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Collecting seismic data requires an energy source to generate waves and sensors to receive those waves. The appropriate energy source and receiver depend on the location and the application. This article describes different types of equipment used for seismic data acquisition. A variety of seismic sources exist that can apply vertical impulse forces to the surface of the ground. These devices are viable energy sources for onshore seismic work.
In most exploration and reservoir seismic surveys, the main objectives are, first, to correctly image the structure in time and depth and, second, to correctly characterize the amplitudes of the reflections. Assuming that the amplitudes are accurately rendered, a host of additional features can be derived and used in interpretation. Collectively, these features are referred to as seismic attributes. The simplest attribute, and the one most widely used, is seismic amplitude, and it is usually reported as the maximum (positive or negative) amplitude value at each sample along a horizon picked from a 3D volume. It is fortunate that, in many cases, the amplitude of reflection corresponds directly to the porosity or to the saturation of the underlying formation.
A variety of seismic sources exist that can apply vertical impulse forces to the surface of the ground. These devices are viable energy sources for onshore seismic work. Included in this source category are gravity-driven weight droppers and other devices that use explosive gases or compressed air to drive a heavy pad vertically downward. Multiple references describe these types of sources. Chemical-explosive energy sources are popular for onshore seismic surveys but are prohibited at some sites because of environmental conditions, cultural restrictions, or federal and state regulations. Chemical explosives are no longer used as marine energy sources for environmental and ecological reasons. Field tests should always be made before an extensive seismic program is implemented. First, it should be determined whether the selected impulsive source creates adequate energy input to provide data with an appropriate signal-to-noise ratio and a satisfactory signal bandwidth at appropriate offset distances. Second, it is important to determine whether an impulsive source causes unwanted reverberations in shallow strata. Vibroseis energy sources are some of the more popular seismic source options for onshore hydrocarbon exploration.
Interest in quantitative interpretation (QI) of seismic data in the Abu Dhabi region continues to steadily increase, and the objective of creating inversion-ready seismic data is driving evolution of the surface seismic data processing workflows to focus on more detailed and thorough handling of the amplitude and phase throughout processing (pre-, during, and post-imaging). To achieve close well ties across the survey and to ensure the data is suitable for interpretation purposes, zero-phasing and wavelet stability (along with using well information during earth model building) are key stages in the depth imaging seismic processing workflow. Accurate amplitude with offset and azimuth handling is also required for inversion studies. In this paper, we propose a workflow where a geophysically and geologically credible, 3D variable Q-field is built into the earth model early in the processing flow, allowing a more complete approach to handling the Q-effects of the subsurface without increasing project turnaround time. This case study shows that a data-driven spatially variable Q-field combined with Kirchhoff Pre-Stack Depth migration compensates effectively for both amplitude and phase effects, providing a broadband image with improved event continuity and better handling of noise compared with applying a constant pre-migration Q-compensation (which was previously thought to be suitable for this low-relief region). By calibrating the variable Q-field to available well logs and near surface information, and ensuring that the different geophysical parameters in the earth model are all suitably coupled, an enhanced image is achieved which then requires minimal spectral shaping or residual phase corrections post migration. Ray-based Q-tomography workflows allow iterative 3D updates alongside coupled subsurface properties like anisotropy and velocity, within a high-resolution Earth model suitable for depth imaging. Reliable phase stability, higher resolution, broader useable bandwidth and improved amplitude preservation are key targets of this holistic approach.
Unal, Ebru (University of Houston) | Rezaei, Ali (University of Houston) | Siddiqui, Fahd (University of Houston) | Likrama, Fatmir (Halliburton) | Soliman, M. (University of Houston) | Dindoruk, Birol (Shell International Exploration and Production, Inc.)
In the last decade, technical advancements have greatly improved the design and execution efficiency of well completions, leading to improved recovery from unconventional reservoirs. However, analyzing fracture diagnostic tests in unconventional plays are still challenging due to high uncertainty in predictive capabilities in the context of fracture dynamics during treatment. The main objective of this study is to identify fracture behavior during injection and pressure fall-off periods in hydraulic fracturing treatments and diagnostic fracture injection tests (DFIT), respectively.
In this study, discrete wavelet transformation (DWT) was used to analyze real field injection and fall-off data in the wavelet domain. The analyzed data are from multi-stage hydraulic fracturing operations and DFIT in unconventional horizontal wells. DWT coefficients reveal very crucial information related to the nature of the events within recorded signals; they also reveal various patterns that are hard to recognize otherwise. The high-frequency components of the pressure and rate signals (detail coefficients) that are calculated by the wavelet transformation determine localization and separation of various events. We compared the identified events for injection and fall-off periods with moving reference point (MRP) and G-function analysis, respectively.
The main advantage of our proposed approach is that it is based on real-time data and does not require any assumptions related to existing or created fractures. Also, it is very sensitive to physical changes in the system; thus, it reveals hidden information related to those changes. Consequently, the energy of detail coefficients represents several events at different frequencies. We used pseudo-frequency of wavelet coefficients as a diagnostic tool for an accurate comparison of fracture propagation and fracture closure events to determine similarities and differences between them. For example, the signal energy of detail coefficients from the wavelet transformation of hydraulic fracturing data demonstrates abrupt frequency changes during dilation or fracture height growth during fracture propagation. Therefore, we were able to identify those events by energy density analysis in both time and pseudo-frequency domains in an objective manner, which otherwise was not possible with conventional methodologies such as G- function derivative analysis.
This paper details the successful methodology for effective implementation of a new fracture diagnostic technique for fracturing operations or DFITs in unconventional horizontal wells. This new fracture diagnostic method does not require any reservoir or fracture pre-assumptions; it mainly relies on the pressure behavior, which is a result of various events at different frequencies. Pressure fall-off behavior of a DFIT gives essential information related to closure event of the created mini-fracture. Identification of these events at different pseudo-frequency ranges improves the understanding of the dynamic fracture behavior also the characteristics of the reservoir. Unlike many other diagnostic techniques, this data-driven approach requires minimum input/data for analysis. This approach also lends itself to real-time application quite easily.
The Delaware and Midland Basins are multistacked plays with production being drawn from different zones. Of the various prospective zones in the Delaware Basin, the Bone Spring and Wolfcamp formations are the most productive and thus are the most-drilled zones. A 3D seismic survey was acquired in the northern part of Delaware Basin and after processing was picked up, to understand the reservoirs of interest and pick the sweet spots. The whole reservoir characterization exercise was carried out on this data in three different phases. We discuss phase 1 here, beginning with a brief description of the geology of the area and the stratigraphic column, and going on to the well ties for the different available wells over the 3D seismic survey, estimation of the shear curves where the measured shear curves were missing, the generation of an accurate low-frequency model for impedance inversion, preconditioning of the prestack seismic data, use of different lithotrends in inversion and finally the prestack simultaneous impedance inversion.
The Permian Basin in west Texas and southeast New Mexico is the most prolific of all the basins in the US. The Delaware Basin forms the western subbasin of the Permian, the Midland Basin the eastern part, and both are separated by the Central Basin Platform (Figure 1). The Delaware and Midland Basins are multistacked plays with production being drawn from different zones. Of the various prospective zones in the Delaware Basin, the Bone Spring and Wolfcamp formations are the most prolific and thus the most-drilled zones.
3D seismic data acquisition and processing
A three-dimensional seismic survey was acquired in the Delaware Basin, spread over the Ward, Loving and Winkler counties (Figure 1). The size of the seismic survey was 407 mi2 (1050 km2) and its acquisition completed in November 2017. The seismic data had 2 ms sample interval, 5 s record length, and with a bin size of 82.5 ft. by 82.5 ft. (25.2 x 25.2 m). The processing of this large data volume was completed in May 2018 with anisotropic prestack time migration (PSTM) gathers and stacked volume with 5D interpolation.
The processing of the data was completed in April 2018 and picked up with the objective of seismic reservoir characterization that would help in understanding the reservoirs of interest and prove useful towards cost-effective drilling.
Biswal, Debakanta (Adani Welspun Exploration Limited) | Nedeer, Nasimudeen (Adani Welspun Exploration Limited) | Banerjee, Subrata (Adani Welspun Exploration Limited) | Singh, Kumar Hemant (Indian Institute of Technology)
The boundary between a thick carbonate layer and its substrata is often a well-defined reflector due to the presence of shaly and clayey layers beneath the carbonates. This reflector and other underlying reflectors result in a velocity pull-up effect because the seismic velocities within the carbonates are higher than that of the surrounding sediments. The geometry of velocity pull-up beneath the carbonate body is related to the geometry of the structure and the thickness of the carbonate body the seismic wave travels through.
In B9 area of Mumbai Offshore basin, the reservoir facies are largely represented by clastics deposited along tidal deltaic lobes. Wells drilled though Daman formation have encountered good quality pay sands within the Daman formation. This pay has produced commercial quantities of hydrocarbons in the vicinity making the area attractive for further exploration and exploitation. The overlying Bombay formation consists mainly of shale with occasional bands of limestone and claystone. The development of thick isolated carbonates bodies within Bombay formation is observed in "C" structure on which "Well-C" is placed. This is seen to significantly constrain the structural configuration in the "C" area. There is a possibility of substantial extension of the "C" structure towards south if the impact of velocity pull up due to carbonate build up can be successfully mitigated. The ultimate challenge is to image the Daman reservoirs, mitigating overburden lateral velocity variations.
In addition to a layered cake depth conversion approach for depth conversion of the time map, a more robust approach, PSDM followed by depth conversion was carried out. This paper highlights the merit of different methods.
Hydrocarbon-charged sediments detection and characterization are the main concern of petroleum explorers and producers. Over the past decades, the Amplitude Variation with Offset (AVO) technique had proved to be a very successful tool in hydrocarbon identification and recognition. AVO attributes have been used particularly to extract information about the lithology (sand, shale, etc.) and fluid content of the subsurface. It unraveled successful discoveries in many sedimentary basins around the globe. The success was documented mainly in the West Delta deep marine and analogous shallow unconsolidated rocks of Pliocene age worldwide. However, due to the fact that most of the hydrocarbon potential reserves in those basins and in easily explored areas have been discovered, the attention of the oil industry has been directed to enhance recovery from producing formations and exploring more difficult and complex environments (e.g. deep offshore, deep closely stacked thin bedding reservoirs, thin narrow and meandering reservoir channels, etc.). Thus, AVO attributes are insufficient for achieving the goals reached in earlier time. With the advent of seismic attributes technology, innovative seismic attributes appeared and proved to have potential in achieving information which used to be extracted using AVO. Of these innovative attributes, Spectral Decomposition (SD) proved to be a powerful tool in revealing subtle details that aseismic broadband may burry. Over the last decades, numerous published works have discussed how this attribute can be used to differentiate both lateral and vertical lithologic and pore-fluid changes; as well as delineating stratigraphic traps and identifying subtle frequency variations caused by hydrocarbons from world different environments and geological settings. The first section of this chapter focuses principally on the definition of seismic attributes and their applications in reservoir studies from the literature.
The objective of this paper is to develop a framework under which we can improve the clastic reservoir characterization by using the pre-stack inversion and the neural-network analysis. The aim is to go beyond the limitations of full-stack seismic data and reduce the uncertainty as much as possible.
Bao, Yi (Exploration and Development Research Institute of Daqing Oilfield Company Ltd. CNPC.) | Wang, Cheng (Exploration and Development Research Institute of Daqing Oilfield Company Ltd. CNPC.) | Chen, Shu-min (Exploration and Development Research Institute of Daqing Oilfield Company Ltd. CNPC.) | Wang, Jian-min (Exploration and Development Research Institute of Daqing Oilfield Company Ltd. CNPC.) | Chen, Zhi-de (Exploration and Development Research Institute of Daqing Oilfield Company Ltd. CNPC.) | Pei, Jiang-yun (Exploration and Development Research Institute of Daqing Oilfield Company Ltd. CNPC.) | Wu, Jia-yi (Exploration and Development Research Institute of Daqing Oilfield Company Ltd. CNPC.)
The existing seismic data in the deep layer of Songliao Basin have low vertical resolution, poor imaging accuracy and weak ability to depict anisotropy of seismic data, so the seismic data can not meet the geological requirements of fine target characterization. In order to identify thinner reservoirs and smaller faults in deep and complex structural areas, to complete sequence subdivision on volcanic rocks of Yingcheng formation and the dense sand of Shahezi formation, BWH seismic data acquisition is deployed in Anda sag. Aiming at the characteristics of clear description of BWH wave field but low SNR. A Full-frequency Fidelity and Amplitude preserving processing Technology (Flow) supported by surface consistent time-varying pulse deconvolution and viscoelastic medium prestack time migration and depth migration techniques is formed. Compared with the old data, the target band width of the BWH data has been widened by 15 Hz, the imaging quality of the complex structural area is improved obviously, and the prediction coincidence rate of the thin sand body over 8m is increased by more than 10 percentage points. The thin interbed is developed in continental sedimentary basin, and the horizontal heterogeneity is serious. The BWH acquisition and full frequency amplitude preserving processing technology will bring a new solution for fine target exploration in deep and complex structural area of Continental Sedimentary basin.
I examine the basis of slow convergence of tomographic full waveform inversion (TFWI) and discover that the reason behind it is the unbalanced effects of amplitudes and phase in the design of the regularization term. This imbalance results in a strong reliance of the kinematic updates on the amplitude fitting, slowing down the convergence. To mitigate the problem I propose two modifications to the tomographic inversion. First, by modifying the regularization term to focus more on the phase information, and second, simultaneously updating the source function for modeling. The adjustments reduce the gradient artifacts and allow for explicit control over the amplitudes and phases of the residuals.
Tomographic full waveform inversion (
The modeling operator is able to match the observed data by extending the velocity model with the proper axis, no matter what the accuracy of the initial model is, by using kinematic information from the extended axis with disregard to the occurrence of cycle skipping. The inversion is set up to extract all the essential information from the virtual axes and smoothly fold them back into their original, nonextended form of the model. The kinematic and dynamic information of the data were successfully inverted with exceptional robustness and precision.
Even though cycle-skipping is not an issue with TFWI, this method creates its own challenges, which are; its high computational cost and the big number of iterations that it needs (
Two adjustments to TFWI are proposed to reduce the slow convergence and allow for more control of the ratio between amplitude and phase. These adjustments are consistent in the framework of TFWI and allow for an accurate calculation of the gradient in the data space. The adjustments were tested and resulted in a reduction in the kinematic artifacts in the gradient.