse imaging using regularized full‐waveform inversion including a prior model and model weighting, if the prior information exists on the location of expected variations. This scheme applies strong prior model constraints outside of the expected areas of time‐lapse changes and relatively less prior constraints in the time‐lapse target zones. In application of this process to the Marmousi model data set, the local resolution analysis performed with spike tests shows that the target‐oriented inversion prevents the occurrence of artefacts outside the target areas, which could contaminate and compromise the reconstruction of the effective time‐lapse changes, especially when using the sequential difference strategy. In a strongly noisy case, the target‐oriented prior model weighting ensures the same behaviour for both time‐lapse strategies, the double‐difference and the sequential difference strategies and leads to a more robust reconstruction of the weak time‐lapse changes. The double‐difference strategy can deliver more accurate time‐lapse variation since it can focus to invert the difference data. However, the double‐difference strategy requires a preprocessing step on data sets such as time‐lapse binning to have a similar source/receiver location between two surveys, while the sequential difference needs less this requirement. If we have prior information about the area of changes, the target‐oriented sequential difference strategy can be an alternative and can provide the same robust result as the double‐difference strategy.     

A feasibility study of borehole radar as a permanent downhole sensor

Permanent downhole sensors provide the eyes and ears to the reservoir and enable monitoring the reservoir conditions on a real‐time basis. In particular, the use of sensors and remotely controlled valves in wells and on the surface, in combination with reservoir flow models provide enormous benefits to reservoir management and oil production. We suggest borehole radar measurements as a promising technique capable to monitor the arrival of undesired fluids in the proximity of production wells. We use 1D modelling to investigate the expected signal magnitude and depth of investigation of a borehole radar sensor operating in an oilfield environment. We restrict the radar applicability to environments where the radar investigation depth can fit the reservoir size necessary to be monitored. Potential applications are steam chamber monitoring in steam assisted gravity drainage processes and water front monitoring in thin oil rim environments. A more sophisticated analysis of the limits of a radar system is carried out through 2D finite‐difference time‐domain simulations. The metal components of the wellbore casing can cause destructive interference with the emitted signal. A high dielectric medium surrounding the production well increases the amplitude of the signal and so the radar performance. Other reservoir constraints are given by the complexity of the reservoir and the dynamic of the fluids. Time‐lapse changes in the heterogeneity of the background formation strongly affect the retrieval of the target reflections and gradual fluid saturation changes reduce the amplitudes of the reflections.     

Theory and seismic applications of the eigenimage discrete wavelet transform

Discrete wavelet transforms are useful in a number of signal processing applications. To improve the scale resolution, a joint function of time, scale and eigenvalue that describes the energy density or intensity of a signal simultaneously in the wavelet and eigenimage domains is constructed. A hybrid method, which decomposes eigenimages in the wavelet domain, is developed and tested on field data with a variety of noise types. Several illustrative examples examine the ability of wavelet transforms to resolve features at several scales. Successful applications to time‐lapse seismic reservoir monitoring are presented. In reservoir monitoring, the scale‐dependent properties of the eigenstructure of the 4D data covariance matrix enable us to extract the low‐frequency time‐lapse signal that is the result of internal diffusive losses caused by fluid flow.     

Sensitivity analysis of temperature‐index melt simulations to near‐surface lapse rates and degree‐day factors at Vestari‐Hagafellsjökull,Langjökull,Iceland

The performance of temperature‐index melt models is particularly affected by the choice of near‐surface lapse rate used to determine the sum of positive daily temperatures at different elevations, and by the choice of factor used to relate this sum to the rate of melting. Data from the Langjökull ice cap are used in this study to quantify the influence of lapse‐rate and degree‐day factor variation on temperature‐index melt simulations. The lapse rate was significantly lower during summer than in spring or autumn, as a result of diabatic cooling, reducing boundary‐layer sensitivity to free‐air temperature change. The summer lapse rate was also significantly lower than the saturated adiabatic lapse rate. A sensitivity of approximately 600 mm water equivalent (w.e.) cumulative June–August melt per 0.1 °C 100 m^–1 change in lapse rate was found across a 500‐m altitude range. The sensitivity to a 1‐mm w.e. °C^–1 day^–1 change in degree‐day factors varied more: from approximately 500 mm w.e. cumulative summer melt at low elevation to approximately 200 mm w.e. at high elevation, reflecting the decline in melt rates associated with the greater persistence of snow with increasing altitude. The determination of a degree‐day factor for snow is complicated by the densification of the ageing snowpack, but the application of a parameterization for near‐surface density on the basis of albedo helped account for the development of snow water equivalence. Lapse rate was parameterized as a function of standardized anomalies in 750 hPa reanalysis temperature and significantly improved the simulation of cumulative summer melt compared with models applying the saturated adiabatic lapse rate. Copyright © 2012 John Wiley & Sons, Ltd.     

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.     

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.     

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.     

Wavelet correlation filter for wide-angle seismic data

A new filtering technique for single‐fold wide‐angle reflection/refraction seismic data is presented. The technique is based on the wavelet decomposition of a set of adjacent traces followed by coherence analysis. The filtering procedure consists of three steps. In the first, a wavelet decomposition of traces into different detail levels is performed. In the second, the coherence attributes for each level are evaluated by calculating cross‐correlation functions of detail portions contained in a space–time moving window. Finally, the filtered traces are obtained as a weighted reconstruction of the trace details. Each weight is obtained from the coherence‐attributes distribution estimated in a proper interval. A sequence of tests is then conducted in order to select possible optimum or unsuitable wavelet bases. The efficiency of the filter proposed was assessed by calculating some properly designed parameters in order to compare it with other standard de‐noising techniques. The proposed method produced a clear signal enhancement in high‐density wide‐angle seismic data, thus proving that it is a useful processing tool for a reliable correlation of seismic phases.     

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.