Orthogonal contribution summation to build 3D internal multiple models

Internal multiple adaptive subtraction using Huber norm

Incorrect imaging of internal multiples can lead to substantial imaging artifacts. It is estimated that most seismic images available to exploration and production companies have had no direct attempt at internal multiple removal. Previously, we have considered the role of sparsity promoting transforms for improving practical prediction quality for algorithms derived from the inverse scattering series (ISS). Furthermore, we have developed a demigration-migration approach to perform multidimensional internal multiple prediction with migrated data and provided a synthetic proof of concept. Now, we consider application of the demigration-migration approach to field data from the Norwegian Sea and compare it to a poststack method (from a previous related work). Beyond application to a wider range of data with our approach, we consider algorithmic and implementational optimizations of the ISS prediction algorithms to further improve the applicability of the multidimensional formulations.

Linear inversion is defined as the linear approximation of a direct-inverse solution. This definition leads to data requirements and specific direct-inverse algorithms, which differ with all current linear and nonlinear approaches, and is immediately relevant for target identification and inversion in an elastic earth. Common practice typically starts with a direct forward or modeling expression and seeks to solve a forward equation in an inverse sense. Attempting to solve a direct forward problem in an inverse sense is not the same as solving an inverse problem directly. Distinctions include differences in algorithms, in the need for a priori information, and in data requirements. The simplest and most accessible examples are the direct-inversion tasks, derived from the inverse scattering series (ISS), for the removal of free-surface and internal multiples. The ISS multiple-removal algorithms require no subsurface information, and they are independent of earth model type. A direct forward method solved in an inverse sense, for modeling and subtracting multiples, would require accurate knowledge of every detail of the subsurface the multiple has experienced. In addition, it requires a different modeling and subtraction algorithm for each different earth-model type. The ISS methods for direct removal of multiples are not a forward problem solved in an inverse sense. Similarly, the direct elastic inversion provided by the ISS is not a modeling formula for PP data solved in an inverse sense. Direct elastic inversion calls for PP, PS, SS, … data, for direct linear and nonlinear estimates of changes in mechanical properties. In practice, a judicious combination of direct and indirect methods are called upon for effective field data application.

Due to shale-carbonate alternating successions with a gentle structure, primary reflections are severely interfered by various orders of strong and complex internal multiples from the overburden to reservoir levels in carbonate fields in the Middle East. These factors make the existing techniques ineffective, and still pose various geophysical challenges. This study aims to demonstrate an innovative scheme to eliminate internal multiples based on the Marchenko equation, originated from a basis of the inverse scattering theory. The extension of the Marchenko equation to surface seismic data enables a retrieval of upgoing and downgoing Green’s functions between a virtual source in a given subsurface location and receivers at the surface. Such a key feature in the Marchenko method is capable of identifying and/or eliminating internal multiples in a data-driven fashion, without the need for explicit subsurface models or numerical modelling. The technique estimates all the downgoing reflections from the overburden level, interfering primaries in the target level as internal multiples, which are subsequently subtracted from the input data to derive internal-multiple free data. To thoroughly assess the value of the Marchenko method, a numerical study was conducted. The realistic earth model that incorporates subsurface contexts in a carbonate field in the Middle East was derived to generate synthetic data through finite-difference modelling. The Marchenko-based internal multiple elimination was applied to synthesized data followed by reverse time migration. As true subsurface responses are known here, this trial properly revealed the effectiveness of the algorithm. For a comparison purpose, we also performed another processing flow using conventional internal multiple elimination that makes use of periodicity and velocity discrimination. The Marchenko scheme successfully estimates various types of internal multiples, such as over- and under-corrected multiples and even flat internal multiples, regardless of their periodicities, at once. Despite its ability to effectively suppress internal multiples, the final imaging results indicate that underlaying primary events are still preserved. The technique also leads to notable improvements in the imaging quality as compared to conventional processing flow. In addition to the effectiveness of the Marchenko method, we also describe a dedicated workflow adapted in this study to deal with strong and complex internal multiples. The unique advantage of the Marchenko scheme over existing approaches is its ability to predict internal multiples in a data-driven manner without precisely specifying multiple generators, assuming behaviors of internal multiples, or requiring prior knowledge of subsurface context. The Marchenko method can be also implemented for various ways such as redatuming, target oriented imaging and velocity estimation, source inversion problem, passive seismic, and electromagnetic, which will certainly provide several aspects of additional value.

Breakthrough and significance of technology on internal multiple recognition and suppression: A case study of Sinian Dengying Formation in Central Sichuan Basin, SW China

Multiples are a key problem over the Clair area, mainly caused by the complexity in the overburden. The paper describes a much improved combination of demultiples techniques, which have been applied to the latest Clair South West HDOBC survey. The sequence consists a top-down approach removing successive multiples with PZ summation, Wavefield Extrapolation Multiples Modeling, GSMP and TauPQ deconvolution. Water bottom WEMM plays a key role, effectively predicting water layer multiples in a 3D sense. GSMP complements the results of the other techniques against short period multiples, but more importantly it also predicts other long period surface multiples which are cutting through at reservoir level. The results are a much improved level of multiples suppression, although some surface multiples contamination is still present, and internal multiples have not been attenuated.

This article, written by Special Publications Editor Adam Wilson, contains highlights of paper IPTC 18293, “Near-Surface Velocity Model of Dukhan Field From Multiphysics Survey To Enhance PSDM Seismic Imaging,” by K. Setiyono, Qatar Petroleum; S. Gallo, C. Boulanger, F. Bruere, F. Moreau, and B. Rondeleux, CGG; and J. Snow, Qatar Petroleum, prepared for the 2015 International Petroleum Technology Conference, Doha, Qatar, 7-9 December. The paper has not been peer reviewed. Dukhan field affords an opportunity to assess alternative near-surface velocity-modeling work flows that specifically integrate microgravity (MGR) and vertical electrical sounding (VES). A pilot study of the Dukhan seismic data demonstrates that integration of MGR/VES into prestack depth migration (PSDM) improves the fidelity of seismic images and results in an improved depth match. The resultant MGR/VES PSDM pilot model improved the velocity model between the surface and top Simsima formation on the basis of visible impact on the deeper structure obtained from imaging and better fit between the seismic depth horizons and well measured depths. Introduction The Dukhan field (Fig. 1) along the southwest coast of Qatar is an elongated anticline that has significant hydrocarbon reservoirs in the Jurassic Arab and deeper formations. In 2007, Qatar Petroleum invested in a new full-field, land and shallow-water 3D-seismic survey of the area. Despite considerable and continuous progress in seismic technology, obtaining an accurate, quantitative, well-focused seismic depth image at reservoir level remains challenging. In land seismic, a poor characterization of the near-surface geology is detrimental to the depth imaging of underlying structures. The proper knowledge of the near surface to correct for its perturbations onto the seismic wavefield remains one of the main challenges to be addressed. The near surface influences the kinematics as well as the dynamics of the source-generated seismic waves. Knowledge of the near surface to correct for its induced distortions is critical for a reliable use of seismic images, structures, and amplitude at reservoir level. The near-surface lateral and vertical velocity variations often are not accessible with seismic methods, even to the seismic refraction survey, because their depth of investigation is limited to the top of the shallowest hard layer. In addition, rapid lateral changes and large velocity contrasts are unfavorable to seismic refraction.

Three-dimensional human face modeling is a very popular topic with many applications,such as facial animation, face recognition and model-based facial video communication. Therefore, how to model the facial geometry, texture intensity and illumination variation is important in computer vision and graphics. Previous works on 3D head modeling from a single face image utilized prior information on 3D head models. However, it is difficult to accurately reconstruct the 3D face model from a single face image with expression since the facial expression induces 3D face model deformation in a complex manner. The main challenge is the coupling of the neutral 3D face model and the 3D deformation due to expression, thus making the 3D model estimation from a single face image with expression very challenging. On the other hand, the illumination condition also makes the problem more difficult. In this thesis,we focus on developing a 3D face model reconstruction system including surface registration and training of 3D face models with expressional deformations as well as the estimation of the 3D neutral shape and the 3D expressional deformation from a single face image. The proposed reconstruction algorithm integrates the linear and non-linear subspace representations for a prior 3D neutral morphable model and the probabilistic manifold-based 3D expressional deformation. We incorporate the face geometry, expression deformation, texture and illumination information into the problem so that it is well constrained. The reconstructed 3D face models can also be further extended and applied to many real-world applications.

Quasi‐static elastic dislocations in a homogeneous elastic half‐space are commonly used to model earthquake faulting processes. Recent studies of the 1989 Kalapana, Hawaii, and Loma Prieta, California, earthquakes suggest that spatial variations in elastic properties are necessary to reconcile geodetic and seismic results (Arnadottir et al., 1991; Eberhart‐Phillips and Stuart, 1992). In this paper, we use a moduli perturbation approach to investigate the effect of lateral and vertical variations in elastic properties on the elastic fields produced by dislocations. The method is simple, efficient, and in some cases leads to closed form solutions. The zero‐order solution is simply the solution for a homogeneous body. The first‐order correction for elastic heterogeneity is given by a volume integral involving the spatial variations in moduli, the displacements due to a dislocation in a homogeneous half‐space, and the half‐space Green's function. The same representation can be also used to obtain higher‐order solutions. If there are only piecewise constant variations in shear modulus, the volume integral can be reduced to a surface integral (or line integral in two‐dimensions). Comparisons with the analytical solutions for a screw dislocation in a layered medium suggest that the perturbation solutions are valid for nearly an order of magnitude variation in modulus. It is shown that a simple two‐dimensional model with both vertical and lateral variations in the elastic properties may explain a large part of the discrepancy between seismic and geodetically inferred fault depths for the 1989 Kalapana, Hawaii, earthquake.

Well abandonment in the context of CO2 storage operations demands a mitigation strategy for CO2 leakage along the wellbore. To prevent possible CO2 transport toward the surface and to protect the wellbore material from contact with acid brine, we propose forming a salt seal around the wellbore at reservoir level, after CO2 injection into a depleted gas field. The mechanism of water evaporation into dry gas and subsequent salting‐out of the dissolved halite is a well‐known issue in hydrocarbon production. We propose alternating injection of brine and CO2 to facilitate intentional salt clogging of the reservoir. Salt clogging was studied with TOUGH2, simu‐lating multiple cycles of brine and CO2 injection. We developed two near‐well reservoir models – a homogeneous 2D model and a more complex heterogeneous 2D model – using certain characteristics of the K12‐B depleted gas field. The homogeneous 2D model yields a 50‐cm thick salt bank around the well and complete permeability impairment after eight cycles of brine‐CO2 injection. Addition of vertical permeability heterogeneities causes variation in the lateral extent of salt precipitation and hence vertical discontinuities in the salt bank. A carefully designed injection strategy – with more injection cycles and lower injection rates – improves the vertical sealing. Predictions of the amount of required clogging for effective sealing would benefit from more accurate porosity‐permeability relationships and insights in the long‐term stability of the salt bank regarding re‐dissolution. We conclude that alternating brine‐CO2 injection could be a promising method for intentional salt‐clogging of the near‐wellbore area. © 2013 Society of Chemical Industry and John Wiley & Sons, Ltd

Reservoirs are highly relevant infrastructure assets, and now, more than ever, they play an essential role in society’s welfare and national security. Their importance is related to regional socioeconomic development due to their capacity to store water for different uses, such as human consumption, agricultural irrigation, flood control, and hydroelectric energy production, among other important services. However, many reservoirs are reaching the end of their period of life, and others are showing undesired displacements and cracking. Four 3D surveys were conducted on a reservoir that serves the Metropolitan Area of Monterrey City in Mexico. These surveys were carried out over a period of 5 years using GNSS observation to assist in understanding the actual dam kinematics, i.e., the behavior of its longitudinal and transversal displacements and the possible correlation with the reservoir level. The high‐precision leveling and close‐range remote sensing data were assessed and then mapped. The high‐precision geodetic and leveling techniques allowed us to locate and measure 84 established permanent control points with errors of about ± 0.003 m. The mapping of displacements was made possible by modeling the positive and negative translations. The highest uplifts (11 mm) occurred at the left riverbank, and the highest subsidences (−5 mm) occurred along the downstream piers from the middle of the dam crest to the right riverbank. A ground laser scanner (GLS) produced 3D digital models with geometrical and radiometric characteristics, detecting displacements among the dam crest elements. The synergy of GNSS and high‐leveling techniques allows the possibility to measure displacements, while the use of geographical information system (GIS) and geomatic techniques allows a better visualization through 2D and 3D maps validated using traditional topographical methods.

This paper develops a Bayesian inverse modelling framework for the in-situ characterisation of walls' thermal performance in the presence of thermal anomalies subject to uncertainty. For any given wall, the proposed framework uses in-situ contact measurements of temperature and heat flux in order to approximate the (posterior) distribution of a set of parameters which are inputs of a 3D heat transfer model of the wall that accounts for the presence of unknown anomalies. The set of inputs that we infer include (i) the geometry of the thermal anomaly as well was its material properties, (ii) the as-built thermophysical properties of the clear part (i.e. without anomaly) of the wall (iii) surface resistances and (iv) modelling errors that arise from unaccounted sources of uncertainty in the boundary conditions. The geometry of the unknown thermal anomaly is parameterised with a level-set function that is inferred within the proposed Bayesian approach. In order to incorporate prior statistical information of the thermal anomaly, a Gaussian process conditioned on measurements from thermal images is employed to build a prior on the level-set function. The posterior distribution of inferred inputs is approximated via the implementation of an Ensemble Kalman Inversion algorithm that provides stable and accurate approximations of the posterior. This paper also proposes a methodology that uses the inferred 3D model to derive a thermally equivalent 1D model of the wall that is suitable for its integration with existing building energy performance software. The proposed inverse modelling technique is experimentally validated by characterising the thermal performance of an insulation panel in the presence of a thermal anomaly. Our computations show that the proposed approach produces a 3D model that accurately describes thermal performance, and a derived equivalent 1D model that effectively reproduces the dynamic thermal performance of the insulation panel in the presence of the thermal anomaly.

The lateral and vertical thermochemical heterogeneity in the mantle is a long-standing question in geodynamics. The forces that control mantle flow and therefore Plate Tectonics arise from the density and viscosity lateral and vertical variations. Satellite gravity data are a unique source of information on the density structure of the Earth due to its global and relatively uniform coverage, which complements gravimetric terrestrial measurements. Gravity data (geoid, gravity, gravity gradients) sense subsurface mass anomalies have proven to be helpful in determining the Earth’s thermochemical field in virtue of density’s relatively stronger dependence on rock composition compared to seismic velocities. However, the inversion of gravity data alone for the density distribution within the Earth is an ill-posed problem with a highly non-unique solution that requires regularization and smoothing, implying additional and independent constraints. A common approach to estimate the density field for geodynamical purposes is to simply convert seismic tomography anomalies sometimes assuming constraints from mineral physics. Such converted density field does not match in general with the observed gravity field, typically predicting anomalies the amplitudes of which are too large. Furthermore, a complete description of the Earth’s gravity field must include the internal density distribution and must satisfy the requirement of mechanical equilibrium as well. Therefore, the deformation of the density contrast interfaces (surface of the Earth and Core Mantle Boundary-CMB, primarily) must be consistent with the 3D mass distribution for a given rheological structure of the Earth. With the current resolution of modern tomography models and integrated geophysical-petrological modelling it is possible to consistently predict the topography of the mineral phase transitions across the transition zone (i.e., olivine à wadsleyite, and ringwoodite+majorite à perovskite+ ferropericlase) based on a temperature and chemical description of the Earth. However, for a consistent representation of the gravity field such thermochemical (i.e., density) 3D models must be compatible with the mantle flow arising from the equilibrium equations that explains both the surface topography (dynamic + isostatic-lithospheric components) and the CMB topography. Here we present a new inversion scheme to image the global thermochemical structure of the whole mantle constrained by state-of-the-art seismic waveform inversion, satellite gravity (geoid and gravity anomalies and gradiometric measurements from ESA's GOCE mission) and surface heat flow data, plus surface and CMB dynamic topography (Stokes flow). The model is based upon an integrated geophysical-petrological approach where mantle seismic velocities and density are computed within a thermodynamically self-consistent framework, allowing for a direct parameterization in terms of the temperature and composition variables.

This report has documented the methodologies and the data used for developing rock property sets for three infiltration maps. Model calibration is necessary to obtain parameter values appropriate for the scale of the process being modeled. Although some hydrogeologic property data (prior information) are available, these data cannot be directly used to predict flow and transport processes because they were measured on scales smaller than those characterizing property distributions in models used for the prediction. Since model calibrations were done directly on the scales of interest, the upscaling issue was automatically considered. On the other hand, joint use of data and the prior information in inversions can further increase the reliability of the developed parameters compared with those for the prior information. Rock parameter sets were developed for both the mountain and drift scales because of the scale-dependent behavior of fracture permeability. Note that these parameter sets, except those for faults, were determined using the 1-D simulations. Therefore, they cannot be directly used for modeling lateral flow because of perched water in the unsaturated zone (UZ) of Yucca Mountain. Further calibration may be needed for two- and three-dimensional modeling studies. As discussed above in Section 6.4, uncertainties for these calibrated properties are difficult to accurately determine, because of the inaccuracy of simplified methods for this complex problem or the extremely large computational expense of more rigorous methods. One estimate of uncertainty that may be useful to investigators using these properties is the uncertainty used for the prior information. In most cases, the inversions did not change the properties very much with respect to the prior information. The Output DTNs (including the input and output files for all runs) from this study are given in Section 9.4.

Many imaging algorithms for microwave breast cancer detection are limited by the assumption that the heterogeneity of the female breast is approximated by an effective permittivity during the reconstruction process. Since other modalities like ultrasound or MRI are used in conjunction with microwaves in recent years, it might be possible to estimate a complex 3D permittivity model that can be used within the reconstruction process as prior information. In this paper, we present a novel beamforming procedure for radar-based microwave breast cancer detection that incorporates a 3D-permittivity model. Hence, the reconstruction can take place in time domain on a piecewise basis rather than range domain. This approach is analyzed in this paper by means of a heterogeneous numerical breast phantom using Bristol's 31-element array configuration.