Zwartjes, Paul (Shell Global Solutions International B.V.) | Mateeva, Albena (Shell International Exploration and Production, Inc.) | Chalenski, David (Shell International Exploration and Production, Inc.) | Duan, Yuting (Shell International Exploration and Production, Inc.) | Kiyashchenko, Denis (Shell International Exploration and Production, Inc.) | Lopez, Jorge (Shell International Exploration and Production, Inc.)
We met these needs through multiple surveys in one field in the Gulf of Mexico. We show that our vision of using DAS VSP to fill gaps in time between OBN surveys is feasible and robust against variances in shot geometry and source size. These successfully-completed field trials accelerate technology maturation and lay the foundation for future frequent monitoring around specific wells. Introduction In 2013, the feasibility of acquiring Distributed Acoustic Sensing (DAS) data for 3D VSP in deepwater was first proven (Mateeva et al., 2013a, Wu et al., 2015) and its potential to enable frequent seismic monitoring around wells identified (Mateeva et al., 2013b). Since then, we have reported on learnings from several deepwater acquisitions (Tatanova et al., 2017) and explained how DAS fits in our pursuit of low-cost seismic surveillance, a desired solution for the successful management of complicated fields (Chalenski et al., 2016). Most recently, we carried out a 4D proof-of-concept of DAS VSP (Zwartjes et al., 2017; well W1 in Table 1) and developed a methodology for assessing its value against other 4D options (Lopez et al., 2017). We concluded that 4D DAS VSP would be competitive in terms of cost and value-to-investment ratio for surveillance in deepwater.
Ongoing improvements in computational capability and seismic acquisition have made imaging using multi-component elastic waves feasible. Multicomponent seismic data can provide additional subsurface information, such as fracture distributions and elastic properties (MacLeod et al., 1999; Mehta et al., 2009; Sen, 2009). For elastic reverse-time migration, the constructed vector wavefields allow for a variety of imaging conditions (Yan and Sava, 2008; Denli and Huang, 2008; Artman et al., 2009; Wu et al., 2010). One widely used imaging condition is crosscorrelation of separated wave modes from the source and receiver wavefields, which yields PP, PS, SP, and SS images. However, because PS and SP reflectivities change signs at certain incidence angles, the computed PS and SP images change polarities at the corresponding angles. Duan and Sava (2014) propose an imaging condition for elastic reverse-time migration, generating PS and SP scalar images with consistent polarity information for all experiments. This imaging condition requires additional information, i.e. the reflector normal field. Here, we investigate two practical problems associated with this imaging condition, including the estimation of the reflector normals when the reflectors are imaged at incorrect positions, and the imaging of a reflector by waves arriving from opposite sides.
Least-squares migration (LSM) can produce images with improved resolution and reduced migration artifacts. We propose a method for elastic least-squares reverse time migration (LSRTM) based on a new perturbation imaging condition that yields scalar images of squared P and S velocity perturbations. These perturbation images are simply related to physical subsurface properties, and in addition, they do not suffer from polarity reversals seen with other more conventional elastic imaging methods. We use 2D examples to demonstrate the proposed LSRTM algorithm using our perturbation imaging condition. Results show that elastic LSRTM increases the image resolution and attenuates artifacts, while providing images where the relative amplitudes of the reflectors can be used for reservoir characterization.
Presentation Date: Monday, October 17, 2016
Start Time: 1:25:00 PM
Presentation Type: ORAL
We propose 3D angle decomposition methods from elastic reverse time migration using time- and space-lag common image point gathers, time-lag common image gathers, and space-lag common image gathers computed by elastic wavefield migration. We compute time-lag common image gathers at multiple contiguous locations, instead of isolated positions as is commonly done with common image gathers. Then, we transform the extended images to the angle domain using slant stacks along surfaces that connect neighboring positions, instead of line slant stacks for isolated common image gathers. We demonstrate our methods using 2D and 3D synthetic examples and show that our techniques provide accurate opening and azimuth angles, and that they can handle steeply dipping reflectors and converted wave modes.
Presentation Date: Monday, October 17, 2016
Start Time: 4:10:00 PM
Presentation Type: ORAL
We propose elastic isotropic wavefield tomography formulated with the misfit of observed and recorded data as the objective function. Using the elastic isotropic wave-equation formulated for slowly varying media, we invert for the squared velocities of compressional (P) and shear (S) waves. Poor illumination of P- and S-waves often prevents reliable update of the model parameters, while preserving their intrinsic physical relationships. Thus, we introduce a model constraint term in the objective function, which sets the ratio of P- and S-wave velocities to a chosen range, assumed to be generally linear as suggested by laboratory measurements or well logs. Examples demonstrate that this constraint yields models that are more physically plausible than models obtained using only the data misfit as the objective function.
Seismic tomography is a commonly used tool for building models of subsurface parameters from recorded seismic data. Wavefield tomography is well-developed under the acoustic assumption (Tarantola, 1984; Pratt, 1999; Operto et al., 2004; Biondi and Almomin, 2014); however, recorded seismic data include shear waves in addition to the compressional waves. Because all wave modes contain useful information about the subsurface, elastic wavefield tomography better characterizes the subsurface (Tarantola, 1986; Pratt, 1990; Guasch et al., 2012; Vigh et al., 2012). There are many possible parameterizations for elastic models, which lead to different inversion schemes. For example, Tarantola (1986) shows wavefield tomography for compressional impedance, shear impedance, and density, while Mora (1988) and Guasch et al. (2012) compute P- and S-velocity models using wavefield tomography.
Though inversion for multi-parameters adds more physical information to the updated model compared to single-parameter inversion, different parameters in the updated model may not be physically realistic (Plessix, 2006), i.e. inversion may not be able to resolve the model parameters while preserving their intrinsic relationships. Therefore, such physical relationships need to be enforced explicitly because their action on the inverted model differs from the alternative constraints provided by data or by shaping regularization. Physical relationships between model parameters in elastic media can be derived from well logs, seismic data, and laboratory measurements, but they can also be derived based on first-principle physical relationships (Tsuneyama, 2006; Compton and Hale, 2013). Experiments show that the relationship between P and S velocities is generally linear (Castagna et al., 1985; Katahara, 1999; Tsuneyama, 2006); therefore, enforcing a range of constant ratios between the two velocities could guide the model update, thus increasing the robustness of wavefield tomography.
Receiver-side water-column multiples acquired with ocean-bottom seismic sensors can be used for elastic imaging of the subsurface, which can provide additional information relative to more conventional acoustic imaging. In this paper, we generalize the procedures for elastic migration using water-column multiples. We first separate receiver-side water-column multiples from primaries in recorded OBS data, and then use mirror imaging to migrate the multiples. However, additional procedures are required in the elastic case, including correcting the polarity change in PS and SP images and attenuating artifacts caused by non-physical wave-mode conversions. With these additional procedures, we are able to obtain PP, PS, SP, and SS images.
Wavefield-based tomographic methods are idoneous for recovering velocity models from seismic data. The use of wavefields rather than rays is more consistent with the bandlimited nature of seismic data. Image domain methods seek to improve the focusing in extended images, thus producing better seismic images. However, image domain methods produce low resolution models due to the fact that their objective functions are smooth, particularly in the vicinity of the global minimum. In contrast, data-domain methods produce high resolution models but suffer from strong non-linearity causing cycle skipping if certain conditions are not met. By combining the characteristics of each method, we can obtain models that produce better images and contain high resolution features at the same time. We demonstrate a the workflow that combines both methods with an application to a broadband marine 2D dataset with a variable streamer depth.
Polarity changes in converted-wave images constructed by elastic reverse-time migration causes destructive interference after stacking over the experiments of a seismic survey. We derive a simple imaging condition for converted waves imaging designed to correct the image polarity and reveal the conversion strength from one wave mode to another. Our imaging condition exploits pure P- and S-modes obtained by Helmholtz decomposition. Instead of correlating components of the vector S-mode with the scalar P-mode, we exploit the entire S wavefield at once to produce a unique image. We generate PS and SP image using geometrical relationships between the propagation directions for the P and S wavefields, the reflector orientation, and the S-mode polarization direction. Compared to alternative methods for correcting PS and SP images polarity reversal, our imaging condition is simple and robust and does not add significantly to the cost of elastic reverse-time migration.
Summary Arbitrary Difference Precise Integration (ADPI) method is evolved from Finite Difference (FD) method, and it adopts integration scheme in time domain. In this paper, we deduce the formula of ADPI method based on 1-D elastic equation. The numerical comparison shows that ADPI is more stable than FD method. In forward modeling cases, ADPI method is applied in 2D and 3D elastic wave equation forward modeling. Results show that the travel time of reflected seismic wave is accurate and the method can be easily applied to elastic wave equation forward modeling for geological models.
Seismic modeling is an effective method for studying the propagation of seismic waves within complex structures. Based on finite difference method, the arbitrary difference precise integration (ADPI) for seismic forward modeling was developed for 3-D seismic modeling in this paper. When it comes to cases of 3-D modeling, compared with CPU single-core or multi-core processors, graphic processing unit (GPU) parallel calculation shows its outstanding ability of fast calculation to make a seismic forward modeling closer to real seismic records at very low cost of personal computer. Cases study of 3D seismic forward modeling confirm the correction and efficiency about the methodology of ADPI techniques and its GPU algorithms.