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- Volume 67, Issue 1, 2019
Geophysical Prospecting - Volume 67, Issue 1, 2019
Volume 67, Issue 1, 2019
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Review Paper: Post‐stack 4D seismic time‐shifts: Interpretation and evaluation
Authors Colin MacBeth, Maria‐Daphne Mangriotis and Hamed AminiABSTRACTA review and analysis of post‐stack time‐lapse time‐shifts has been carried out that covers published literature supplemented by in‐house datasets available to the authors. Time‐shift data are classified into those originating from geomechanical effects and those due to fluid saturation changes. From these data, conclusions are drawn regarding the effectiveness of post‐stack time‐shifts for overburden and reservoir monitoring purposes. A variety of field examples are shown that display the range and magnitude of variation for each class of application. The underlying physical mechanisms creating these time‐shifts are then described, and linked to a series of generic and field‐specific rock physics calculations that predict their magnitudes. These calculations serve as a guide for practitioners wishing to utilize this information on their own datasets. Conclusions are drawn regarding the reliability of this attribute for monitoring purposes, and the extent to which further development is required and how it should be reported by authors.
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Acoustic directional snapshot wavefield decomposition
Authors Max Holicki, Guy Drijkoningen and Kees WapenaarABSTRACTUp–down wavefield decomposition is effectuated by a scaled addition or subtraction of the pressure and vertical particle velocity, generally on horizontal or vertical surfaces, and works well for data given on such surfaces. The method, however, is not applicable to decomposing a wavefield when it is given at one instance in time, i.e. on snapshots. Such situations occur when a wavefield is modelled with methods like finite‐difference techniques, for the purpose of, for example, reverse time migration, where the entire wavefield is determined per time instance. We present an alternative decomposition method that is exact when working on snapshots of an acoustic wavefield in a homogeneous medium, but can easily be approximated to heterogeneous media, and allows the wavefield to be decomposed in arbitrary directions. Such a directional snapshot wavefield decomposition is achieved by recasting the acoustic system in terms of the time derivative of the pressure and the vertical particle velocity, as opposed to the vertical derivative in up–down decomposition for data given on a horizontal surface. As in up–down decomposition of data given at a horizontal surface, the system can be eigenvalue decomposed and the inverse of the eigenvector matrix decomposes the wavefield snapshot into fields of opposite directions, including up–down decomposition. As the vertical particle velocity can be rotated at will, this allows for decomposition of the wavefield into any spatial direction; even spatially varying directions are possible. We show the power and effectiveness of the method by synthetic examples and models of increasing complexity.
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Stretch‐free generalized normal moveout correction
Authors Jorge H. Faccipieri, Tiago A. Coimbra and Rodrigo BlootABSTRACTThe effective application of normal moveout correction processes mainly depends on four factors: the chosen traveltime approximation, the stretching associated with the given traveltime, crossing events and phase changes, the last two being inherent to the seismic data. In this context, we conduct a quantitative analysis on stretching considering a general traveltime expression depending on half‐offset and midpoint coordinates. Through this analysis, we propose a mathematically proven procedure to eliminate stretching, which can be applied to any traveltime approximation. The proposed method is applied to synthetic and real data sets, considering different traveltime approximations and achieved complete elimination of stretching.
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Target‐level waveform inversion: a prospective application of the convolution‐type representation for the acoustic wavefield
More LessABSTRACTNowadays, full‐waveform inversion, based on fitting the measured surface data with modelled data, has become the preferred approach to recover detailed physical parameters from the subsurface. However, its application is computationally expensive for large inversion domains. Furthermore, when the subsurface has a complex geological setting, the inversion process requires an appropriate pre‐conditioning scheme to retrieve the medium parameters for the desired target area in a reliable manner. One way of dealing with both aspects is by waveform inversion schemes in a target‐oriented fashion. Therefore, we propose a prospective application of the convolution‐type representation for the acoustic wavefield in the frequency–space domain formulated as a target‐oriented waveform inversion method. Our approach aims at matching the observed and modelled upgoing wavefields at a target depth level in the subsurface, where the seismic wavefields, generated by sources distributed above this level, are available. The forward modelling is performed by combining the convolution‐type representation for the acoustic wavefield with solving the two‐way acoustic wave‐equation in the frequency–space domain for the target area. We evaluate the effectiveness of our inversion method by comparing it with the full‐domain full‐waveform inversion process through some numerical examples using synthetic data from a horizontal well acquisition geometry, where the sources are located at the surface and the receivers are located along a horizontal well at the target level. Our proposed inversion method requires less computational effort and, for this particular acquisition, it has proven to provide more accurate estimates of the target zone below a complex overburden compared to both full‐domain full‐waveform inversion process and local full‐waveform inversion after applying interferometry by multidimensional deconvolution to get local‐impulse responses.
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First‐break picking for microseismic data based on cascading use of Shearlet and Stockwell transforms
Authors Yao Cheng, Yue Li and Chao ZhangABSTRACTFirst‐break picking of microseismic data is a significant step in microseismic monitoring. There is a great error in conventional first‐break picking methods based on time domain analysis in low signal to noise ratio. S‐transform may provide a novel approach, it can extract the time–frequency features of the signal and reduce the picking error because of its high time–frequency resolution and good time–frequency clustering; however, the S‐transform is not well suited for microseismic data with high noise. For applications to array data where the weak signal has spatial coherency as well as some distinct temporal characteristics, we propose to combine the shearlet transform with a time–frequency transform. In the proposed method, the shearlet transform is used to capture spatial coherency features of the signal. The information of the signal and noise in shearlet domain is represented by shearlet coefficients. We use the correlation of signal coefficients at adjacent fine scales to give prominence to signal features to accurately discriminate the signal from noise. The prominent signal coefficients make the signal better gathered in time–frequency spectrum of the S‐transform. Finally, we can get reliable and accurate first breaks based on the change of energy. The performance of the proposed method was tested on synthetic and field microseismic data. The experimental results indicated that our method is outstanding in terms of both picking precision and adaptability to noise.
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A five component land seismic sensor for measuring lateral gradients of the wavefield
Authors Everhard Muyzert, Nihed Allouche, Pascal Edme and Nicolas GoujonABSTRACTWe built a five‐component (5C) land seismic sensor that measures both the three‐component (3C) particle acceleration and two vertical gradients of the horizontal wavefield through a pair of 3C microelectromechanical accelerometers. The sensor is a small cylindrical device planted vertically just below the earth's surface. We show that seismic acquisition and processing 5C sensor data has the potential to replace conventional seismic acquisition with analogue geophone groups by single 5C sensors placed at the same station interval when combined with a suitable aliased ground roll attenuation algorithm. The 5C sensor, therefore, allows for sparser, more efficient, data acquisition.
The accuracy of the 5C sensor wavefield gradients depends on the 3C accelerometers, their sensitivity, self‐noise and their separation. These sensor component specifications are derived from various modelling studies. The design principles of the 5C sensor are validated using test data from purpose‐built prototypes. The final prototype was constructed with a pair of 3C accelerometers separated by 20 cm and with a self‐noise of 35 ng Hz−1/2.
Results from a two‐dimensional seismic line show that the seismic image of 5C sensor data with ground roll attenuated using 5C sensor gradient data was comparable to simulated analogue group data as is the standard in the industry. This field example shows that up to three times aliased ground roll was attenuated. The 5C sensor also allows for correcting vertical component accelerometer data for sensor tilt. It is shown that a vertical component sensor that is misaligned with the vertical direction by 10° introduces an error in the seismic data of around –20 dB with respect to the seismic signal, which can be fully corrected. Advances in sensor specifications and processing algorithms are expected to lead to even more effective ground roll attenuation, enabling a reduction in the receiver density resulting in a smaller number of sensors that must be deployed and, therefore, improving the operational efficiency while maintaining image quality.
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Acoustic and petrophysical properties of mechanically compacted overconsolidated sands: Part 2 – Rock physics modelling and applications
Authors Sirikarn Narongsirikul, Nazmul Haque Mondol and Jens JahrenABSTRACTPart one of this paper reported results from experimental compaction measurements of unconsolidated natural sand samples with different mineralogical compositions and textures. The experimental setup was designed with several cycles of stress loading and unloading applied to the samples. The setup was aimed to simulate a stress condition where sediments underwent episodes of compaction, uplift and erosion. P‐wave and S‐wave velocities and corresponding petrophysical (porosity and density) properties were reported. In this second part of the paper, rock physics modelling utilizing existing rock physics models to evaluate the model validity for measured data from part one were presented. The results show that a friable sand model, which was established for normally compacted sediments is also capable of describing overconsolidated sediments. The velocity–porosity data plotted along the friable sand lines not only describe sorting deterioration, as has been traditionally explained by other studies, but also variations in pre‐consolidation stress or degree of stress release. The deviation of the overconsolidated sands away from the normal compaction trend on the VP/VS and acoustic impedance space shows that various stress paths can be predicted on this domain when utilizing rock physics templates. Fluid saturation sensitivity is found to be lower in overconsolidated sands compared to normally consolidated sands. The sensitivity decreases with increasing pre‐consolidation stress. This means detectability for four‐dimensional fluid saturation changes can be affected if sediments were pre‐stressed and unloaded. Well log data from the Barents Sea show similar patterns to the experimental sand data. The findings allow the development of better rock physics diagnostics of unloaded sediments, and the understanding of expected 4D seismic response during time‐lapse seismic monitoring of uplifted basins. The studied outcomes also reveal an insight into the friable sand model that its diagnostic value is not only for describing sorting microtextures, but also pre‐consolidation stress history. The outcome extends the model application for pre‐consolidation stress estimation, for any unconsolidated sands experiencing similar unloading stress conditions to this study.
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Relations between static and dynamic moduli of sedimentary rocks
By Erling FjærABSTRACTStatic moduli of rocks are usually different from the corresponding dynamic moduli. The ratio between them is generally complex and depends on several conditions, including stress state and stress history. Different drainage conditions, dispersion (often associated with pore fluid effects), heterogeneities and strain amplitude, are all potential reasons for this discrepancy. Moreover, comparison of static and dynamic moduli is often hampered and maybe mistaken due to insufficient characterization of anisotropy.
This paper gives a review of the various mechanisms causing differences between static and dynamic moduli. By careful arrangements of test conditions, it is possible to isolate the mechanisms so that they can be studied separately. Non‐elastic deformation induced by the large static strain amplitudes is particularly challenging, however a linear relationship between non‐elastic compliance and stress makes it possible to eliminate also this effect by extrapolation to zero strain amplitude.
To a large extent, each mechanism can be expressed mathematically with reasonable precision, thus quantitative relations between the moduli can be established. This provides useful tools for analyses and prediction of rock behaviour. For instance, such relations may be used to predict static stiffness and even strength based on dynamic measurements. This is particularly useful in field situations where only dynamic data are available. Further, by utilizing the possibility for extrapolation of static measurements to zero strain amplitude, dispersion in the range from seismic to ultrasonic frequencies may be studied by a combination of static and dynamic measurements.
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A new fluid factor and its application using a deep learning approach
More LessABSTRACTAmplitude interpretation for hydrocarbon prediction is an important task in the oil and gas industry. Seismic amplitude is dominated by porosity, the volume of clay, pore‐filled fluid type and lithology. A few seismic attributes are proposed to predict the existence of hydrocarbon. This paper proposes a new fluid factor by adding a correct item based on the J attribute. The algorithm is verified through stochastic Monte Carlo modelling that contains various rock physical properties of sand and shale. Both gas and oil responses are separated by the new fluid factor. Furthermore, an approach based on the neural network model is trained using the deep learning method to predict the new fluid factor. The confusion matrix shows that this model performs well. This model allows the application of the new fluid factor in the seismic data. In this study, the Marmousi II data set is used to examine the performance of the new fluid factor, and the result is good. Most hydrocarbon reservoirs are identified in the shale–sandstone sequences. The combination of deep learning and the new fluid factor provides a more accurate way for hydrocarbon prediction.
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Quantification and spatial distribution of pore‐filling materials through constrained rock physics template and fluid response modelling in Paleogene clastic reservoir from Cauvery basin, India
ABSTRACTSands belonging to Kamalapuram Formation of Paleocene‐Eocene age are deposited in Cauvery basin as incised valley fill during a regressive cycle. Here we attempt to quantify the influence of diagenesis on pore‐filling materials using rock physics template constrained by geohistory modelling. Primarily, porosity–velocity and acoustic impedance – the ratio of P‐wave and S‐wave velocity (VP/Vs) cross‐plots are used as rock physics templates. Rock physics template has efficiently quantified pore‐filling materials namely; contact cement and non‐contact cement. The estimated contact cement and non‐contact cement are correlated with conventional petrophysical logs within the selected depth interval. Further, this correlation is used to interpret the composition of pore‐filling materials. Shallower depth intervals (I and II) exhibit moderate non‐contact cement (4–5%) and insignificant contact cement (1–2% approx.) depositions. However, deeper interval (III) records a significant amount of pore‐filling materials amounting average of 12% non‐contact cement and 4% contact cement. Pore‐filling materials demonstrate a positive correlation with the depth of burial. The fluid response is substantially affected by the degree of diagenesis, composition and spatial distribution of pore‐filling materials. Shallower depth intervals (1770–1786 m and 1858–1878 m) are relatively more sensitive to fluid changes as it is affected by insignificant contact cement. The depth interval 1770–1786 m shows class II (oil) and class III (gas) amplitude variation with offset anomalies. The sand occurring in depth interval 1858–1878 m demonstrates class IIP (oil) and II (gas) anomaly. The deeper interval (2118–2170 m) is comparatively stiffer and demonstrates class I amplitude variation with offset (oil and gas sand) anomaly.
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Quantitative integration of 3D and 4D seismic impedance into reservoir simulation model updating in the Norne Field
Authors Masoud Maleki, Alessandra Davolio and Denis José SchiozerABSTRACTThe ultimate goal of reservoir simulation in reservoir surveillance technology is to estimate long‐term production forecasting and to plan development and management of petroleum fields. However, maintaining reliable reservoir models which honour available static and dynamic data, involve inherent risks due to the uncertainties in space and time of the distribution of hydrocarbons inside reservoirs. Recent applications have shown that these uncertainties can be reduced by quantitative integration of seismic data into the reservoir modelling workflows to identify which areas and reservoir attributes of the model should be updated. This work aims using seismic data to reduce ambiguity in calibrating reservoir flow simulation model with an uncertain petro‐elastic model, proposing a circular workflow of inverted seismic impedance (3D and 4D) and engineering studies, with emphasis on the interface between static and dynamic models. The main contribution is to develop an updating procedure for adjusting reservoir simulation response before using it in the production forecasting and enhance the interpretive capability of reservoir properties. Accordingly, the workflow evaluates consistency of reservoir simulation model and inverted seismic impedance, assisted by production history data, to close the loop between reservoir engineering and seismic domains. The methodology is evaluated in a complex, faulted, sandstone reservoir, the Norne benchmark field, where a significant reservoir behaviour understanding (about the static and dynamic reservoir properties) is obtained towards the quantitative integration of seismic impedance data. This leads to diagnosis of the reservoir flow simulation reliability and generation of an updated simulation model consistent with observed seismic and well production history data, as well as a calibrated petro‐elastic model. Furthermore, as Norne Field is a benchmark case, this study can be considered to enrich the discussions over deterministic or probabilistic history matching studies.
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Review Paper: Historical development of the total normalized gradient method in profile gravity field interpretation
Authors I.S. Elysseieva and R. PaštekaABSTRACTIn the Russian school, the total normalized gradient method belongs to the most wide‐spread of direct interpretation methods for potential field data. This method was also used and partly developed by many experts from abroad. The main advantage of the total normalized gradient method is its relative independence of parameters such as the expected differential density of interpreted structures. The method is built from a construction of a specially transformed field (total normalized gradient) on a section crossing the potential field sources. The special properties of this transformed field allow it to be used to detect the source positions. From the 1960s, the mathematical basis of the method underwent enormous development and several modifications of the method have been elaborated. The total normalized gradient operator itself represents a relatively complicated, non‐linear band‐pass filter in the spectral domain. The properties of this operator can be handled by means of several parameters that act to separate the information about field sources at different depth levels. In this contribution, we describe the development of the method from its very beginning (based mostly on qualitative interpretation of simple total normalized gradient sections) through to more recent numerical improvements to the method. These improvements include the quasi‐singular points method, which refines the filter properties of the total normalized gradient operator and defines an objective criteria (so called criterion ‘α’ and ‘Г') for the definition of source depths in the section. We end by describing possibilities for further development of the method in the future.
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Multi‐frequency electromagnetic method for inductive measurement of ground induced polarization and resistivity
ABSTRACTA geophysical electromagnetic method to inductively measure the ground electrical resistivity and induced polarization has recently been tested. Its basic characteristics involve three major differences from other methods: the two electrical ground parameters are obtained through measuring magnetic field. For this purpose, a transmitter–receiver (T, R) electromagnetic system is used that operates in the frequency domain and consists of a horizontal loop as the transmitter for the perpendicular loops configuration on the ground surface; the measured function is the (T, R) inductive coupling main variation produced due to the presence of the earth, that is the magnetic field radial component; the measurements are conducted at a large number of frequencies (139 in the more advanced prototype), and the measured function is explored in the frequency interval 0.2 Hz to 1 kHz, a much broader frequency range of the induced polarization effect spectrum, than the one conventionally used in field exploration. Three major aspects are emphasized: (1) the existence of a small ‘main zone’ interior to a half‐space, which is responsible for most of the magnetic energy that the receiver measures on the half‐space surface. This permits to substitute the entire half‐space by the ‘main zone’ and, in a second step, to substitute the ‘main zone’ by an equivalent homogeneous half‐space with the electrical characteristics of such ‘main zone’; (2) the existence of a closed solution for the fields that the (T, R) system generates on the surface of a homogeneous isotropic half‐space, which provides exact functions with the two electrical parameters of interest as the variables (the apparent resistivity and relative polarization parameter); (3) the values of the electrical parameters so determined can be attributed to the central point of the ‘main zone’. Three‐horizontal layers half‐space and a conductive sphere in the free‐space are discussed as models. Four field surveys are analysed as examples and show a satisfactory performance of the method for detection of on‐shore hydrocarbon reservoirs, description of induced reservoir variations and structural features mapping at depths up to 2.5 km.
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Three‐dimensional inversion of full magnetic gradient tensor data based on hybrid regularization method
Authors Shuangxi Ji, Huai Zhang, Yanfei Wang, Liangliang Rong, Yaolin Shi and Yongshun ChenABSTRACTRapid developments in SQUID‐based technology make it possible for geophysical exploration to direct measure, inverse and interpret magnetic gradient tensor data. This contribution introduces a novel three‐dimensional hybrid regularization method for inversion of magnetic gradient tensor data, which is based on the minimum support functional and total variation functional. Compared to the existing stabilizers, for example, the minimum support stabilizer, the minimum gradient support stabilizer or the total variation stabilizer, our proposed hybrid stabilizer, in association with boundary penalization, improves the revision result greatly, including higher spatial and depth resolution, more clear boundaries, more highlighted images and more evident structure depiction. Moreover, suitable selection of model parameter λ will further improve the image quality of the recovered model. We verify our proposed hybrid method with various synthetic magnetic models. Experiment results prove that this method gives more accurate results, exhibiting advantages of less computational costs even when less prior information of magnetic sources are provided. Comparison of results with different types of magnetic data with and without remanence indicates that our inversion algorithm can obtain more detailed information on the source structure based on rational estimation of total magnetization direction. Finally, we present a case study for inverting SQUID‐based magnetic tensor data acquired at Da Hinggan Mountains area, inner Mongolia, China. The result also certifies that the method is reliable and efficient for real cases.
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