Sumit Verma

Seismic attenuation attributes with applications on conventional and unconventional reservoirs

Seismic attenuation, generally related to the presence of hydrocarbon accumulation, fluid-saturated fractures, and rugosity, is extremely useful for reservoir characterization. The classic constant attenuation estimation model, focusing on intrinsic attenuation, detects the seismic energy loss because of the presence of hydrocarbons, but it works poorly when spectral anomalies exist, due to rugosity, fractures, thin layers, and so on. Instead of trying to adjust the constant attenuation model to such phenomena, we have evaluated a suite of seismic spectral attenuation attributes to quantify the apparent attenuation responses. We have applied these attributes to a conventional and an unconventional reservoir, and we found that those seismic attenuation attributes were effective and robust for seismic interpretation. Specifically, the spectral bandwidth attribute correlated with the production of a gas sand in the Anadarko Basin, whereas the spectral slope of high frequencies attribute correlated with the production in the Barnett Shale of the Fort Worth Basin.

Estimation of total organic carbon and brittleness volume

AbstractThe Barnett Shale in the Fort Worth Basin is one of the most important resource plays in the USA. The total organic carbon (TOC) and brittleness can help to characterize a resource play to assist in the search for sweet spots. Higher TOC or organic content are generally associated with hydrocarbon storage and with rocks that are ductile in nature. However, brittle rocks are more amenable to fracturing with the fractures faces more resistant to proppant embedment. Productive intervals within a resource play should therefore contain a judicious mix of organics and mineralogy that lends to hydraulic fracturing. Identification of these intervals through core acquisition and laboratory-based petrophysical measurements can be accurate but expensive in comparison with wireline logging. We have estimated TOC from wireline logs using Passey’s method and attained a correlation of 60%. However, errors in the baseline interpretation can lead to inaccurate TOC. Using nonlinear regression with Passey’s TOC, nor...

Vector correlation of amplitude variation with azimuth and curvature in a post-hydraulic-fracture Barnett Shale survey

AbstractKnowledge of induced fractures can help to evaluate the success of reservoir stimulation. Seismic P-waves through fracturing media can exhibit azimuthal variation in traveltime, amplitude, and thin-bed tuning, so amplitude variation with azimuth (AVAz) can be used to evaluate the hydraulic-fracturing-caused anisotropy. The Barnett Shale of the Fort Worth Basin was the first large-scale commercial shale gas play. We have analyzed two adjacent Barnett Shale seismic surveys: one acquired before hydraulic fracturing and the other acquired after hydraulic fracturing by more than 400 wells. Although not a rigorous time-lapse experiment, comparison of AVAz anisotropy of these two surveys provided valuable insight into the possible effects of hydraulic fracturing. We found that in the survey acquired prior to hydraulic fracturing, AVAz anomalies were stronger and highly correlated with major structural lineaments measured by curvature. In contrast, AVAz anomalies in the survey acquired after hydraulic fra...

Seismic signal denoising using thresholded variational mode decomposition

Noise reduction is important for signal analysis. In this paper, we propose a hybrid denoising method based on thresholding and data-driven signal decomposition. The principle of this method is to reconstruct the signal with previously thresholded intrinsic mode functions (IMFs). Empirical mode decomposition (EMD) based methods decompose a signal into a sum of oscillatory components, while variational mode decomposition (VMD) generates an ensemble of modes with their respective centre frequencies, which enables VMD to further decrease redundant modes and keep less residual noise in the modes. To illustrate its superiority, we compare VMD with EMD as well as its derivations, such as ensemble EMD (EEMD), complete EEMD (CEEMD), improved CEEMD (ICEEMD) using synthetic signals and field seismic traces. Compared with EMD and its derivations, VMD has a solid mathematical foundation and is less sensitive to noise, while both make it more suitable for non-stationary seismic signal decomposition. The determination of mode number is key for successful denoising. We develop an empirical equation, which is based on the detrended fluctuation analysis (DFA), to adaptively determine the number of IMFs for signal reconstruction. Then, a scaling exponent obtained by DFA is used as a threshold to distinguish random noise and signal between IMFs and the reconstruction residual. The proposed thresholded VMD denoising method shows excellent performance on both synthetic and field data applications. In this paper, we propose an adaptive denoising method based on data-driven signal mode decomposition, where the noise is represented by the residual/last mode. The proposed approach adaptively extracts the noise component depending on the data statistics rather than defining a fixed priori threshold.

Data conditioning of legacy seismic using migration-driven 5D interpolation

AbstractLegacy seismic surveys cover much of the midcontinent USA and Texas, with almost all 3D surveys acquired in the 1990s considered today to be low fold. Fortunately, recent advances in 5D interpolation have not only enhanced the quality of structural and stratigraphic images, but they have also improved the data sufficiently to allow more quantitative interpretation, such as impedance inversion. Although normal-moveout-corrected, common-midpoint-based 5D interpolation does an excellent job of amplitude balancing and the suppression of acquisition footprint, it appears to misinterpolate undercorrected diffractions, thus smearing fault and stratigraphic edges. We described a least-squares migration-driven 5D interpolation workflow, in which data were interpolated by demigrating the current subsurface image to the missing offsets and azimuths. Such demigration accurately interpolates fault edges and other diffractors, thereby preserving lateral discontinuities, while suppressing footprint and balancing...

Pitfalls in seismic processing: An application of seismic modeling to investigate acquisition footprint

AbstractThe term acquisition footprint is commonly used to define patterns in seismic time and horizon slices that are closely correlated to the acquisition geometry. Seismic attributes often exacerbate footprint artifacts and may pose pitfalls to the less experienced interpreter. Although removal of the acquisition footprint is the focus of considerable research, the sources of such artifact acquisition footprint are less commonly discussed or illustrated. Based on real data examples, we have hypothesized possible causes of footprint occurrence and created them through synthetic prestack modeling. Then, we processed these models using the same workflows used for the real data. Computation of geometric attributes from the migrated synthetics found the same footprint artifacts as the real data. These models showed that acquisition footprint could be caused by residual ground roll, inaccurate velocities, and far-offset migration stretch. With this understanding, we have examined the real seismic data volume...

Seismic-petrophysical reservoir characterization in the northern part of the Chicontepec Basin, Mexico

AbstractThe Chicontepec Formation in east-central Mexico is comprised of complex unconventional reservoirs consisting of low-permeability disconnected turbidite reservoir facies. Hydraulic fracturing increases permeability and joins these otherwise tight reservoirs. We use a recently acquired 3D seismic survey and well control to divide the Chicontepec reservoir interval in the northern part of the basin into five stratigraphic units, equivalent to global third-order seismic sequences. By combining well-log and core information with principles of seismic geomorphology, we are able to map deepwater facies within these stratigraphic units that resulted from the complex interaction of flows from different directions. Correlating these stratigraphic units to producing and nonproducing wells provides the link between rock properties and Chicontepec reservoirs that could be delineated from surface seismic data. The final product is a prestack inversion-driven map of stacked pay that correlates to currently prod...

Calibration of attribute anomalies through prestack seismic modeling

Seismic modeling is commonly used in determining subsurface illumination of alternative seismic survey designs, in the calibration of seismic processing and imaging algorithms, and in the design of effective processing workflows. Seismic modeling also forms the mathematical kernel of impedance inversion and is routinely used to predict the amplitude-variation-with-offset response as a function of rock and fluid properties. However, the use of seismic modeling in seismic attribute studies is less common. We have evaluated four case studies in which 2D synthetic common shot gathers were computed (acoustic or elastic) and processed (including migration) to evaluate possible interpretation hypotheses. The modeling we used in our study shows that the lack of continuous coherence anomalies in a faulted Chicontepec Basin survey was due to overprinting by coherent interbed multiples. Attributes computed from the resulting processed model data revealed that subtle curvature anomalies in a Mississippi Lime survey were due to karst collapse rather than to velocity pushdown related to vertical gas migration. Impedance attributes computed from a Woodford Shale model favored the hypothesis of increased porosity correlated with the occurrence of subtle faults rather than amplitude dimming due to poor fault imaging. Finally, modeling of a fractured basement survey in the Texas Panhandle survey indicated that headwave suppression preserved the basement fracture response while increasing the signal-to-noise ratio. Seismic attribute study on seismic modeling results helped significantly in testing possible interpretation hypotheses in all of our case studies.

Seismic Inversion Based SRV and Reserves Estimation for Shale Plays

Estimation of stimulated rock volume (SRV) is the cornerstone offield development planning in shale reservoirs. The EUR has a first order dependency on the SRV and therefore its estimation is extremely critical for field development. In this paper, we propose a methodology to estimate the SRV and hence the EUR for a shale reservoir using seismic data, flow and geomechanical simulation. The backbone of our methodology is seismic inversion coupled with geomechanical simulation. We apply our technique to data acquired from the Barnett shale. In this work, we first use 3D seismic and sonic logs to perform pre-stack seismic inversion. Then, we derive the distribution of Poissons ratio and Youngs modulus in the area of interest (AOI). We constrain the porosity in our geo cellular model using a rock type model. Our rock type model for this work is based on k-means clustering on multi-well log analysis. We modeled a well in the AOI for which microseismic data is available. Weused a coupledflow and geomechanical simulator to mimic the fracturing process and the fluid volumes injected during the actual completion of the well. For geomechanical coupling, we used Barton-Bandis model in seismic inversionderived Youngs modulus and Poissons ratio 3D volumes. Next, we compare our results with the SRV obtained by an analysis of microseismic data. We reconcile differences in the model-derived SRV and then calibrate the resulting flow model and use the history-matched model for forecasting production. Our results indicate an excellent match on SRV and therefore production data. Because we usevariable geomechanical parameters along the lateral, we observe irregular SRVs and drainage areas consistent with the microseismic data. Our methodology for predicting microseismic can be used for asset evaluation, acreage prioritization and to optimize the completion design in unconventional plays.

Introduction to special section: Multidisciplinary studies for geologic and geophysical characterization of CO2 storage reservoirs

There are currently 15 large-scale carbon capture and storage (CCS) projects and multiple pilot injection projects operating across the world. A critical challenge for successful CCS programs is to reliably and economically predict long-term behavior of CO2 in potential storage reservoirs. As with