Introduction to this special section: Reservoir characterization Part I

2020 ◽  
Vol 39 (2) ◽  
pp. 82-83
Author(s):  
Ali Tura ◽  
Margarita Corzo
Keyword(s):  
Oil And Gas ◽  
Reservoir Characterization ◽  
Joint Inversion ◽  
Special Section ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Reflection Mode ◽  
Amplitude Variation With Offset ◽  
Zoeppritz Equations ◽  
Full Waveform

In 1980, Aki and Richards published linearized formulations of the Zoeppritz equations from 1919. From then on, many flavors and variations of the P-P reflection mode so-called amplitude variation with offset (AVO) equations have been published and used. Assuming the earth is isotropic, these equations are used day in and day out in the industry for reservoir characterization and to find oil and gas in the subsurface. Some publications have shown that using the P-P and P-S reflections in a joint inversion can increase the accuracy of the inverted parameters. Technically, however, there has been little divergence from the linearized Zoeppritz equations until lately when full-waveform inversion started to gain traction, initially for velocity model estimation and imaging and more recently applied to reservoir characterization.

New tools for 2D full-waveform inversion: applications on Brazilian Pre-Salt velocity model from Santos Basin

2020 ◽  
Author(s):  
Henrique Santos ◽  
Claus Eikmeier ◽  
Ernani Volpe
Keyword(s):  
Oil And Gas ◽  
Model Building ◽  
Waveform Inversion ◽  
Numerical Algorithms ◽  
Velocity Model ◽  
Southeastern Brazil ◽  
Full Waveform Inversion ◽  
Case Scenario ◽  
Velocity Inversion ◽  
Full Waveform

<p>In this work, we present full-waveform inversion (FWI) results of a typical Brazilian Pre-Salt model (Santos Basin) using new open-source tools. The large accumulations of oil with excellent quality and high commercial value discovered in the pre-salt carbonates of southeastern Brazil, especially in the Santos Basin, have made this province one of the most prospective in the world. Velocity model building in areas of highly complex geology (like the Santos Basin) remains a challenging step in seismic processing. FWI proved to be an efficient tool for the determination of high-resolution details in multiparameter models of complex subsurface structures, and it has been applied in different geophysical problem scales. However, since FWI is a computationally and mathematically challenging problem, many issues remain open, such as more efficient ways to deal with multiparameter inversion problems such crosstalk and different orders of magnitude in the seismic signal for different classes of parameters. Inversions for more than one class of parameters are of particular importance in the estimation of the physical properties of rocks (poroacoustic or poroelastic applications), for example, to monitoring oil and gas reservoirs and for monitoring the injection of carbon dioxide into geological structures. Also, programming complex numerical algorithms for each application is time-consuming and often evades the expertise of researchers from the geoscientific community. In this sense, a high-level computational tool for simulations and inversions would greatly improve the working time for researchers. Existing finite difference based FWI tools such as Devito, and finite elements based partial differential equations (PDE) solvers tools such as FEniCS and Firedrake are being explored and used for these purposes. In this work, we initially present an FWI acoustic isotropic inversion test (velocity inversion only), performed with the Devito software while a particular code is being developed in FEniCS and Firedrake computer programs. Devito is also a new and under development software and therefore must be tested under different conditions. Our first numerical results indicate the potential of using freely available computational programs in a real case scenario.</p>

scholarly journals Full-Waveform Inversion for Imaging Faulted Structures: A Case Study from the Japan Trench Forearc Slope

2021 ◽  
Author(s):  
Ehsan Jamali Hondori ◽  
Chen Guo ◽  
Hitoshi Mikada ◽  
Jin-Oh Park
Keyword(s):  
Seismic Data ◽  
Initial Velocity ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Control Measures ◽  
Japan Trench ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Time Migration ◽  
Shallow Sediments

AbstractFull-waveform inversion (FWI) of limited-offset marine seismic data is a challenging task due to the lack of refracted energy and diving waves from the shallow sediments, which are fundamentally required to update the long-wavelength background velocity model in a tomographic fashion. When these events are absent, a reliable initial velocity model is necessary to ensure that the observed and simulated waveforms kinematically fit within an error of less than half a wavelength to protect the FWI iterative local optimization scheme from cycle skipping. We use a migration-based velocity analysis (MVA) method, including a combination of the layer-stripping approach and iterations of Kirchhoff prestack depth migration (KPSDM), to build an accurate initial velocity model for the FWI application on 2D seismic data with a maximum offset of 5.8 km. The data are acquired in the Japan Trench subduction zone, and we focus on the area where the shallow sediments overlying a highly reflective basement on top of the Cretaceous erosional unconformity are severely faulted and deformed. Despite the limited offsets available in the seismic data, our carefully designed workflow for data preconditioning, initial model building, and waveform inversion provides a velocity model that could improve the depth images down to almost 3.5 km. We present several quality control measures to assess the reliability of the resulting FWI model, including ray path illuminations, sensitivity kernels, reverse time migration (RTM) images, and KPSDM common image gathers. A direct comparison between the FWI and MVA velocity profiles reveals a sharp boundary at the Cretaceous basement interface, a feature that could not be observed in the MVA velocity model. The normal faults caused by the basal erosion of the upper plate in the study area reach the seafloor with evident subsidence of the shallow strata, implying that the faults are active.

Joint full-waveform GPR and ER inversion applied to field data acquired on the surface

Geophysics ◽  
2021 ◽  
pp. 1-77
Author(s):  
diego domenzain ◽  
John Bradford ◽  
Jodi Mead
Keyword(s):  
Ground Penetrating Radar ◽  
Joint Inversion ◽  
Waveform Inversion ◽  
Shallow Groundwater ◽  
Computational Domain ◽  
Alluvial Deposits ◽  
Subsurface Structures ◽  
Full Waveform ◽  
Stable Source ◽  
Ground Penetrating

We exploit the different but complementary data sensitivities of ground penetrating radar (GPR) and electrical resistivity (ER) by applying a multi-physics, multi-parameter, simultaneous 2.5D joint inversion without invoking petrophysical relationships. Our method joins full-waveform inversion (FWI) GPR with adjoint derived ER sensitivities on the same computational domain. We incorporate a stable source estimation routine into the FWI-GPR.We apply our method in a controlled alluvial aquifer using only surface acquired data. The site exhibits a shallow groundwater boundary and unconsolidated heterogeneous alluvial deposits. We compare our recovered parameters to individual FWI-GPR and ER results, and to log measurements of capacitive conductivity and neutron-derived porosity. Our joint inversion provides a more representative depiction of subsurface structures because it incorporates multiple intrinsic parameters, and it is therefore superior to an interpretation based on log data, FWI-GPR, or ER alone.

Target-oriented inversion using the Patched Green′s function method

Geophysics ◽  
2021 ◽  
pp. 1-77
Author(s):  
Danyelle da Silva ◽  
Edwin Fagua Duarte ◽  
Wagner Almeida ◽  
Mauro Ferreira ◽  
Francisco Alirio Moura ◽  
...  
Keyword(s):  
Condensed Matter ◽  
Waveform Inversion ◽  
Time Lapse ◽  
Velocity Model ◽  
Dyson Equation ◽  
Computational Time ◽  
Green Functions ◽  
Target Area ◽  
Computational Domain ◽  
Full Waveform

We have designed a target-oriented methodology to perform Full Waveform Inversion using a frequency-domain wave propagator based on the so-called Patched Green’s Function (PGF) technique. Originally developed in condensed matter physics to describe electronic waves in materials, the PGF technique is easily adaptable to the case of wave propagation in a spatially variable media in general. By dividing the entire computational domain into two sections, namely the target area and the outside target area, we calculate the Green Functions related to each section separately. The calculations related to the section outside the target are performed only once at the beginning of inversion, whereas the calculations in the target area are performed repeatedly for each iteration of the inversion process. With the Green Functions of the separate areas, we calculate the Green Functions of the two systems patched together through the application of a Recursive Dyson equation. By performing 2D and time-lapse experiments on the Marmousi model and a Brazilian Pre-salt velocity model, we demonstrate that the target-oriented PGF reduces the computational time of the inversion without compromising accuracy. In fact, when compared with conventional FWI results, the PGF-based calculations are identical but done in a fraction of the time.

Full-waveform inversion for full-wavefield imaging: Decades in the making

2021 ◽  
Vol 40 (5) ◽  
pp. 324-334
Author(s):  
Rongxin Huang ◽  
Zhigang Zhang ◽  
Zedong Wu ◽  
Zhiyuan Wei ◽  
Jiawei Mei ◽  
...  
Keyword(s):  
Model Building ◽  
Seismic Imaging ◽  
Structural Information ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Data Sets ◽  
Full Waveform Inversion ◽  
Data Types ◽  
Velocity Models ◽  
Full Waveform

Seismic imaging using full-wavefield data that includes primary reflections, transmitted waves, and their multiples has been the holy grail for generations of geophysicists. To be able to use the full-wavefield data effectively requires a forward-modeling process to generate full-wavefield data, an inversion scheme to minimize the difference between modeled and recorded data, and, more importantly, an accurate velocity model to correctly propagate and collapse energy of different wave modes. All of these elements have been embedded in the framework of full-waveform inversion (FWI) since it was proposed three decades ago. However, for a long time, the application of FWI did not find its way into the domain of full-wavefield imaging, mostly owing to the lack of data sets with good constraints to ensure the convergence of inversion, the required compute power to handle large data sets and extend the inversion frequency to the bandwidth needed for imaging, and, most significantly, stable FWI algorithms that could work with different data types in different geologic settings. Recently, with the advancement of high-performance computing and progress in FWI algorithms at tackling issues such as cycle skipping and amplitude mismatch, FWI has found success using different data types in a variety of geologic settings, providing some of the most accurate velocity models for generating significantly improved migration images. Here, we take a step further to modify the FWI workflow to output the subsurface image or reflectivity directly, potentially eliminating the need to go through the time-consuming conventional seismic imaging process that involves preprocessing, velocity model building, and migration. Compared with a conventional migration image, the reflectivity image directly output from FWI often provides additional structural information with better illumination and higher signal-to-noise ratio naturally as a result of many iterations of least-squares fitting of the full-wavefield data.

Multi-parameter model building for the Qiuyue structure using four-component ocean-bottom seismometer data

Geophysics ◽  
2021 ◽  
pp. 1-52
Author(s):  
Yuzhu Liu ◽  
Xinquan Huang ◽  
Jizhong Yang ◽  
Xueyi Liu ◽  
Bin Li ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Waveform Inversion ◽  
Velocity Model ◽  
P Wave ◽  
Velocity Analysis ◽  
Full Waveform Inversion ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Full Waveform ◽  
P Wave Velocity

Thin sand-mud-coal interbedded layers and multiples caused by shallow water pose great challenges to conventional 3D multi-channel seismic techniques used to detect the deeply buried reservoirs in the Qiuyue field. In 2017, a dense ocean-bottom seismometer (OBS) acquisition program acquired a four-component dataset in East China Sea. To delineate the deep reservoir structures in the Qiuyue field, we applied a full-waveform inversion (FWI) workflow to this dense four-component OBS dataset. After preprocessing, including receiver geometry correction, moveout correction, component rotation, and energy transformation from 3D to 2D, a preconditioned first-arrival traveltime tomography based on an improved scattering integral algorithm is applied to construct an initial P-wave velocity model. To eliminate the influence of the wavelet estimation process, a convolutional-wavefield-based objective function for the preprocessed hydrophone component is used during acoustic FWI. By inverting the waveforms associated with early arrivals, a relatively high-resolution underground P-wave velocity model is obtained, with updates at 2.0 km and 4.7 km depth. Initial S-wave velocity and density models are then constructed based on their prior relationships to the P-wave velocity, accompanied by a reciprocal source-independent elastic full-waveform inversion to refine both velocity models. Compared to a traditional workflow, guided by stacking velocity analysis or migration velocity analysis, and using only the pressure component or other single-component, the workflow presented in this study represents a good approach for inverting the four-component OBS dataset to characterize sub-seafloor velocity structures.

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