Vertical seismic profiling using a daisy‐chained deployment of fibre‐optic cables in four wells simultaneously – Case study at the Ketzin carbon dioxide storage site

The geological storage of carbon dioxide is considered as one of the measures to reduce greenhouse gas emissions and to mitigate global warming. Operators of storage sites are required to demonstrate safe containment and stable behaviour of the storage complex that is achieved by geophysical and geochemical monitoring, combined with reservoir simulations. For site characterization, as well as for imaging the carbon dioxide plume in the reservoir complex and detecting potential leakage, surface and surface‐borehole time‐lapse seismic monitoring surveys are the most widespread and established tools. At the Ketzin pilot site for carbon dioxide storage, permanently installed fibre‐optic cables, initially deployed for distributed temperature sensing, were used as seismic receiver arrays, demonstrating their ability to provide high‐resolution images of the storage formation. A vertical seismic profiling experiment was acquired using 23 source point locations and the daisy‐chained deployment of a fibre‐optic cable in four wells as a receiver array. The data were used to generate a 3D vertical seismic profiling cube, complementing the large‐scale 3D surface seismic measurements by a high resolution image of the reservoir close to the injection well. Stacking long vibro‐sweeps at each source location resulted in vertical seismic profiling shot gathers characterized by a signal‐to‐noise ratio similar to gathers acquired using geophones. A detailed data analysis shows strong dependency of data quality on borehole conditions with significantly better signal‐to‐noise ratio in regions with good coupling conditions.     

Application of the continuous wavelet transform on seismic data for mapping of channel deposits and gas detection at the CO2SINK site, Ketzin, Germany

Conventional seismic data are band limited and therefore, provide limited geological information. Every method that can push the limits is desirable for seismic data analysis. Recently, time‐frequency decomposition methods are being used to quickly extract geological information from seismic data and, especially, for revealing frequency‐dependent amplitude anomalies. Higher frequency resolution at lower frequencies and higher temporal resolution at higher frequencies are the objectives for different time‐frequency decomposition methods. Continuous wavelet transform techniques, which are the same as narrow‐band spectral analysis methods, provide frequency spectra with high temporal resolution without the windowing process associated with other techniques. Therefore, this technique can be used for analysing geological information associated with low and high frequencies that normally cannot be observed in conventional seismic data. In particular, the continuous wavelet transform is being used to detect thin sand bodies and also as a direct hydrocarbon indicator. This paper presents an application of the continuous wavelet transform method for the mapping of potential channel deposits, as well as remnant natural gas detection by mapping low‐frequency anomalies associated with the gas. The study was carried out at the experimental CO₂ storage site at Ketzin, Germany (CO₂SINK). Given that reservoir heterogeneity and faulting will have significant impact on the movement and storage of the injected CO₂, our results are encouraging for monitoring the migration of CO₂ at the site. Our study confirms the efficiency of the continuous wavelet transform decomposition method for the detection of frequency‐dependent anomalies that may be due to gas migration during and after the injection phase and in this way, it can be used for real‐time monitoring of the injected CO₂ from both surface and borehole seismics.     

地震复谱分解技术及其在烃类检测中的应用

谱分解技术在地震解释领域已得到广泛应用,但常用的谱分解方法存在两方面的不足.一是时间分辨率低,难以对薄层进行刻画;二是在烃类检测中多解性强,难以区分流体类型.为了改善该问题,本文提出一种基于地震复谱分解技术的烃类检测方法.复谱分解是指用一个包含多个不同频率Ricker子波的复子波库对地震道进行分解,从而得到时变子波频率和相位信息的过程.借助稀疏反演技术复谱分解可以获得高分辨率的时频能量谱和时频相位谱.本文首先通过拟合算例验证了复谱分解方法刻画薄层的能力以及求取子波频率和相位的准确性.然后利用基于Kelvin-Voigt模型的黏弹波动方程数值模拟对衰减引起子波相位改变的原因进行了分析.最后通过实际资料应用展示了本文方法在储层预测中的高时间分辨率优势,验证了利用子波相位信息识别气藏的有效性.     

Monitoring CO2 saturation using time‐lapse amplitude versus offset analysis of 3D seismic data from the Ketzin CO2 storage pilot site,Germany

The injection of CO₂ at the Ketzin pilot site commenced in June 2008 and was terminated in August 2013 after 67 kT had been injected into a saline formation at a depth of 630–650 m. As part of the site monitoring program, four 3D surface seismic surveys have been acquired to date, one baseline and three repeats, of which two were conducted during the injection period, and one during the post‐injection phase. The surveys have provided the most comprehensive images of the spreading CO₂ plume within the reservoir layer. Both petrophysical experiments on core samples from the Ketzin reservoir and spectral decomposition of the 3D time‐lapse seismic data show that the reservoir pore pressure change due to CO₂ injection has a rather minor impact on the seismic amplitudes. Therefore, the observed amplitude anomaly is interpreted to be mainly due to CO₂ saturation. In this study, amplitude versus offset analysis has been applied to investigate the amplitude versus offset response from the top of the sandstone reservoir during the injection and post‐injection phases, and utilize it to obtain a more quantitative assessment of the CO₂ gaseous saturation changes. Based on the amplitude versus offset modelling, a prominent decrease in the intercept values imaged at the top of the reservoir around the injection well is indeed associated solely with the CO₂ saturation increase. Any change in the gradient values, which would, in case it was positive, be the only signature induced by the reservoir pressure variations, has not been observed. The amplitude versus offset intercept change is, therefore, entirely ascribed to CO₂ saturation and used for its quantitative assessment. The estimated CO₂ saturation values around the injection area in the range of 40%–60% are similar to those obtained earlier from pulsed neutron‐gamma logging. The highest values of 80% are found in the second seismic repeat in close vicinity to the injection and observation wells.     

The first post‐injection seismic monitor survey at the Ketzin pilot CO2 storage site: results from time‐lapse analysis

The injection of CO₂ at the Ketzin pilot CO₂ storage site started in June 2008 and ended in August 2013. During the 62 months of injection, a total amount of about 67 kt of CO₂ was injected into a saline aquifer. A third repeat three‐dimensional seismic survey, serving as the first post‐injection survey, was acquired in 2015, aiming to investigate the recent movement of the injected CO₂. Consistent with the previous two time‐lapse surveys, a predominantly west–northwest migration of the gaseous CO₂ plume in the up‐dip direction within the reservoir is inferred in this first post‐injection survey. No systematic anomalies are detected through the reservoir overburden. The extent of the CO₂ plume west of the injection site is almost identical to that found in the 2012 second repeat survey (after injection of 61 kt); however, there is a significant decrease in its size east of the injection site. Assessment of the CO₂ plume distribution suggests that the decrease in the size of the anomaly may be due to multiple factors, such as limited vertical resolution, CO₂ dissolution, and CO₂ migration into thin layers, in addition to the effects of ambient noise. Four‐dimensional seismic modelling based on dynamic flow simulations indicates that a dynamic balance between the newly injected CO₂ after the second repeat survey and the CO₂ migrating into thin layers and being dissolved was reached by the time of the first post‐injection survey. In view of the significant uncertainties in CO₂ mass estimation, both patchy and non‐patchy saturation models for the Ketzin site were taken into consideration.     

Comparison of surface seismic sources at the CO2SINK site, Ketzin, Germany

In 2004 three seismic surface sources (VIBSIST, accelerated weight drop and MiniVib) were tested in a pilot study at the Ketzin test site, Germany, a study site for geological storage of CO₂ (EU project CO₂SINK). The main objectives of this pilot study were to 1) evaluate the response of the Ketzin site to reflection seismics, especially at the planned injection depth, 2) test different acquisition parameters and 3) use the results to guide the planning of the 3D survey. As part of these objectives, we emphasize the source performance comparison in this study. The sources were tested along two perpendicular lines of 2.4 km length each. Data were acquired by shooting at all stations (source and receiver spacing of 20 m) on both lines, allowing common‐midpoint stacked sections to be produced. The sources' signal characteristics based on signal‐to‐noise ratio, signal penetration and frequency content of raw shot records were analysed and stacked sections were compared. The results show that all three surface sources are suitable for reflection seismic studies down to a depth of about 1 km and provide enough bandwidth for resolving the geological targets at the site, i.e., the Weser and Stuttgart Formations. Near surface conditions, especially a thick weathering layer present in this particular area, strongly influence the data quality, as indicated by the difference in reflectivity and signal‐to‐noise ratio of the two common‐midpoint lines. The stacked sections of the MiniVib source show the highest frequency signals down to about 500 ms traveltime (approximately 500 m depth) but also the shallowest signal penetration depth. The VIBSIST source generates signals with the highest signal‐to‐noise ratio and greatest signal penetration depth of the tested sources. In particular, reflections below 900 ms (approximately 1 km depth) are best imaged by the VIBSIST source. The weight drop performance lies in between these two sources and might be recommended as an appropriate source for a 3D survey at this site because of the shorter production time compared to the VIBSIST and MiniVib sources.     

Wavelet‐based cepstrum decomposition of seismic data and its application in hydrocarbon detection

How to use cepstrum analysis for reservoir characterization and hydrocarbon detection is an initial question of great interest to exploration seismologists. In this paper, wavelet‐based cepstrum decomposition is proposed as a valid technology for enhancing geophysical responses in specific frequency bands, in the same way as traditional spectrum decomposition methods do. The calculation of wavelet‐based cepstrum decomposition, which decomposes the original seismic volume into a series of common quefrency volumes, employs a sliding window to move over each seismic trace sample by sample. The key factor in wavelet‐based cepstrum decomposition is the selection of the sliding‐window length as it limits the frequency ranges of the common quefrency section. Comparison of the wavelet‐based cepstrum decomposition with traditional spectrum decomposition methods, such as short‐time Fourier transform and wavelet transform, is conducted to demonstrate the effectiveness of the wavelet‐based cepstrum decomposition and the relation between these two technologies. In hydrocarbon detection, seismic amplitude anomalies are detected using wavelet‐based cepstrum decomposition by utilizing the first and second common quefrency sections. This reduces the burden of needing dozens of seismic volumes to represent the response to different mono‐frequency sections in the interpretation of spectrum decomposition in conventional spectrum decomposition methods. The model test and the application of real data acquired from the Sulige gas field in the Ordos Basin, China, confirm the effectiveness of the seismic amplitude anomaly section using wavelet‐based cepstrum decomposition for discerning the strong amplitude anomalies at a particular quefrency buried in the broadband seismic response. Wavelet‐based cepstrum decomposition provides a new method for measuring the instantaneous cepstrum properties of a reservoir and offers a new field of processing and interpretation of seismic reflection data.     

Delineation of reservoirs using remote sensing and their storage estimate: an example of the Yellow River basin,China

Reservoirs are an integral component of water resources planning and management. Periodic and accurate assessment of the water storage change in reservoirs is an extraordinarily important aspect for better watershed management and water resources development. In view of the shortcomings of conventional approaches in locating reservoirs' spatial location and quantifying their storage, the remote sensing technique has several advantages, either for a single reservoir or for a group of reservoirs. The satellite‐based remote sensing data, encompassing spatial, spectral and temporal attributes, can provide high‐resolution synoptic and repetitive information with short time intervals on a large scale. Using remote sensing images in conjunction with Google Earth and field check of representative reservoirs, the spatial distribution of constructed reservoirs in the Yellow River basin was delineated, and their storage volume and the residence time of the stored water were estimated. The results showed that 2816 reservoirs were extracted from the images, accounting for 89·5% of the registered total. All large‐ and medium‐sized reservoirs were extracted while small reservoirs may not be extracted due to coarse resolution and cloud‐cover shadows. An empirical relationship between the extracted water surface area and the compiled storage capacity of representative reservoirs was developed. The water storage capacity was estimated to be 66·71 km³, about 92·7% of the total storage capacity reported by the authority. Furthermore, the basin was divided into 10 sub‐basins upon which the water's residence time was analysed. The water discharge in the basin has been greatly regulated. The residence time has surged to 3·97 years in recent years, ranking the Yellow River in the top three of the list in terms of residence time and flow regulation among large river systems in the world. It is expected that it will be further extended in future owing to decreasing water discharge and increasing reservoir storage capacity. Copyright © 2011 John Wiley & Sons, Ltd.     

S变换谱分解技术在深反射地震弱信号提取中的应用

在深反射地震资料处理中,当来自深部的有效弱信号和噪声干扰频带差异较小且难以区分时,传统滤波方法的应用会受到限制.谱分解方法是一种使用离散傅里叶变换,基于信号的频率-振幅谱等信息生成高分辨率地震图像的方法,通常用来识别介质物性横向分布特征,处理复杂介质内频谱变化和局部相位的不稳定性等问题,包括定位复杂断层和小尺度断裂等.S变换作为一种新的时频分析方法,具有自动调节分辨率的能力,近些年来被广泛应用到勘探地震、大地电磁等数据处理中,逐渐成为地球物理方法中噪声压制的有效方法之一.与常规石油反射地震资料相比,深反射主动源地震为了探测深部结构信息,常采用大药量激发方式、长排列观测系统等,导致深部有效信号基本湮灭在噪声干扰之中.针对深反射数据特点,本文结合谱分解和S变换技术,首先设计了简单的脉冲函数实验数据,证实S变换方法的有效性,同时说明谱分解方法的效果受所用时频分析方法影响较大,而其中决定分辨能力的变换窗函数的选取尤为重要.在此基础上,分别应用到深反射地震资料的单道和叠加剖面实际数据上,对比分析了传统变换谱分解和S变换谱分解的应用效果,单道资料对比结果表明:相比传统谱分解,S变换谱分解方法具有自动调节分辨率的能力,能够精确的标定深反射地震资料中弱信号不同时刻的频率分量;叠加剖面资料应用结果表明:由S变换谱分解得到的剖面结果与其他谱分解方法结果整体上具有较高的一致性,同时清晰地刻画出原叠加剖面上被噪声湮灭的低频细节特征,提高了剖面的分辨率及同相轴连续性;对比结果明显看出,Gabor变换谱分解方法得到的结果同相轴较为破碎,分析原因认为这是由Gabor变换的时频分解方法的定长窗函数所致,窗口大小不会随着信号频率的变化来调节长度,只能在处理的过程中根据一定的记录长度范围选取窗函数参数,而S变换谱分解方法在窗函数的选取时,通过时变信号的局部频率特征自动调节窗口长度,能够更好的刻画各个频段的细节特征,在深反射剖面成像应用中效果尤为明显.本文结果表明S变换谱分解技术在深地震叠加剖面上的应用有效地提高了来自深部弱反射信号的信噪比和分辨率,并刻画出了叠加剖面上所不具有的低频细节特征,在实际深反射地震资料处理中能有效保护低频弱信号获得更好的成像效果.本文为深地震反射资料中弱信号的保护处理找到一种有效的方法.     

THE DETERMINATION OF THE SEISMIC QUALITY FACTOR Q FROM VSP DATA: A COMPARISON OF DIFFERENT COMPUTATIONAL METHODS1

Ten methods for the computation of attenuation have been investigated, namely: amplitude decay, analytical signal, wavelet modelling, phase modelling, frequency modelling, rise-time, pulse amplitude, matching technique, spectral modelling and spectral ratio. In particular, we have studied the reliability of each of these methods in estimating correct values of Q using three synthetic VSP seismograms for plane P-waves with different noise contents. The investigations proved that no single method is generally superior. Rather, some methods are more suitable than others in specific situations depending on recording, noise or geology. The analytical signal method has been demonstrated to be superior if true amplitude recordings are available. Otherwise spectral modelling or, in the ‘ noise-free’ case the spectral ratio method, is optimal. Finally, two field VSPs in sediments are investigated. Only in the case of the highest quality VSP can significant information be deduced from the computed attenuation.     

Sparsity‐enhanced wavelet deconvolution

We propose a three‐step bandwidth enhancing wavelet deconvolution process, combining linear inverse filtering and non‐linear reflectivity construction based on a sparseness assumption. The first step is conventional Wiener deconvolution. The second step consists of further spectral whitening outside the spectral bandwidth of the residual wavelet after Wiener deconvolution, i.e., the wavelet resulting from application of the Wiener deconvolution filter to the original wavelet, which usually is not a perfect spike due to band limitations of the original wavelet. We specifically propose a zero‐phase filtered sparse‐spike deconvolution as the second step to recover the reflectivity dominantly outside of the bandwidth of the residual wavelet after Wiener deconvolution. The filter applied to the sparse‐spike deconvolution result is proportional to the deviation of the amplitude spectrum of the residual wavelet from unity, i.e., it is of higher amplitude; the closer the amplitude spectrum of the residual wavelet is to zero, but of very low amplitude, the closer it is to unity. The third step consists of summation of the data from the two first steps, basically adding gradually the contribution from the sparse‐spike deconvolution result at those frequencies at which the residual wavelet after Wiener deconvolution has small amplitudes. We propose to call this technique “sparsity‐enhanced wavelet deconvolution”. We demonstrate the technique on real data with the deconvolution of the (normal‐incidence) source side sea‐surface ghost of marine towed streamer data. We also present the extension of the proposed technique to time‐varying wavelet deconvolution.     

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.     

Elastic wave‐vector decomposition in heterogeneous anisotropic media

The goal of wave‐mode separation and wave‐vector decomposition is to separate a full elastic wavefield into three wavefields with each corresponding to a different wave mode. This allows elastic reverse‐time migration to handle each wave mode independently. Several of the previously proposed methods to accomplish this task require the knowledge of the polarisation vectors of all three wave modes in a given anisotropic medium. We propose a wave‐vector decomposition method where the wavefield is decomposed in the wavenumber domain via the analytical decomposition operator with improved computational efficiency using low‐rank approximations. The method is applicable for general heterogeneous anisotropic media. To apply the proposed method in low‐symmetry anisotropic media such as orthorhombic, monoclinic, and triclinic, we define the two S modes by sorting them based on their phase velocities (S1 and S2), which are defined everywhere except at the singularities. The singularities can be located using an analytical condition derived from the exact phase‐velocity expressions for S waves. This condition defines a weight function, which can be applied to attenuate the planar artefacts caused by the local discontinuity of polarisation vectors at the singularities. The amplitude information lost because of weighting can be recovered using the technique of local signal–noise orthogonalisation. Numerical examples show that the proposed approach provides an effective decomposition method for all wave modes in heterogeneous, strongly anisotropic media.     

Non-minimum phase wavelet estimation by non-linear optimization of all-pass operators

Convolution of a minimum‐phase wavelet with an all‐pass wavelet provides a means of varying the phase of the minimum‐phase wavelet without affecting its amplitude spectrum. This observation leads to a parametrization of a mixed‐phase wavelet being obtained in terms of a minimum‐phase wavelet and an all‐pass operator. The Wiener–Levinson algorithm allows the minimum‐phase wavelet to be estimated from the data. It is known that the fourth‐order cumulant preserves the phase information of the wavelet, provided that the underlying reflectivity sequence is a non‐Gaussian, independent and identically distributed process. This property is used to estimate the all‐pass operator from the data that have been whitened by the deconvolution of the estimated minimum‐phase wavelet. Wavelet estimation based on a cumulant‐matching technique is dependent on the bandwidth‐to‐central‐frequency ratio of the data. For the cumulants to be sensitive to the phase signatures, it is imperative that the ratio of bandwidth to central frequency is at least greater than one, and preferably close to two. Pre‐whitening of the data with the estimated minimum‐phase wavelet helps to increase the bandwidth, resulting in a more favourable bandwidth‐to‐central‐frequency ratio. The proposed technique makes use of this property to estimate the all‐pass wavelet from the prewhitened data. The paper also compares the results obtained from both prewhitened and non‐whitened data. The results show that the use of prewhitened data leads to a significant improvement in the estimation of the mixed‐phase wavelet when the data are severely band‐limited. The proposed algorithm was further tested on real data, followed by a test involving the introduction of a 90°‐phase‐rotated wavelet and then recovery of the wavelet. The test was successful.     

Fluid injection monitoring using electrical resistivity tomography — five years of injection at Ketzin,Germany

Between the years 2008 and 2013, approximately 67 kilotons of CO₂ have been injected at the Ketzin site, Germany. As part of the geophysical monitoring programme, time‐lapse electrical resistivity tomography has been applied using crosshole and surface‐downhole measurements of electrical resistivity tomography. The data collection of electrical resistivity tomography is partly based on electrodes that are permanently installed in three wells at the site (one injection well and two observation wells). Both types of ERT measurements consistently show the build‐up of a CO₂‐related resistivity signature near the injection point. Based on the imaged resistivity changes and a petrophysical model, CO₂ saturation levels are estimated. These CO₂ saturations are interpreted in conjunction with CO₂ saturations inferred from neutron‐gamma loggings. Apart from the CO₂–brine substitution response in the observed resistivity changes, significant imprints from the dynamic behaviour of the CO₂ in the reservoir are observed.     

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.     

Application of spectral decomposition and neural networks to characterise deep turbidite systems in the outer fold and thrust belt of the Niger Delta

We have applied a wavelet‐based spectral decomposition scheme and a multi‐layered feed‐forward neural network to interpret turbidite depositional systems from three‐dimensional reflection seismic data and well logs for a prospective hydrocarbon zone in the outer fold and thrust belt of the Niger Delta. The goal was to overcome difficulties in interpreting depositional systems from deep sections of the Field, occasioned by loss of seismic resolution with depth and the sparse distribution of wells. The decomposition scheme allowed us to delineate multiple depositional systems not apparent on the conventional seismic amplitude display. These systems include linear channel systems with terminal splay lobes, a sinuous channel system and its abandoned meander loops, and sediment wave features in overbank areas. Delineated channel morphologies and transport directions varied both laterally and vertically and were possibly dependent upon the disposition of the pre‐thrusting paleo‐seafloor. Terminal splay lobes are fragmented and coincident with the locations of topographic lows, which are possibly related to the initial configurations of the oceanic basement below. Predicted porosity and resistivity distributions have morphologies that correlate well with the mapping provided by the spectral decomposition scheme. The property distributions indicate that reservoir prone systems in the Field and possibly within the outer fold and thrust belt are composed primarily of channel systems, both linear and sinuous, and their associated splay lobes. The channel systems appear vertically stacked, and this situation possibly increases the potential success rate for exploration wells in the region. Beyond channel limits, redistributive bottom currents varying rapidly in speed and direction apparently encouraged the dispersal of sand‐rich sediments to form sediment waves. Despite the limited well control, the methodology significantly aided our interpretation. It proved effective at revealing the distribution of reservoir prone facies within the Field and provided insight into the dominant factors that controlled deposition within the Field.     

4D signal enhancement using singular-value decomposition: application to mapping oil–water contact movement across the Nelson Field

A new method for time‐lapse signal separation and enhancement using singular‐value decomposition is presented. Singular‐value decomposition is used to separate a 4D signal into its constituent parts: common geology, time‐lapse response and noise. Synthetic tests which demonstrate the advantages of the singular‐value decomposition technique over traditional differencing methods are also presented. This signal separation and enhancement technique is used to map out both the original and moved oil–water contacts across the Nelson Field. The singular‐value decomposition technique allows the oil–water contact to be mapped across regions which would have been missed using traditional differencing methods. In particular, areas toward the edges of the field are highlighted by the technique. The oil–water contact is observed to move upwards across the field, with the largest movements being associated, as anticipated, with natural production. The results obtained are broadly consistent with those predicted by the reservoir simulator model. Singular‐value decomposition is demonstrated to be a useful tool for enhancing the time‐lapse signal and for gaining confidence in areas where traditional differencing fails.     

Application of synchrosqueezed wavelet transforms to estimate the reservoir fluid mobility

This paper presents a new methodology for estimating reservoir fluid mobility using synchrosqueezed wavelet transforms. Synchrosqueezed wavelet transforms, which adopts a reassignment method, can improve the temporal and spatial resolutions of conventional time‐frequency transforms. The synchrosqueezed wavelet transforms‐based fluid mobility estimation requires the favourable selection of sensitive low‐frequency segment and more accurate estimation of the change rate of the low frequency segment in the spectrum. The least‐squares fitting method is employed in the synchrosqueezed wavelet transforms‐based fluid mobility estimation for improving the precision of the estimation of change rate of the low‐frequency segment in the spectrum. We validate our approach with a model test. Two field examples are used to illustrate that the fluid mobility estimation using the synchrosqueezed wavelet transforms‐based method gives a better reflection of fluid storage space and monitors hydrocarbon‐saturated reservoirs well.     

Localization and de-noising seismic signals on SASW measurement by wavelet transform

SASW method is a nondestructive in situ testing method that is used to determine the dynamic properties of soil sites and pavement systems. Phase information and dispersion characteristics of a wave propagating through these systems have a significant role in the processing of recorded data. Inversion of the dispersive phase data provides information on the variation of shear-wave velocity with depth. However, in the case of sanded residual soil, it is not easy to produce the reliable phase spectrum curve. Due to natural noises and other human intervention in surface wave date generation deal with to reliable phase spectrum curve for sanded residual soil turn into the complex issue for geological scientist. In this paper, a time–frequency analysis based on complex Gaussian Derivative wavelet was applied to detect and localize all the events that are not identifiable by conventional signal processing methods. Then, the performance of discrete wavelet transform (DWT) in noise reduction of these recorded seismic signals was evaluated. Furthermore, in particular the influence of the decomposition level choice was investigated on efficiency of this process. This method is developed by various wavelet thresholding techniques which provide many options for controllable de-noising at each level of signal decomposition. Also, it obviates the need for high computation time compare with continuous wavelet transform. According to the results, the proposed method is powerful to visualize the interested spectrum range of seismic signals and to de-noise at low level decomposition.