Multicomponent Acquisition Research Articles

Multicomponent Seismic Data Reconstruction via a Biquaternion-Based Vector POCS Method

Multicomponent seismic exploration as a powerful geophysical technology has attracted more and more attention in seeking and identifying subtle oil and gas reservoirs. However, like traditional single-component acquisition, multicomponent seismic data acquisition also encounters sparse and irregular sampling problems. The conventional reconstruction methods treat multicomponent data as independent components and recover the missing traces in a component-by-component manner. These componentwise approaches ignore the internal mutual relationships among different components and damage the vector characteristics of the seismic wavefield. Quaternion algebra provides an effective vector representation tool for multicomponent data. Upon that, we present a new vector Projection Onto Convex Sets (POCS) method with biquaternion Fourier transform to reconstruct the irregularly missing traces of 3-D and three-component (3-D-3C) seismic data. Compared to the current real-valued quaternion reconstruction methods implemented in the time domain, the proposed method performed in the frequency domain can fully maintain the conjugate symmetry property of the biquaternion data and only reconstruct the positive or negative frequency slices of the observed 3-D-3C data. Besides, the new method can simultaneously interpolate the 3C or 4C data with different missing patterns. We compare the proposed vector POCS method with the scalar POCS method through experiments with a synthetic 3-D-3C dataset and a field 3-D-3C volume. Both experiments demonstrate the effectiveness and superiority of the proposed method.

Accurately Stable Q-Compensated Reverse-Time Migration Scheme for Heterogeneous Viscoelastic Media

The development of multi-component seismic acquisition technology creates new possibilities for the high-precision imaging of complex media. Compared to the scalar acoustic wave equation, the elastic wave equation takes the information of P-waves, S-waves, and converted waves into account simultaneously, enabling accurate description of actual seismic propagation. However, inherent attenuation is one of the important factors that restricts multi-component high-precision migration imaging. Its influence is mainly reflected in the following three ways: first, the attenuation of the amplitude energy makes the deep structure display unclear; second, phase distortion introduces errors to the positioning of underground structures; and third, the loss of high frequency components reduces imaging resolution. Therefore, it is crucial to fully consider the absorption and attenuation characteristics of the real Earth during seismic modeling and imaging. This paper aims to develop an accurate attenuation compensation reverse-time migration scheme for complex heterogeneous viscoelastic media. We first utilize a novel viscoelastic wave equation with decoupled fractional Laplacians to depict the Earth’s attenuation behavior. Then, an adaptive stable attenuation compensation operator is developed to realize high-precision attenuation compensation imaging. Several synthetic and field data analyses verify the effectiveness of the proposed method.

Application of multi-wave and multi-component seismic data in the description on shallow-buried unconsolidated sand bodies: Example of block J of the Orinoco heavy oil belt in Venezuela

The use of multi-wave and multi-component seismic information for reservoir prediction and characterization has been a popular research direction. The study area is located in the Orinoco heavy oil belt in Venezuela. The reservoir is a braided river delta plain deposit and the sandstone is shallowly buried and unconsolidated. Thereby, it is difficult to predict and characterize the type of reservoir effectively with seismic data of conventional P-waves. Based on multi-wave and multi-component seismic acquisition data, the study has conducted petrophysical analysis and seismic horizon calibration with converted wave (PS). Vertically, superimposed sand bodies were identified with PP wave because the PP wave has higher vertical resolution than that of PS wave. Laterally, sectional morphology and plane distribution scale of sand bodies were delineated by using the higher lateral resolution of PS wave. By combining the characteristics of PP wave and PS wave, five models for intersection and sand body superposition were summarized and the architecture units of sand bodies were divided. The seismic attribute (RMS amlpitude) boundary characteristics and continuity of the high amplitude region described by PS wave are more evident to obtain plane distribution of channel bars and braided channels. Three different seismic inversion results of seismic impedance, density and sand thickness from three different methods were compared. The average accuracy of sand body prediction with the method of PP-PS wave combined pre-stack inversion reached approximately 85% which is greater than that of the PP wave post-stack inversion and PP-PS combined post-stack inversion, with accuracy of 64% and 66% respectively. The research results showed that in the study area, the combination of multi-wave and multi-component seismic reflection information can effectively identify and predict multi-stage superimposed sand bodies with clearer vertical superposition and more accurate lateral boundary. Due to the inherent non-uniqueness of seismic information on predicting reservoir distribution, the resolution of seismic data and the difficulty of identification of the highly superimposed shallow-buried unconsolidated sandbodies, reservoir prediction uncertainty still exists. In particular, the interpretation on the sedimentary microfacies distribution and sand-body scale may only be one of the relatively reliable interpretation schemes.

Quantitative T2 MRI is predictive of neurodegeneration following organophosphate exposure in a rat model

Organophosphorus compounds, such as chemical warfare nerve agents and pesticides, are known to cause neurological damage. This study measured nerve agent-related neuropathology and determined whether quantitative T2 MRI could be used as a biomarker of neurodegeneration. Quantitative T2 MRI was performed using a 9.4 T MRI on rats prior to and following soman exposure. T2 images were taken at least 24 h prior, 1 h and 18–24 h after soman exposure. Rats were pre- and post-treated with HI-6 dimethanesulfonate and atropine methyl nitrate. A multicomponent T2 acquisition and analysis was performed. Brains were stained with Fluoro-Jade C to assess neurodegeneration. Rats exposed to soman developed behavioral expression of electrographic seizures. At 18–24 h after soman exposure, significant increases in T2, a possible marker of edema, were found in multiple regions. The largest changes were in the piriform cortex (before: 47.7 ± 1.4 ms; 18–24 h: 82.3 ± 13.4 ms). Fluoro-Jade C staining showed significant neurodegeneration 18–24 h post exposure. The piriform cortex had the strongest correlation between the change in relaxation rate and percent neurodegeneration (r = 0.96, p < 0.001). These findings indicate there is regionally specific neurodegeneration 24 h after exposure to soman. The high correlation between T2 relaxivity and histopathology supports the use of T2 as a marker of injury.

Shale Anisotropy Model Building Based on Deep Neural Networks

AbstractSeismic anisotropy parameters are essential in the processing and interpretation of modern array data with multicomponent, long offsets and wide azimuth acquisitions. Traditional well logs do not measure anisotropy in a vertical well and thus cannot provide the needed information. Conventional calibration‐based as well as recent inversion‐based rock physics modeling methods involve tuning parameters and subjective choices that are largely empirical and difficult to generalize. Here we present a machine learning approach to alleviate these problems. Since it is impossible to collect massive labeled field well log data, we generate paired synthetic data of features (porosity, density, vertical and wave velocities, wave and shear moduli) and labels (bulk and shear moduli of rock matrices and aspect ratio of ellipsoidal cracks). By tuning hyperparameters we obtain an optimal fully connected neural network with four hidden layers that fits well with the synthetic data. The neural network is applied to published laboratory measurements and field well log data from a Chinese well and a U.S. well without any modification. We show that anisotropy models estimated by the deep neural network agree well with the inversion results and with the laboratory measurements. The neural network optimized by extensive training based on massive synthetic data removes the subjectivity in parameter selection, generalizes to different geological environments, and has the potential to provide real‐time anisotropy estimation while logging.

Elastic wave-equation migration velocity analysis preconditioned through mode decoupling

Multicomponent seismic data acquisition can reveal more information about geologic structures and rock properties than single component acquisition. Full elastic wave seismic imaging, which uses multicomponent seismic to its full potential, is promising because it provides more opportunities to understand the material properties of the earth by the joint use of P- and S-waves. A prerequisite of seismic imaging is the availability of a reliable macrovelocity model. Migration velocity analysis for P-waves, which can fill that requirement for the P-wave velocity, has been well-studied, especially under the acoustic approximation. However, a reliable estimation of the S-wave velocities remains troublesome. Elastic wave-equation migration velocity analysis has the potential to build P- and S-wave velocity models together, but it inevitably suffers from the effects of mode coupling and conversion in the forward and adjoint wavefield reconstructions. We have developed a differential semblance optimization approach to sequentially invert the background P- and S-wave velocity models from extended PP- and PS-images in the subsurface offset domain. Preconditioning of the gradients with respect to the S-wave velocity through mode decoupling can improve the reliability of the optimization. Numerical investigations with synthetic examples demonstrate the effectiveness of gradient preconditioning and the feasibility of our migration velocity analysis approach for elastic wave imaging.

The Galperin source: A novel efficient multicomponent seismic source

Multicomponent acquisition enables a more complete observation of the seismic wavefield compared with single-component measurements and has therefore experienced increased interest in the past few decades. Whereas the use of multicomponent receivers is well-established, efficient and effective multicomponent sources are still difficult to realize. One of the main drawbacks of common multicomponent sources is that the source coupling differs for different components. Differences in the source coupling can lead to amplitude variations introducing uncertainties when jointly analyzing data from two or three components (e.g., for multicomponent polarization analysis). To overcome this problem, we have designed a new multicomponent vector source, referred to as the Galperin source. The design is inspired by the Galperin receiver configuration, and it consists of three orthogonal source vectors ([Formula: see text], [Formula: see text], and [Formula: see text]), which all have the same inclination relative to the horizontal. Using the Galperin configuration, three orthogonal source components can be acquired without moving the source and changing the source coupling, which also increases acquisition efficiency. We built a prototype of the Galperin source and compared it with other multicomponent sources used for near-surface investigations. Comparisons in the time and frequency domains indicate a good agreement between data acquired using the Galperin source and other, more conventional, sources. However, because the three source acquisition vectors [Formula: see text], [Formula: see text], and [Formula: see text] and the resulting processing coordinates [Formula: see text], [Formula: see text], and [Formula: see text] are linked by a rotational matrix, errors on one component can project into others. Therefore, precise leveling of the Galperin source and identical source strength for all three source components is essential to minimize errors.

Using Mirror Migration of OBS Data to Image the Deepwater Area of South China Sea

Ocean bottom seismograph (OBS) is widely used in investigating deep crustal structure, which is characterized by a large amount of data information and abundant frequency components because of its multi-component acquisition. OBS is seldom used in deepwater oil and gas exploration and basin research due to the high cost. The complicated seismic wave field is caused by the complex seabed topography, basin and oil and gas structure in deepwater area, which increases the difficulty of image processing. In addition to reflection imaging, we utilize the multiple of OBS data to make accurate imaging and have achieved desirable results in a deep sea area in South China Sea in this paper. Firstly, the original P and Z components of OBS data are processed by wave field separation to obtain the upgoing wave filed and downgoing wave filed. Secondly, its image velocity filed is constructed. Finally, downgoing wave data is used to image (called mirror migration). Compared with conventional migration, the mirror migration can clearly image the seabed and provide better illumination for shallow layer below the seafloor in the case of sparse nodes, which is proved by the migration results of theoretical and real data in this paper.

Multicomponent 3D-3C data acquisition and processing for characterization of Vaca Muerta Formation in Neuquén Basin, Argentina

The Neuquén Basin in Argentina has been producing for more than 100 years. Currently, the unconventional resources of the Vaca Muerta Formation are the ones that are most actively explored and studied. The reservoir is thick and heterogeneous in geomechanical properties and organic content. Therefore, to put a successful drilling program in place, one should study the reservoir using existing vertical wells and remote sensing methods like surface seismic, vertical seismic profiling, microseismic, etc. Properties derived from laterally dense seismic methods can be coupled with rock property measurements from the vertically dense well logs via developed rock physics relationships. An integrated reservoir model populated with rock properties will high-grade areas of the reservoir suitable for horizontal drilling and hydraulic fracturing. To better understand the Vaca Muerta Formation, the first multicomponent survey was shot in the Neuquén Basin at the beginning of 2017.

Shallow diffraction imaging in an SH-wave crosshole configuration

Imaging shallow subsurface voids, such as karsts, sinkholes, pinch-outs, dikes, and man-made voids, is an important task in near-surface geophysics. We have developed a new diffraction-based methodology for void detection and imaging. Due to the low signal-to-noise ratio of the diffracted signal in surface acquisition setups, we advocate the use of an SH-wave multicomponent crosshole acquisition. Naturally, the same setup can be used for velocity model building using tomography and for void imaging. The SH-wave data are migrated using a model-based, image-point-dependent automatic muting function that separates direct arrivals from diffracted events in the migration process. For the purpose of location and velocity analysis, data are migrated to the depth imaging offset domain. Only when the velocity model and imaging locations are correct will the diffracted energy be coherently focused to the void location and the diffracted event moveout in the migrated gather will be flat. We found that the received diffracted signal is clearer and has better temporal separation compared with a conventional P-wave crosshole survey. We determined the usefulness of this method using synthetic and field data examples for 2D acquisitions and a synthetic 3D case, showing that a precise imaging is possible. The importance of the S-waves velocity model, which can be extracted from the same survey using conventional tomography methods, is also discussed.

Comparing P-P, P-SV, and SV-P mode waves in the Midland Basin, West Texas

We acquired 3D multicomponent data in Andrews County, Midland Basin, West Texas with a seismic survey. We extracted direct-SV modes generated by a vertical-force source (an array of three inline vertical vibrators) from the vertical component of multicomponent geophones. This seismic mode, SV-P, was created by reprocessing legacy 2D/3D P-wave seismic data to create converted-wave data and consequently forgoing the need for a multicomponent seismic acquisition program to obtain important S-wave information from the subsurface. We have compared P-P, P-SV, and SV-P traveltime and amplitude characteristics to determine which seismic mode provided better characterization of the targeted reservoirs and reduced exploration risk.

A 2D automatic converted-wave static-correction algorithm

Although multicomponent data acquisition opens the door for sharper seismic images and more accurate subsurface characterization, it also brings many challenges into multicomponent data processing. Among these challenges, converted-wave (S-wave) static correction is significant. Due to the fact that the earth may have dramatically different velocity responses to P- and S-waves, P-wave statics and S-wave statics should be treated as two independent problems; as a result, approximating S-wave statics by a simple scaling of the P-wave statics is not a satisfying solution. A new automatic S-wave static-correction algorithm is proposed and has been successfully applied on a full-fold Arabian Gulf ocean-bottom-cable (OBC) data set with promising results.

3D-3C Multicomponent Seismic – A successful fracture characterization case study in Algeria

Multi-component acquisition has been used in the industry for many years for fracture density and orientation studies with proven success. In the field under study, it has been observed from well information at target level that there is a relationship between gas production and natural fractures, faults, and changes in facies. The target horizon located at a depth of approximately 1950 m is composed of low-porosity gas-bearing Ordovician sandstones of 5 to 6% average porosity. The Ordovician is characterized by a highly heterogeneous matrix affected by natural fractures. This paper describes a 3D multi-component land seismic project conducted in Algeria, designed to perform a fracture characterization study. This pilot survey, acquired in 2010 over the Tin Fouye Tabankort West block, is the first land 3D-3C acquisition ever performed in Algeria. It covers an area of about 67 km² centered on a well location. The following project phases will be described hereafter: (1) 3D-3C survey design and field operations, (2) Main steps of the PP and PS-wave pre-processing sequences, (3) PP and PS-wave interpretation study at deep levels made possible by the cleaned and signalpreserved seismic data. The resulting PP seismic dataset from the 3D-3C survey provides a better resolution of subtle faults and lineaments than the conventional 3D acquired in 2003 and reprocessed in 2010, even though the noise level remains slightly high. Furthermore, PS seismic data shows evidence of azimuthal anisotropy in relation to the faults and lineaments interpreted on the PP dataset. Anisotropy analysis results tie reasonably well with FMI information available in the Ordovician, showing great potential for using this technology for fracture studies.

Multicomponent reduced scale seismic modelling: upgrade of the MUSC laboratory with application to polarization observations

Reduced scale physical modelling is a useful intermediate step to fill the gap between field measurements and numerical simulations. In many different areas of seismology, multicomponent measurements are now commonly recorded and processed. However, up to now, laboratory facilities providing flexible and accurate reproduction of large multicomponent seismic experiments have not reached maturity. Within this context, we present an improvement of a measurement facility (MUSC) developed previously to enable the flexible and versatile reproduction of seismic experiments at reduced scale. This new measurement system provides simultaneous measurements of the vertical and the horizontal components of seismic wavefields by taking advantage of recent developments in laser ultrasonic sensing technologies. Reference measurements on an aluminum block are carried out in order to quantitatively evaluate multicomponent measurements. Noise characterization, surface wave ellipticity analysis and waveform comparisons with a semi-analytical model are presented. To enable the simultaneous comparison of phase and polarization attributes, we also introduce a regularized version of the polarization attributes and apply it to synthetic and experimental data. These comparisons demonstrate that high fidelity multicomponent reduced scale physical modelling is possible with this new facility. An illustrative example with a model containing a shallow cavity is presented. In this case, multicomponent measurements help to identify the cavity signature but multiples have a detrimental effect on regularized instantaneous polarization attributes. By assessing the reliability of the MUSC measurement facility in the performance of massive high-quality multicomponent data acquisition at the laboratory scale, this study highlights the interesting potentials of reduced scale modelling of seismic wave propagation for a large variety of applications

Image registration guided wavefield tomography for shear-wave velocity model building

Multicomponent acquisitions offer the opportunity to form elastic migration images and to estimate elastic parameters of the subsurface. Compared with better constrained P-wave velocity inversions, it is more difficult to estimate the S-wave velocity due to strong nonlinearities introduced by converted S-waves. We have developed an iterative S-wave velocity inversion method guided by image registration. Given an accurate P-wave velocity and a simple initial S-wave model, we form P-P and P-S images using elastic reverse time migration. We use image registration to find the shifts between the P-S and P-P images. The S-wave velocity model could be updated iteratively by minimizing the differences between the original and the fractionally warped P-S images. A simple layered model and a modified Marmousi model are used to demonstrate the viability of the new method. In both examples, high-quality P-S images, as well as smooth S-wave velocity models, are inverted efficiently with a homogeneous S-wave initial model.

Six-component seismic land data acquired with geophones and rotation sensors: Wave-mode selectivity by application of multicomponent polarization filtering

Multicomponent acquisition systems today record incomplete data because they do not measure rotations. Geophones or accelerometers provide linear motion and hydrophones provide pressure, but no current commercial acquisition system includes sensors that measure rotations. Without rotations, the data provide incomplete recording of the wavefield because in three dimensions, there are six degrees of freedom — three linear displacements and three rotations. In two small 2D seismic surveys recorded with six components, three-component geophones were deployed and three-component rotation sensors that measured pitch, roll, and yaw were deployed. Pitch was measured independently with closely spaced geophones. Measuring rotations with closely spaced geophones is not practical in production, but it can be used in research and development to validate rotation-sensor data. A comparison of pitch measured by two independent methods finds that they fit after instrument designature. Data provided by rotation sensors have additional value because they can be used in analysis of singular value decomposition (SVD) to identify and separate ground roll and body waves.

Time-lapse seismic modeling for CO2 sequestration at the Dickman Oilfield, Kansas

Carbon dioxide capture and injection into the subsurface has aroused great interest in the past few years as a method to enhance oil recovery and mitigate [Formula: see text] emissions. The Dickman Oilfield located in Kansas provides two possible [Formula: see text] sequestration targets: a regional deep saline reservoir (the primary objective) and a shallower mature depleted oil reservoir (secondary). We focused on the shallower depleted oil reservoir through a 250-year flow-simulation scenario and a fault leakage test. Seismic responses at various time intervals were simulated to help monitor [Formula: see text] flow paths and injection stability. A complex and realistic geologic model with unconformity was embedded in the flow-simulation model. A regridding technique was used that assigned geologic values to a regular seismic grid that allowed 2D acoustic and elastic finite-difference simulation. Gassmann fluid substitution theory was used to obtain the reservoir properties with different [Formula: see text] saturations, and the vertical seismic profile was used to assist in identifying geologic layers. A [Formula: see text] plume and flow path from the leakage test can be detected from the differences in seismic data (5 to 10 ms time shift) from the first year of injection and the last year of monitoring. This was supported by comparison with the prestack field data available in the Dickman Oilfield. [Formula: see text]-induced reflectivity changes are relatively larger for PS events than for PP events, implying that multicomponent data acquisition and processing may give added value to characterization and monitoring of carbon capture and storage projects. We assessed 4D seismic monitoring in the evaluation of long-term [Formula: see text] containment stability for the Dickman Oilfield and suggested that time-lapse surveys will be useful.

Application of three-component VSP technology at seismically difficult sites: An example from the FutureGen 2.0 site, Morgan County, Illinois, USA

Reflection seismic data provide the primary technology for imaging subsurface geology between and distal to wellbores; and where rock physics properties are suitable, surface seismic and vertical seismic profiles (VSP's) can provide important CCUS monitoring modalities. In addition, seismic data provide the subsurface framework for locating microseismic events and reducing risk of induced seismicity. Seismic surveys have traditionally been limited to acquisition and processing of compressional (P) -wave data, but modern technology includes the use of three-component receivers that can additionally record shear (S) wave modes that have been generated at the surface or converted from P-waves in the subsurface. Each collected waveform can potentially produce a separate data volume and new information on the subsurface. This paper reviews the insights gained through application of multicomponent VSP technology at the FutureGen2.0 site where, typical of many proposed CCUS and CCS sites, traditional P- wave surface seismic imaging is considerably impacted by seismic noise. We conclude that a comparison of shear and P-wave data and interferometric processing allows a better understanding of subsurface geology, and provides input parameters for improved acquisition of surface seismic data at CCUS sites in old, fast rocks or below depleted oil and gas fields. Although results will vary by locality, we suggest that because of the insights provided by an analysis of multicomponent data, multicomponent acquisition and processing should become part of standard best practices for site characterization and evaluation.

On data-independent multicomponent interpolators and the use of priors for optimal reconstruction and 3D up/down separation of pressure wavefields

In marine acquisition, the interference between the upgoing and downgoing wavefields introduces a receiver ghost which reduces the effective bandwidth of the seismic wavefield. A two-component streamer provides means for removing the receiver ghost by measuring pressure and vertical particle velocity. However, due to nonuniform and relatively sparse sampling in the crossline direction, the seismic data are usually severely aliased in the crossline direction and the deghosting may not be feasible in a true 3D sense. A true multicomponent streamer measures all components of the particle motion wavefield in addition to the pressure wavefield. This enables solving the 3D deghosting and crossline reconstruction problems simultaneously, without making assumptions on the wavefield or the subsurface. We havedeveloped two data-independent algorithms suited for multicomponent acquisition. The first algorithm reconstructs the total pressure wavefield in the crossline direction by using the pressure and the crossline component of particle motion simultaneously. The second algorithm reconstructs the upgoing pressure wavefield by using the pressure, the crossline, and the vertical components of particle motion simultaneously. Both algorithms are optimal in the minimum-mean-squares-error sense and are ideally suited for a small number of irregularly spaced samples, as is common in towed marine acquisition. We find that by using the spectrum of the wavefield as a priori information, these algorithms have the potential to overcome higher-order aliasing than what is predicted by multichannel sampling theorems. Such a priori information can be extracted from an unaliased portion of the seismic data in novel and robust manners.

Technology Focus: Seismic Applications (March 2010)

Technology Focus Finding and producing hydrocarbons from increasingly complex reservoirs and the push to maximize recovery stimulated a decade of steady growth in high-end seismic solutions covering the full E&amp;P life cycle. In challenging imaging environments, the improvements achieved with the latest acquisition and processing technology are significant. Not surprisingly, associated cost pressures and budget constraints increasingly force geophysicists to strive for adequate and cost-effective solutions. Simultaneously, we experience a renewed focus on adding value by pushing the integration with other disciplines to new levels. Papers reviewed for the new Seismic Applications feature highlight how seismic technologies pay dividends on the basis of an improved understanding of the subsurface. Several contributions discuss wide-azimuth seismic, which has become the norm in complex-imaging environments such as the Gulf of Mexico. Advances are not confined to marine surveys, and densely sampled wide-cross-spread surveys are being acquired onshore also. The logistical efforts for these modern surveys are large. Accurate planning and detailed survey design are essential for efficient and successful delivery. Beyond improved imaging, rich-azimuth seismic, probably in combination with multicomponent acquisition, has a realistic potential to enable fracture detection on the basis of azimuthal-anisotropy analysis. This technology can provide considerable value in carbonates and tight reservoirs in which fractures have a strong effect on connectivity and production rates. Robust and accurately calibrated rock-physics models are a prerequisite to bridge the gap between seismic and reservoir modeling. For carbonates, this is notoriously difficult, and enhanced physical models are being developed that result in more-reliable reservoir-property predictions. Reservoir models only approximate the actual subsurface, and seismic constraints are used more routinely to reduce remaining uncertainties. Next to static-model updates, repeated 4D-seismic surveys provide information about the dynamic-reservoir behavior. Permeability maps derived from 4D seismic can be incorporated during the history-matching process, providing a promising leap toward real integration of subsurface disciplines and improved recovery. Seismic Applications additional reading available at OnePetro: www.onepetro.org IPTC 13692 • “Multicomponent-Seismic Applications for Maximizing Efficiency and Production from Fractured-Carbonate Reservoirs in Idd El Shargi Field” by E. Maili, Occidental Petroleum of Qatar, et al. IPTC 13882 • “Microseismic Reservoir Monitoring in a Deep-Wellbore Carbonate Environment in Kazakhstan” by K.G. Maver, SPE, Schlumberger, et al. IPTC 13870 • “Wide-Azimuth Seismic Azimuthal Analysis in Offset Vector Domain for Velocity and Amplitude” by Jean-Luc Boelle, Total, et al.