1,720,966 research outputs found
Inversion methods for the separation of blended data
No full textThe recording and storage capacity of modern seismic acquisition systems is continuously growing, enabling denser sampling and the acquisition of better-quality data. One big hurdle is survey time, since the duration of a survey is directly proportional to the number of sources fired. The proposed way forward is to deploy nearly simultaneous sources. Then, the acquired data are blended, i.e., the response to multiple sources is recorded in a single shot record. The objective of this thesis is to provide a method for the separation of blended data with a specific focus on the marine case. The result of this method will contain the response to only one source in every shot record, hence, the subsequent processing steps will not suffer from the interference noise caused by blending. In order to address this challenge, a firm mathematical formulation is required. Based on this formulation, the problem of separating blended data can be cast as a constrained optimisation problem. A constraint reflects the prior knowledge about the solution, in this case the separated data. The fundamental property of coherency is chosen as constraint and the problem can be solved with the aid of an iterative algorithm. A comparison of this algorithm with similar algorithms currently developed in the industry reveals that there are small but important theoretical and implementational differences. The leakage subspace, a mathematical notion inspired by the convergence analysis of this iterative algorithm, contains data that cannot be separated uniquely. This subspace can be computed prior to the acquisition of the data and establishes the link between acquisition parameters and separation efficiency. The separation method has been successfully applied to one of the few real 3D blended datasets currently available. Moreover, numerically blended datasets have been created based on unblended field data and then have been efficiently separated. Numerical blending gives us the freedom to utilize and study the method under different blending conditions. A well-known challenge in the processing of marine seismic data is the presence of strong surface-related multiples, i.e., up going energy from the subsurface that has been reflected at the surface and travels back into the subsurface. A field-data example showed that the separation algorithm, equipped with a surface-multiple prediction term, is able to suppress the surface-multiples while separating the blended data. Another approach is the use of a sparse inversion scheme for the same objective. This algorithm utilizes prior knowledge in terms of travel-time operators and provided excellent results when tested on simple numerical data. This thesis proposes a solution to the challenge of separating blended data. The added business value of such separation algorithms is significant for any exploration company since it can lead to a substantial reduction of the data acquisition cost.Geoscience & EngineeringCivil Engineering and Geoscience
Imaging velocity and attenuation scatterers with wave equation migration
No full textThe thesis deals with wave-equation migration in a visco-acoustic medium, where an ambiguity appears when one tries to image simultaneous velocity and attenuation perturbations.Department of GeotechnologyCivil Engineering and Geoscience
Electric characterization of layered sand and clay under continuous fluid flow conditions: Experiments and data analysis for frequencies between 100 kHz and 3 MHz
No full textAs geophysicists we are interested in the capabilities of electromagnetic methods for exploration, characterization, and monitoring of the subsurface. For frequencies below 1 MHz, the electromagnetic field is primarily diffusive, rendering the method very little resolving power. For this reason the resistivity values of layered structures cannot be resolved separately, but some average resistivity representing a stack of layers can be found from measured data. Diffusive electromagnetic methods find their application in discriminating large contrasts in electric conductivity values. These contrasts can occur between soil/rock and metallic inclusions or between the soil/rock mass and its pore fluid. In this thesis we are interested in the electromagnetic effects of the possibly strong contrast between the rocks or soils and the pore fluid. The electric response of fluid filled rocks and soils depends mainly on saturation level, porosity, the electric properties of the constituents, the pore fluid concentration, and pore geometry. In this thesis we try to improve our understanding of the effective electromagnetic response behavior of un-compacted sand, clay, and their layered mixtures. Measurements were conducted at frequencies from 100 kHz to 3 MHz during continuous inflow and outflow of water as a function of saturation level and pore water salinity using NaCl with concentrations of 1, 10, or 100 mmol/l. The effective electric conductivity is measured for homogeneous and layered sand and clay samples and layered combinations of sand and clay. The experimentally obtained macroscopic, frequency-dependent, and therefore complex-valued, electric conductivity is analyzed as a function of the various parameters. Initially, we used a much wider frequency range from 210 Hz to 3 MHz as offered by the measuring device, but due to strong electrode polarization in the two-electrode setup it was finally decided to restrict the analysis to the frequency band from 100 kHz to 3 MHz where we are sure no electrode polarization effect is present in the data. The procedures used to account for the electrode polarization effects are described in detail in Chapter 1. The electrode polarization cannot be calibrated for, but can be incorporated in the model increasing the number of unknown parameters. This is a viable option in principle, but leads to the uncertainty that errors in the electrode polarization model leads to unknown errors in the obtained effective conductivity values that cannot be identified as such. For this reason and to be more accurate it was decided to limit the frequency range from 100 kHz to 3 MHz. The objective of Chapter 2 is to determine whether the effect of heterogeneities at scales much smaller than the skin depth on a macroscopic electric measurement can be captured by introducing an effective frequency-dependent electrical resistivity that can be described by simple functions of macroscopic properties, such as porosity, water saturation, and salinity. For the experimental part of our study, we employed the two-electrode cell technique to measure the complex impedance over a broad frequency range, from 100 kHz up to 3 MHz. We conducted main drainage and secondary imbibition cycles at atmospheric pressure and temperatures between 21 ?C and 22 ?C. We found that the hysteretic effect, being the difference in the measured electric impedance between first drainage and second imbibition, is more pronounced for the homogeneous configurations than for the heterogeneous samples in the real part of the effective complex permittivity at higher concentrations of NaCl. Known effective medium theory for layered media works well for dry and fully saturated layered sand, when the NaCl solution concentration is 1 mmol/l. It fails for fully saturated layered sands at salinities of 10 mmol/l or more. Known effective medium models that are based on first principles are static limits or linearizations of non-linear behavior. When these linearizations are adequate descriptions of the effective behavior the models work well. At the salinity levels above 1 mmol/l, there appear to be measurable effects of effective non-linear behavior of the layered sands. To describe such behavior, new models need to be developed. The static effective medium theory does not work for partially saturated sands, independent of salinity, indicating that improved effective medium models should accommodate the water saturation dependence as well as frequency and salinity dependence. We introduce a special case of an existing five parameter model, which is a reduced form of the double Cole-Cole model, to describe the measured effective electric resistivity. This model very well fits the frequency-dependent complex electric resistivity data of homogeneous and layered unconsolidated sands during the drainage and the imbibition cycles under continuous flow conditions and the three different salinities used in these experiments. In Chapter 3, we investigate the effects of pore liquid salt concentration on the complex electric response of two different unconsolidated samples, layered sand and sand-clay, in the frequency range of 100 kHz to 3 MHz to study the effect of grain size on the effective response. The electric parameters that describe the electric response of the samples are obtained with the same two-electrode measurement cell as described in Chapter 2. Under continuous fluid flow conditions, first drainage and secondary imbibition cycles were conducted for the two different three-layered samples saturated with saline-water in three different NaCl solution concentrations at atmospheric pressure and temperatures between 21 ?C and 22 ?C. Analysis revealed that for a fixed frequency but varying water saturation the real part of electric permittivity increases with increasing salt concentration. For the highest NaCl solution concentration, the hysteretic effect becomes more pronounced and remains present at higher frequencies. For the two samples, plots of the conductivity amplitude and phase as a function of frequency show large variation with water saturation and NaCl solution concentrations, suggesting that this sensitivity is useful for environmental and geo-engineering characterization in vadose zone. Determining the five parameters in our model is numerically challenging, because it is a strongly non-linear and ill-posed inverse problem. The inversion has to be carried out for each water saturation level and each salt concentration level. It would be very beneficial to have a model that captures not only frequency dependence, but also water saturation dependence. Archie’s law is the best known candidate to do that. However, we found that Archie’s law cannot capture the variations in the complex resistivity with saturation, especially for samples with substantial fine-grain fractions. Archie’s law is valid for the real part of the complex resistivity and for samples with coarse-grain fractions. As an alternative, we propose a relaxation model. Its parameters vary exponentially with saturation. This model is inspired by the experimentally observed dependence on water saturation on all samples used in our tests. The relaxation model provides a good fit to the saturation dependence of our^ complex resistivity data and improves significantly on Archie’s classic law and is described in detail in Chapter 4. Measured electric responses of samples provide strong indications of changes in fluid saturation, salt concentration, and heterogeneity (here only layering). This makes it a promising technique for real time in-situ measurements. One application is in Enhanced Oil Recovery (EOR), where real-time monitoring of production-related changes is useful. Moreover, the results of our investigations could be applied to borehole logging data, because the frequency range and physical scale that we use are similar to those in borehole logging.GeotechnologyCivil Engineering and Geoscience
Deblending of seismic data
No full textSeismic imaging is one of the most common geophysical techniques for hydrocarbon exploration. Seismic acquisition is a trade-off between economy and quality. In conventional acquisition, the time intervals between successively firing sources are large enough to avoid interference in time. To obtain an efficient survey, the spatial source sampling is often (too) large, which results in spatial source aliasing. Simultaneous or blended acquisition was proposed by Beasley et al. (1998) and Berkhout (2008) in order to address this issue. In blended acquisition, temporal overlap between shot records is allowed. This additional degree of freedom in survey design has the potential to significantly reduce seismic acquisition costs while maintaining or even improving the data quality. Incoherent shooting plays a major role in the blended acquisition. It aims at preserving the energy distribution over the entire data bandwidth. There are several parameters that have to be considered in blended acquisition. Source encoding, lateral source configuration, blending factor, and survey condition are the most important parameters to be taken into account. These parameters are closely related and should not be considered irrespectively of each other. The acquired blended data can be processed in two ways: direct imaging and deblending. Deblending, which is the main focus of this thesis, is the procedure of retrieving the data as if they were acquired in the conventional, unblended way. After deblending the conventional, standard processing flows can be applied in practice. Since deblending is an underdetermined problem, a unique solution can not be achieved by matrix inversion. A least-squares solution could be used instead. However, the least-squares solution does not remove the interference due to other sources, called the blending noise. Fortunately, the character of the blending noise is different in different domains, i.e., it is coherent in the common source domain, but incoherent in the common receiver, common offset, and common midpoint domains. At the same time, the signal remains coherent in all domains. The incoherent character of the blending noise is directly related to the blended acquisition design. The coherence of the signal and the incoherence of the blending noise are the key properties that are used for deblending. In this thesis, an iterative inversion method is proposed for deblending, which is based on estimation and subtraction of the blending noise. In this method, the blending noise is modelled from the estimated signal and subtracted in an iterative fashion. The signal estimate is achieved by a process called coherencepass filtering, which consists of a filter in some domain followed by a thresholding step. At each iteration, the threshold is lowered and more of the blending noise is estimated and subsequently removed. Any type of filter that is capable of distinguishing between coherent signal and incoherent blending noise can be utilized in the coherence-pass filtering process. Three implementations of a coherence-pass filter, namely a median filter, an f-k filter, and a combined median-f-k filter are discussed. Among these, the combined median-f-k filter is a better choice due to the fact that it combines the median filter power in detecting blending noise with the f-k filter power in preserving the signal amplitude. The deblending process can be implemented in different data domains. The domain that is selected for deblending depends to a great extent on the blended acquisition design, acquisition geometry, and data properties. The algorithmic aspects of the deblending algorithm that are discussed in this thesis are related to the threshold automation, stopping criterion, filter edge artefacts, and signal estimation errors. The automation of the thresholding process that is based on the filter impact on the blending noise amplitude reduction, leads to a hands-off algorithm for deblending, optimized both for efficiency and effectiveness. The stopping criterion is based on a least-squares measure that is computed after each iteration. The deblending process is stopped when the measure reaches a stable state where no or negligible improvement is achieved. Furthermore, it is shown that one of the major limiting factors is related to edge artefacts generated by the filter. The blending noise that is estimated by the coherence-pass filtering is called the signal estimation error and is mainly caused by constructive or destructive interference of the blending noise with the signal. The effect of the signal estimation errors is evaluated by introducing errors in the coherence-pass filtering process. The result of this analysis shows that these signal estimation errors can be handled properly. The addressed practical considerations are mainly coherence and noise related issues. The incoherence in the signal is mainly caused by the irregularities in the acquisition geometry, near surface complexities, and topographic variations. Since coherence of the signal plays an essential role in deblending, the incoherence in the signal must be minimized prior to deblending. On the other hand, some of the noise-related issues can be handled during deblending. Proper handling of the practical issues is key to the success of the deblending process. The feasibility of the deblending algorithm is studied by applying it to three conventionally acquired datasets that are blended numerically. In the first example, 2D marine data are blended using upsweep and downsweep signals as source codes. Due to the favourable sophisticated source encoding, the deblending process can be performed per blended shot record using thresholding only, i.e., without blending noise filtering. In the second example, 2D land data are blended by time delays as source codes. In this case, the deblending process is performed in the common offset domain. Results are shown both for the data and their stack. In the last example, 3D land data are blended using two different blending configurations and their deblending results are compared. In this case the deblending process in performed in the common receiver domain. Overall, the obtained results are considered very promising.Geoscience & EngineeringCivil Engineering and Geoscience
Surface-wave separation and its impact on seismic survey design
No full textSurface waves in seismic data are often dominant and mask primaries in land or shallow-water environments. Separating them from the primaries is of great importance either for removing them as noise for reservoir imaging and characterization, or for considering them as signal for near-surface characterization. However, their complex properties, such as dispersion, multi-modality and spatial variability, make the surface-wave separation significantly challenging in processing. To address the challenges, we introduced a method of 3-D surface-wave estimation and separation using a closed-loop approach. The closed loop contains a relatively simple forward model of surface waves and adaptive subtraction of the forward-modelled surface waves from the observed surface waves, making it possible to evaluate the residual between them. In this approach, the surface-wave model is parameterized by the frequency-dependent slowness and source properties for each surface-wave mode. The optimal model parameters are estimated in an iterative way such that the residual is minimized and, consequently, this approach solves the inverse problem. Through synthetic and real data examples, we observed that this method successfully estimates and separates out the surface waves from the seismic data to consequently obtain the subsurface signals. We also observed the method's wide range of applicability to under-sampled, asymmetrically sampled, irregularly sampled and blended seismic data. This suggests the possibility of relaxing requirements for survey parameters in terms of surface-wave separation and, therefore, offers flexibility as well as potential effort reduction with respect to seismic surveys. Seismic survey design corresponds to choosing a set of survey parameters that enables imaging and amplitude-versus-offset applications of target reflectors with sufficient data quality under given economical and operational constraints. However, surface waves are often dominant in the seismic data, as already mentioned, and the effectiveness of surface-wave separation or removal significantly affects that of the subsequent steps for target reflectors. Therefore, they impose additional requirements on the survey parameters for acquisition so that those allow for effective surface-wave separation in processing. We should understand how the application of surface-wave separation affects the choice of survey parameters and the resulting data quality. For this purpose, we discussed the relationship between the survey parameters and the resulting data quality in order to find the essential types of survey parameters and their optimal values for a required data quality in the context of surface-wave separation. For 3-D seismic surveys, the relevant survey parameters are the four spatial sampling intervals and apertures of the template geometry. Two of the four spatial coordinates specify the spatial sampling of the basic subset, and two other coordinates specify the spatial redundancy of the basic subsets, i.e., the fold. The signal-to-noise ratio of the data sets after surface-wave separation serves as an attribute or measure representing the resulting data quality. We carried out a case study, applying surface-wave separation and signal-to-noise ratio estimation to several data sets with different survey parameters. The case study led us to conclude that the spatial sampling intervals of the basic subset are the essential types of survey parameters. The resulting data quality is related to the spatial sampling intervals and follows a trend curve, in which finer spatial sampling intervals improve the resulting data quality until it levels off on a plateau. The shape of this trend curve depends on the method of surface-wave separation. Given this impact of surface-wave separation on survey design, it should be included in the design, next to its intended application for reflection imaging or amplitude-versus-offset analysis. We then discussed the relationship between the survey parameters and the resulting data quality in the context of reflection imaging and amplitude-versus-offset applications. We also carried out a case study for this purpose using the so-called focal-beam method to several data sets with different survey parameters. Through the case study, we observed that the spatial sampling intervals and apertures of the basic subset are the essential types of survey parameters for reflection imaging, and that all the four spatial sampling intervals and apertures of the template geometry are essential for amplitude-versus-offset applications. A noteworthy conclusion is that suitable spatial sampling intervals for surface-wave separation also suffice for reflection imaging and amplitude-versus-offset applications. Therefore, for survey design, the spatial sampling intervals of the basic subset should be determined first for a required signal-to-noise ratio as needed for surface-wave separation. The other survey parameters should be considered next for a required resolution and pre-stack amplitude fidelity as required for reflection imaging and amplitude-versus-offset applications.Geoscience & EngineeringCivil Engineering and Geoscience
Correlation-based seismic velocity inversion
No full textMost of our knowledge of the subsurface comes from the measurement of quantities that are indirectly related to the earth’s structure. Examples are seismic waves, gravity and electromagnetic waves. We consider the use of seismic waves for inference of structural information on an exploration scale. The seismic waves are generated by placing sources at or near the surface and the response is measured with either geophones or hydrophones. From such data, valuable information on the earth’s structure may be inferred up to roughly 10 km depth with a resolution of 50 – 100 m. While such data where interpreted directly in the early days, present-day processing involve detailed mathematical description of wave propagation in terms of density and sound speeds. With the aid of such a mathematical description, the actual seismic experiment may be simulated on a computer. The parameters (density, sound speed) that best describe the subsurface can then be obtained by trying to match the observed data to the simulated data. Such a problem is called an inverse problem. A straightforward way to solve this is to try to fit the data in a least-squares sense. However, due to the specifics of the seismic experiment this only works well for parameters that govern the dynamics of the data. The kinematics are, however, also very important as these are sensitive to large scale velocity changes. To successfully invert the kinematics of the data, the inverse problem needs to be reformulated. In this thesis we investigate such a reformulation. The basic ingredient of this reformulation is the way the mismatch between the data are measured. Instead of subtracting the data – as in the least-squares approach – we infer the kinematic difference (the timeshift, basically) between the simulated and observed data via a weighted norm of the correlation. We discuss the application of this basic principle to both reflection and transmission data. We find that the weighted norm of the correlation is a robust way to measure the shift between complex waveforms and can be successfully applied to cross-well tomography and velocity inversion for horizontally layered media. Preliminary results for non-layered media suggest that the approach is applicable in this case as well.Applied Geophysics and PetrophysicsCivil Engineering and Geoscience
Controlled-Source Electromagnetics for Reservoir Monitoring on Land
Full text linkThe main goal of exploration geophysics is to obtain information about the subsurface that is not directly available from surface geological observations. The results are primarily used for finding potential reservoirs that contain commercial quantities of hydrocarbons. A number of possible geophysical methods exists these days to achieve such a goal. One of them is the controlled-source electromagnetic (CSEM) method. CSEM data can provide resistivity maps of the subsurface. Because the bulk resistivity depends on the resistivity of the pore fluid, these maps may enable us to estimate the nature of the fluid content in the reservoir. The CSEM method exploits electromagnetic fields to remotely characterize the nature of the fluid content in the pores. When a dipole current source is stuck into the ground or placed in the seawater, current flows from one pole to the other through the sediments, creating an electrical field in the subsurface. If highly resistive bodies are present in the subsurface, the electrical field measured at some distance from the source will be larger in amplitude than the field in the absence of these bodies. As hydrocarbon-bearing rock is highly resistive, one may link the larger amplitude to the presence of hydrocarbon reservoirs. A logical consequence of this phenomenon is that the CSEM method may also be suited for monitoring a hydrocarbon reservoir during production. The reason is that water flooding or steam injection for oil production creates resistivity changes in the reservoir, and if those changes are large enough, we can expect differences in the CSEM response with time-lapse surveys. This consideration led us to further investigate the EM monitoring problem. We tried to answer two questions: are the time-lapse changes in the reservoir detectable, particularly in the presence of noise, and if so, could we use timelapse signals to locate where the time-lapse changes happened in the subsurface? In this thesis, we considered land CSEM and found that the resistivity change due to displacement of oil by brine can produce a small but measurable difference in the CSEM response. Interestingly, those response differences at the surface are confined to the lateral extent of resistivity changes in the subsurface, even in the presence of various kinds of repeatability noise. We found a simple and effective method to remove the repeatability noise due to the airwave. Finally, results obtained when incorporating nonlinear EM inversion into the monitoring problem suggest that this application of the CSEM method has the potential to play a significant role in the oil and gas industry.Geoscience & EngineeringCivil Engineering and Geoscience
Elastic wavefield inversion by the alternating update method
No full textFull-waveform inversion is a promising tool for a wide range of imaging scenario, in that it has the potential to harness the non-linear relationship between model parameters and data (as opposed to traditional methodologies), in order to produce truly quantitative results. Non-linearity represents an opportunity, in this sense, but it also begets local minimum issues when gradientbased optimization is employed. In this thesis, we are particularly interested in the quantitative estimation of the elastic parameters of the earth, such as compressibility, shear modulus, and density. If successful, this procedure brings geophysical imaging closer to the ultimate step of seismic exploration: the retrieval of pore pressure and rock properties. This would be of direct use for, say, the oil and gas industry. Other interesting applications are the description of the near surface/near ocean bottom, as a way to reduce drilling hazards, or non-destructive inspection of defects in oil and gas pipes, when ultrasounds are employed.ImPhys/Quantitative Imagin
Inversion of seismic reflection data through focusing
No full textSince most of the easy hydrocarbon reservoirs have been found, accurate sub-surface imaging for oil and gas exploration and production is crucial. Seismic data can provide a band-limited reconstruction of impedance contrasts between different rock formations as well as a subsurface velocity model. Current compute power allows for the use of the full acoustic wave equation for seismic imaging and processing. Least-squares data fitting is an obvious approach but may provide the wrong answer because of local minima in the cost function caused by the absence of low frequencies in the data. An alternative formulation is based on extended images that invokes action at distance to make up for errors in the estimated subsurface velocity model. The action at distance is accomplished by a subsurface shift and the correct model should focus amplitudes at zero shift. The related cost function penalizes image amplitudes at non-zero shift. It has a large basin of attraction but loses its sharpness closer to the minimum. A new formulation is proposed – motivated by high-frequency asymptotic analysis – that provides better results on synthetic and real seismic data and is less sensitive to imaging artifacts.Geoscience & EngineeringCivil Engineering and Geoscience
A simple finite-difference scheme for handling topography with the second-order wave equation
No full textThe presence of topography poses a challenge for seismic modeling with finite-difference codes. The representation of topography by means of an air layer or vacuum often leads to a substantial loss of numerical accuracy. A suitable modification of the finite-difference weights near the free surface can decrease that error. An existing approach requires extrapolation of interior solution values to the exterior while using the boundary condition at the free surface. However, schemes of this type occasionally become unstable and may be impossible to implement with highly irregular topography. One-dimensional extrapolation along coordinate lines results in a simple and efficient scheme. The stability of the 1D scheme is improved by ignoring the interior point nearest to the boundary during extrapolation in case its distance to the boundary is less than half a grid spacing. The generalization of the 1D scheme to more than one dimension requires a modification if the boundary intersects the finite-difference stencil on both sides of the central evaluation point and if there are not enough interior points to build the finite-difference stencil. Examples for the 2D constant-density acoustic case with a fourth-order finite-difference scheme demonstrate the method's capability. Because the 1D assumption is not valid in two dimensions if the boundary does not follow grid lines, the formal numerical accuracy is not always obtained, but the method can handle highly irregular topography.</p
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