Wave equation migration can usually produce high-quality images below complex overburden given sufficient data and an accurate velocity model. However, inaccurately estimated high-contrast, short-wavelength, buried velocity anomalies disrupt the images of seismic reflections from deeper layers. Currently we solve this problem by building velocity models either with tomographic techniques or interpretation-based techniques. Existing velocity model construction methods based on interpretation and insertion of complex model boundaries are time consuming, tedious to implement, and error-prone. More-automated velocity model construction methods such as tomography (Stork, 1992), wave equation migration velocity analysis (Biondi and Sava, 1999) and FWI (Sirgue and Pratt, 2003) tend not to have enough resolution to define boundaries with sufficient sharpness, or may not have sufficient depth of investigation to handle very complex velocity boundaries at arbitrary locations in the model.
Multi-wave seismic exploration is an integrated method that uses P-waves, S-waves, and converted waves to accomplish precise exploration of petroliferous basins and directly predict the location of hydrocarbons. This paper presents a successful example of three-component three-dimensional (3C3D) seismic exploration of a fractured-cavity carbonate reservoir in the northern part of the Tarim Basin in China. We use the different characteristic responses between P-waves and converted waves in fractured-cavity carbonate reservoirs and the converted-wave seismic imaging technique to achieve better imaging in fractured-cavity carbonate formations. The techniques of converted-wave seismic imaging applied in this work include converted-wave static correction, multi-parameter velocity analysis of converted waves, and anisotropic pre-stack time migration (PSTM).
Conventional high-order discontinuous Galerkin schemes suffer from interface errors caused by the misalignment between straight-sided elements and curved material interfaces. We develop a novel discontinuous Galerkin scheme to reduce the errors. Our new scheme use the correct normal vectors to the curved interfaces, while the conventional scheme uses the normal vectors to the element edge. We modify the numerical fluxes to account for the curved interface. Our numerical modeling example demonstrate that our new discontinuous Galerkin scheme significantly suppresses the spurious diffractions seen in the results obtained using the conventional scheme. The computational cost of our scheme is similar to that of the conventional scheme. Our new discontinuous Galerkin scheme is thus particularly useful for large-scale scalar-wave modeling involving complex subsurface structures.
In the exploration and development of oil and gas fields, the nature of the local micro tectonics is one of the key factors that determines the distribution of remaining oil. In general, micro tectonics can be divided into positive microscopic structural and negative microscopic categories. The former is considered to be an area with abundant remaining oil and the second category is an area that is poor in oil and gas reserves or is easily flooded by water. In this paper, we propose an automatic method to identify positive micro structural regimes, and calculate related parameters. The proposed method generalizes a watershed transformation - an image segmentation technique based on the simulation of flooding of a landscape - into the field of seismic exploration. The method not only improves the recognition accuracy of positive micro tectonics, but greatly reduces the manual participation, which, in turn, provides reliable data for injection-production schemes and calculation of remaining reserves. Finally, we illustrate the proposed method using one real 3-D seismic data set. The results show that improved models based on the watershed theory can identify positive micro tectonics with high accuracy.
The full waveform inversion (FWI) can obtain accurate estimates of the parameters of subsurface materials using the steepest descent method with iterative calculations. Applying the Hessian matrix as a pre-conditioner improves the results of FWI. However, obtaining the full or approximate Hessian matrix is not practical because of the intensive computational cost. The diagonal of the pseudo-Hessian matrix is widely used to scale the gradient at a reduced computing cost, but it has problems imaging the deep region of the model. In this study, we suggest a new scaling method for frequency-domain elastic FWI that uses a weighted pseudo-Hessian matrix to overcome the imaging problem caused by the limitations of the pseudo-Hessian matrix. To verify the proposed algorithm, a numerical test is performed with the Model 94 synthetic data.
We present a method for inversion of fracture compliance matrix components from Wide Azimuth (WAZ) noisy synthetic PS-reflection data and show quantitatively that variations of reflection amplitude with offset and azimuth (AVOA) for converted PS-waves are more informative for fracture characterization than P-waves. We consider monoclinic symmetry for fractured reservoir (parameters chosen from Woodford shale), which can be formed by two or more sets of vertical fractures embedded in a VTI background. Components of effective fracture compliance matrices for a medium with monoclinic symmetry are related to the characteristics of the fractured medium. Monte Carlo simulation results show that inversion of PS reflection data is more robust to uncertainties in our a priori knowledge (VTI parameters of unfractured rock) than PP reflection data. Also we show that while inversion of PP reflections is sensitive to contrasts in elastic properties of upper and lower media, inversion of PS reflectivities is robust with respect to such contrasts.
3D reverse-time migration using the cross-correlation imaging condition poses a challenge for the computer-memory requirement and computational complexity, because both the forward-propagated source wavefield and the backward-propagated receiver wavefield should be accessible at the same time step. We develop a new wavefield reconstruction method to balance the computer-memory requirement and computational complexity of reverse-time migration. During the forward simulation of the source wavefield, we store the wavefield at only one or two layers of spatial grid points at/near the model boundaries, and reconstruct the back-propagated source wavefield in the imaging domain using a high-order wave-equation extrapolation scheme. One of conventional reverse-time migration methods uses boundary wavefields stored at multiple layers of spatial grid points. For a finite-difference scheme with the eighth or sixteenth order of accuracy in space, our new method uses only 37.5% of the computer memory required by this conventional method to store the boundary wavefields, and has the almost same accuracy as the latter. We validate our method using synthetic seismic reflection data. Our method produces 2D and 3D migration images of complex subsurface structures as accurate as those yielded using a reverse-time migration method that stores source wavefields at multiple boundary layers to maintain the spatial order of accuracy of the finite-difference scheme near the boundaries.
To mitigate the probem of cycle-skipping for FWI using surface waves on an exploration scale, more robust misfit functions based on alternative data domains have recently been proposed. In this study simple synthetic inversion tests are used to investigate the more robust behavior of these approaches compared to the classical FWI approach. Misfit functions in the ω - p and the ω -k domains are shown to be more robust in the presence of cycle-skipping for very simple to complex laterally varying models.
The construction of subsurface velocity models is an ongoing issue for oil & gas exploration. In complex terrain, such as regions with topography or laterally varying shallow structures, the imaging of deeper exploration targets may still be problematic due to the presence of groundroll. In such cases, an innovative characterization of near surface properties is needed, and the inversion of surface waves, which sample this shallow zone, appears to be essential to image deeper lying targets. Using FullWaveform Inversion (FWI) as a high-resolution imaging technique, allows to extend beyond the 1D limitations of more conventional surface wave imaging methods.
The absence of low-frequency information in real field seismic data prevents Full Waveform Inversion (FWI) applications from obtaining smoothed velocity model for accurate seismic imaging. In addition, for land datasets, FWI with acoustic wave equation is not suitable in describing wave propagations to accommodate surface and converted waves. The seismic data used in this paper was acquired in Saudi Arabia by using an acquisition configuration based on dispersed source arrays having three different frequency bands, namely, 1.5 to 8 Hz, 6.5 to 54 Hz and 50 to 87 Hz. Alternatively, elastic FWI is applied for the estimation of three parameters, namely, the P-wave, S-wave velocities and density to one of this dataset containing 1.5 to 8 Hz. In an algorithm of elastic FWI, wave modeling is performed in the time domain by the first-order wave equation with the staggered grid scheme while other procedures such as calculating the partial derivative wavefields are conducted in the Laplace- or Laplace-Fourier domains based on the second-order wave equation with the finite element method. To demonstrate the validity of the elastic FWI, acoustic reverse time migration was implemented on the initial and inverted P-wave velocities with the data containing 6.5 to 54 Hz.
Andreasen, Mie (University of Copenhagen) | Looms, Majken Caroline (University of Copenhagen) | Jensen, Karsten Høgh (University of Copenhagen) | Sonnenborg, Torben O. (Geological Survey of Denmark and Greenland) | Bogena, Heye (Agrosphere IBG-3) | Juelich, Forschungszentrum (GmbH) | Desilets, Darin (Hydroinnova LLC) | Zreda, Marek (University of Arizona)
We estimate soil moisture content variation for an agricultural field in Denmark using a cosmic-ray neutron probe and compare the results with point measurements using capacitance probes, and modelling result using a one-dimensional hydraulic model. The cosmic-ray data are in good agreement with modelled soil moisture content variation using measured/estimated meteorological variables (i.e. precipitation, potential evapotranspiration, and temperature) as well as unsaturated hydraulic parameters.
Soil moisture in the upper subsurface controls the amount of water returned to the atmosphere through evapotransporation, and thereby also controls the amount of water recharged to the underlying groundwater reservoirs. A detailed knowledge of the soil moisture variation over time is therefore crucial for water balance considerations in catchment modelling. Soil moisture measurements using point-scaled probes, such as Time Domain Reflectrometry (TDR) probes and capacitance probes (e.g. 5TE, Decagon Devices), have been applied in soil moisture networks in several catchments (e.g. Bogena et al., 2010; Bircher et al., 2012), due to the fairly robust and inexpensive equipment now available. Furthermore, the petrophysical equations needed to convert the dielectric permittivity values measured to estimated moisture content are fairly wellestablished and universal for coarse-grained mineral soils (Topp et al., 1980). However, the measurement volume of such a sensor is on centimeter to decimeter scale, and upscaling to catchment models may be challenging. Cosmic-ray neutron probes provide soil moisture estimates at a scale that is more in concurrence with the large-scale hydrological models as the measurement footprint has a diameter of approx. 600 m (Zreda et al., 2008; Desilets and Zreda, 2013). These measurements bridge the considerable gap in scale between point measurements and remotely sensed data (e.g. SMOS satellite, Bircher et al., 2012).