79th EAGE Conference and Exhibition 2017

Though the anisotropy exists popularly in the earth, it is frequently neglected both in geophysical data interpretation and in modelling. However, negligence of the electrical anisotropy can have a serious influence on near-surface prospecting, like airborne electromagnetic (AEM), especially in areas where the underground bears well-developed stratification. In this paper, we first put forward a modelling algorithm, named spectral element method (SEM), for airborne EM modelling for a three-axis anisotropic earth. SEM is a technique based on weighted residual method. The latter uses a polynomial basis function for SEM, which can achieve a high accuracy when increasing the polynomial order. We take as example a horizontal coplanar coil (HCP) of an AEM system to check the accuracy of our algorithm for anisotropic models and we compare the 3rd and 4th order SEM modelling results with 1-D semi-analytical solution for a half-space or layered-earth model. To study the anisotropic effect on AEM responses, we calculate and compare the responses for both isotropic and anisotropic abnormal bodies using 3rd to 5th order SEM. Finally, we analyse the influence of the order of SEM interpolation functions on the AEM responses.

During the last decade geologists and engineers have used the Finite Element Method (FEM) with elasto-plastic or visco-plastic behavior to simulate salt in order to gain a better understanding of the in-situ stress distribution. However, building such FEM models can become time consuming and challenging, especially when complex geometry is involved, and modeling elaborated non-linear salt behavior can take hours to days to process. We have developed a different approach using a fast 3D Boundary Element Method (BEM) and which allows fast model construction and computation (few minutes). Instead of using non-linear mechanical behavior of salt, we use the assumption that salt can be viewed as a pressurized cavity for which unknown parameters like the far field stress and salt pressure gradient are inverted using available fracture, stress or deformation data associated to past or actual deformation around salt. To verify this approach, BEM results have been validated against known 3D analytical solution for pressurized spherical cavity and compared to published, more complex, 3D FEM salt models. The efficiency of this new approach, in terms of model construction and mechanical simulation, is demonstrated through a natural example of faults associated to salt diapirs in the Gulf of Mexico.

Full Waveform Inversion aims to determine parameters of the subsurface by minimising the misfit between the simulated and recorded seismic data. The quality of such fit depends on many different aspects, as for example, the inversion algorithm and the accuracy of the constitutive laws. The latter is particularly important as if there are factors that are not taken into account in the seismic simulation then the inversion algorithm will compensate for their existence in the parameter(s) being estimated. One of such factors is attenuation. Here we introduce an approach that jointly estimates velocity and attenuation using a combination of Quantum Particle Swarm Optimisation with the conventional gradient descent method. This hybrid approach takes advantage of the fact that it is sufficient to estimate smooth models of Q and for this reason these can be represented with a sparse support, thus decreasing substantially the number of weights of the basis functions that have to be estimated and making the use of global algorithms practical. We demonstrate that the proposed method mitigates cross-talk between velocity and attenuation, while allowing the convergence towards accurate models of attenuation and velocity, thus being an effective method for velocity model building and consequently for seismic imaging.

Cycle skipping in the conventional full waveform inversion (FWI) objective function depends on the frequency content of the data, and on the error in the background velocity. The error in background velocity that can be tolerated without skipping cycles is determined by the half cycle criterion. However, the half cycle criterion is offset dependant so that far offsets in the data are more prone to cycle skipping than near offsets. This offset dependence of the half cycle criterion implies that the differentials of residuals with offset can be used as additional constraints in the objective function. In this study we introduce the scaled-Sobolev objective (SSO) that seeks to minimize a smooth version of the data residuals in addition to their derivatives in all data domain dimensions. The smoothing of the data is done using the scaled-Sobolev inner product (SSIP) in the data domain, resulting in an edge-preserving smoothing operator. In the absence of low frequencies, increasing the maximum order of derivatives in SSO is more important than the zeroth order scale factor. Initial results with synthetic data using the Marmousi model show that SSO can overcome a bulk shift in velocity of 30%, with a lowest frequency of 8 Hz.

The paper develops a reliable numerical method to solve inverse dynamic problem for elastic waves equation on the base of nonlinear least-squares formulation which is widely known as Full Waveform Inversion (FWI). The key issue on this way is correct reconstruction of macrovelocity component of the model with input seismic data without time frequencies less than 5–7Hz and reasonable source-recievers offsets. To provide correct macrovelocity reconstruction we introduce modified elastic FWI formulation which is sensitive to smooth space variations of both Vp- and Vs-velocity distributions

Kuwait Oil Company (KOC) is undertaking an EOR project on a heavy oil field. This 3DVSP project was designed to monitor a 30-day steam injection into two reservoir sands which are separated by thin shale and top sealed by a thicker shale.

The goals of this project include creating a repeatable baseline survey for future 4DVSP purposes, acquiring high resolution data so individual thin reservoirs can be imaged, reservoir characterization analysis, and estimation of the steam chamber size after a 30-day CSS injection. Obtaining the highest possible frequencies was identified as a critical success factor for achieving these goals.

Extensive modelling and innovative customization of the acquisition design resulted in high resolution 3D seismic which provided surveillance and steam monitoring of thin vertically stacked reservoirs. The results demonstrated the steam flow direction was complex rather than a simple radial pattern. Reservoir characterization helped explain some of the complexity of the Cyclic Steam Stimulation program. Understanding the reservoirs, barriers, and effectiveness the steam floods will help determine where infill producer or injection wells need to be drilled to optimize production.

A deep exploration well was drilled down to 5300 m on the top of a surface fold in the mountainous Zagros in order to encounter a deep anticline at the top of Permian reservoir formation expected in the area. Due to poor surface seismic, geological and practical considerations were used for locating the well. The structural interpretation was refined during the drilling operation, using: well logs, borehole resistivity imaging, geological data, a 2D surface seismic and an intermediate VSP recorded using a three component (3C) sensor tool implemented with a Relative Bearing / Roll angle sensor.

The VSP data was processed before drilling the deep interval 5300m to 6130m Total Depth (TD), with the intention to predict any reflection below the intermediate 5300m drilled depth.

Next, the whole borehole data was further analyzed after reaching TD. The main focus was on independent extraction of dip/azimuth information from oriented 3C VSP data and from borehole wall resistivity measurements.

The highly folded structure encountered by the well and the absence of high energy seismic reflectors with substantial lateral extension detected by the VSP are coherent with the blurred results on the 2D surface seismic section in the well vicinity.

Seismic waves propagating through attenuative subsurface exhibit amplitude loss and distortion of frequency spectra. Proper description of attenuation process is required to compensate for these effects. Moreover, inelastic attenuation contains information on rock properties and could be utilized in attribute analysis for subsurface characterization. We propose to quantify inelastic (intrinsic) attenuation in horizontally-layered media by wavefield inversion of VSP data with respect to effective interval Q-factors. Impact of short-path multiples in finely-layered subsurface, i.e. scattering at stratigraphic boundaries, and other interference effects are taken into account by forward simulation over a high-resolution elastic model acquired from the well logs (resolution of 1.5m). We present a case study of approximate-zero-offset vertical seismic profile data from Wheatstone offshore site (Northern Shelf of Western Australia). First we describe the algorithm of 1D waveform Q-inversion. Then we validate it on the full-wave synthetics computed for the field survey geometry using a Global Matrix approach (OASES MIT code). Finally, we discuss the results of the Q-inversion application to the field ZVSP dataset versus Q-estimates by Centroid Frequency Shift method.

We have investigated noise estimation in distributed acoustic sensing (DAS). We used an adaptive Wiener filtering method to construct noise maps. The resulting noise maps can be stored together with the images themselves and used in diversity stacks, which provide an uplift in time-lapse repeatability over linear stacking. We found that relatively large gains in VSP repeatability can be made from simple techniques.

We investigate the optimal blending in the finite element method and isogeometric analysis for wave propagation problems. These techniques lead to more cost-effective schemes with much smaller phase errors and two additional orders of convergence. The proposed blending methods are equivalent to the use of nonstandard quadrature rules and hence they can be efficiently implemented by replacing the standard Gaussian quadrature by a nonstandard rule. Numerical examples demonstrate the superior accuracy of the optimally-blended schemes compared with the classical methods.