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Um, Evan (Lawrence Berkeley National Laboratory) | Marchesini, Pierpaolo (Lawrence Berkeley National Laboratory) | Wilt, Michael (Lawrence Berkeley National Laboratory) | Nichols, Edward (Lawrence Berkeley National Laboratory) | Alumbaugh, David (Lawrence Berkeley National Laboratory) | Vasco, Donald (Lawrence Berkeley National Laboratory) | Daley, Thomas (Lawrence Berkeley National Laboratory) | Key, Kerry (Columbia University)
The goal of carbon capture and geological storage (CSS) is to reduce carbon dioxide (CO2) release to the atmosphere by capturing CO2 from powerplants and industrial facilities and subsequently injecting it into a deep permeable geological formation for long-term storage. Successful and safe CCS operations require developing and improving subsurface monitoring technologies for tracking CO2 movement, evaluating storage integrity and early detection of CO2 leak from storage. In this study, we present a novel, fully-integrated Electromagnetic (EM) and seismic acquisition system designed to efficiently detect the boundaries of an injected CO2 plume and monitor its evolution at several stages of injection at a field site. For both methods, we present the preliminary inversion results that will be used as baseline models for future time-lapse crosswell imaging experiments. Presentation Date: Tuesday, October 13, 2020 Session Start Time: 8:30 AM Presentation Time: 11:25 AM Location: 360A Presentation Type: Oral
ABSTRACT Numerical models of contemporary as well as paleo-ice sheets suggest that groundwater and heat exchanges between subglacial sedimentary basins and the ice sheet above, can be substantial and influence the flow of ice above. So far, an approach for the measurement and assessment of such heat fluxes has not been available. Here, we summarise existing evidence for groundwater and heat exchanges between contemporary and paleo ice sheets and the substrate below. We then explain the utility of electromagnetic geophysical measurements in elucidating such exchanges, and present magnetotelluric synthetic models of the deep sedimentary basin beneath the Institute Ice Stream in West Antarctica by way of illustration. Finally, we propose a simple empirical model by which heat exchanges between subglacial sedimentary basins and the overlying ice sheet can be estimated to first-order from electromagnetic data. Presentation Date: Tuesday, September 17, 2019 Session Start Time: 8:30 AM Presentation Start Time: 10:10 AM Location: 301B Presentation Type: Oral
Key, Kerry (Lamont-Doherty Earth Observatory, Columbia University) | Gustafson, Chloe (Lamont-Doherty Earth Observatory, Columbia University) | Blatter, Daniel (Lamont-Doherty Earth Observatory, Columbia University) | Evans, Rob L. (Woods Hole Oceanographic Institution)
Submarine groundwater contained in continental shelves may be a significant global phenomenon, yet little is known about its distribution. Off the US Atlantic coast, boreholes have revealed low salinity groundwater far offshore but are unable to characterize the aquifer’s lateral extent. We conducted a pilot study of large-scale electromagnetic (EM) surveying to map offshore groundwater at locations off New Jersey and Martha’s Vineyard. The high conductivity contrast between resistive fresh or brackish water and the surrounding conductive seawater saturated sediments makes offshore aquifers good targets that are electrically analogous to resistive hydrocarbon reservoirs. We used a combination of seafloor magnetotelluric (MT) and surface-towed controlled-source electromagnetic (CSEM) instrumentation originally developed for hydrocarbon exploration to map the lateral extent of the aquifers. Joint inversion of the MT and CSEM data reveals the aquifers extend about 80 km offshore in both locations. Off New Jersey, the EM results agree well with borehole data that show a shallow low salinity aquifer in the upper 400 m that is underlain by a deeper saline brine.
Presentation Date: Thursday, October 18, 2018
Start Time: 8:30:00 AM
Location: 213A (Anaheim Convention Center)
Presentation Type: Oral
We introduce a new scheme for the reliable 3D inversion of marine controlled-source electromagnetic (EM) data. Our code, named Modeling with Adaptively Refined Elements for 3D EM (MARE3DEM), uses a new variant of the regularized Occam method for the inversion framework. A parallel goal-oriented adaptive finite element method serves as the backbone for the forward operator. Both the forward and inverse model domains are simulated using unstructured tetrahedral meshes, which readily accommodate arbitrarily complex 3D conductivity variations. The unstructured inverse mesh efficiently handles multiple scale structures and allows for fine-scale model parameters within the region of interest while parameters in the outer domain can be made coarser. The inverse and forward domains are decoupled with the initial forward mesh nested in the inverse mesh. This initial mesh is iteratively refined using a goal-oriented adaptive scheme until the forward solution's accuracy converges to the desired tolerance. As the key interface between the forward and inverse operator, the sensitivity kernels that establish a linear relationship between changes in the conductivity model and changes in the modeled responses are efficiently computed using the adjoint-reciprocity method on the optimal refined mesh. Parallel computation of the forward responses and sensitivity kernels follows a data decomposition scheme where independent modeling tasks containing different frequencies and subsets of the transmitters and receivers are simulated in parallel. This gives the algorithm a high degree of scalability for significantly faster solve times when run using hundreds or thousands of processors on a high performance computing cluster. Further parallel scalability is obtained in the regularized Gauss-Newton portion of the inversion using parallel dense matrix-matrix multiplication and matrix factorization routines implemented with the ScaLAPACK library. We show the scalability, reliability and the potential of the algorithm to deal with complex geological scenarios by applying it to the inversion of synthetic marine controlled-source EM data generated for a complex 3D offshore model with significant seafloor topography.
Presentation Date: Thursday, October 20, 2016
Start Time: 11:00:00 AM
Presentation Type: ORAL
Barak, Ohad (Stanford University) | Key, Kerry (Scripps Institution of Oceanography) | Constable, Steven (Scripps Institution of Oceanography) | Milligan, Paul (Seabed Geosolutions) | Ronen, Shuki (Stanford University, Dolphin Geophysical)
There are currently no widely available rotation sensors that can operate on the ocean-bottom. We derive rotation data on the ocean bottom from two surveys that were not originally designed to record them: 1) from geophone recordings in the Moere Vest ocean-bottom survey by differencing adjacent geophones; and 2) from magnetometer recordings in the SERPENT CSEM ocean-bottom survey by extrapolating from the deviations in magnetic field projections on the magnetometer components.
Rigid bodies in a three dimensional world have six degrees of freedom: three components of linear motion and three components of rotation. In the subsurface, the linear motions are the particle velocities and the rotations are the pitch, roll and yaw, as shown in the following table:
where vi are particle velocities along the axis, and ri are rotation rates around the axis.
In ocean-bottom node acquisition, multicomponent geophones that are coupled to the seafloor record the vertical and the two horizontal components of particle velocity. Additionally, a hydrophone records the divergence of the wavefield P=k (V·u), where u are particle displacements and k is the bulk modulus of the water to which the hydrophones are coupled. Rotations are a measurement of the curl of the wavefield r = ½ (V ×v ), and are a recording of the anti-symmetric strains of the medium (Cochard et al., 2006).
Vassallo et al. (2012) use hydrophones together with pressure gradient sensors in marine streamer acquisition to interpolate the pressure wavefield in the crossline direction, between streamer cables. Similarly, the rotational components can be used to interpolate vertical geophone data (Edme et al., 2014), and spatial aliasing of high-wavenumber arrivals can thus be mitigated. Barak et al. (2014b) show that rotation data are extra information, are independent of geophone data, and how they can be used in conjunction with geophone data to identify and separate wave-modes on land using singular-value decomposition polarization analysis.
As of yet there are no industry-grade solutions for recording rotational motion on the ocean bottom, though a few such recording stations have been deployed previously by Pillet et al. (2009).The objective of this paper is to show how rotation data can be extracted from existing ocean-bottom recordings.
This work presents a parallel goal-oriented adaptive finite element method for accurate and efficient electromagnetic modeling of complex 3D structures. An unstructured tetrahedral mesh allows this approach to accommodate arbitrarily complex 3D conductivity variations and a priori known boundaries. Accuracy of the finite element solution is achieved through adaptive mesh refinement that is performed iteratively until the solution converges to the desired accuracy tolerance. Refinement is guided by a goal-oriented error estimator that uses a dual-weighted residual method to optimize the mesh for accurate EM responses at the locations of the EM receivers. Our algorithm is parallelized over frequencies, transmitters and receivers, where the adaptive mesh refinement is performed in parallel on subsets of these parameters. We validate the newly developed algorithm by comparison with controlledsource EM solutions for a 1D layered model. A 3D model with significant seafloor bathymetry variations and a heterogeneous subsurface demonstrates the code’s ability to model complex features.
During the past decade, the commercial investment in marine EM exploration has motivated many innovations in numerical techniques (Constable, 2010; Key, 2012). In particular, adaptive finite element methods (Key andWeiss, 2006; Li and Key, 2007; Ren et al., 2013) have received considerable attention since their unstructured modeling grids can readily accommodate highly complex geological features, such as seafloor topography and stratigraphic horizons. In addition to the ease of handling topography, another key benefit of unstructured grids is the ability to efficiently discretize multiple-scale structures.
Starting with a coarse model discretized by a grid of tetrahedral elements, adaptive methods seek to increase the solution accuracy by iteratively refining the grid, where each iteration consists of selecting a subset of elements for refinement based on an estimate of their contribution to the solution error, and then refining the grid by creating new smaller elements in these regions.
To measures the global contribution to the local error, we develop a goal-oriented error estimation approach using a sensitivity functional that measures how the error in one portion of the model corrupts the solution at the regions of interest, an effect referred to as pollution (Oden and Prudhomme, 2001). Refinement only occurs where the solution is inaccurate and where that inaccuracy corrupts the solution at the receivers’ locations.
Between 1997 and 2003 the Gemini Prospect, Gulf of Mexico, was used as a test ground for development of broadband marine magnetotellurics (MT). In 2003 controlled source electromagnetic (CSEM) data were acquired over Gemini using a prototype 200A transmitter on a profile that included earlier MT sites. In 2013 and 2014 these data were revisited as part of the evaluation of the recently developed Scripps 2D EM inversion/forward modeling code, MARE2DEM, developed largely by K. Key. A portion of the results of this evaluation are presented here with the objective that of examining aspects of the application of the inversion algorithm to real CSEM and MT data, rather than a detailed re-interpretation of the Gemini data set. Of order of 100 inversions were carried out as part of this study. The processed CSEM data were inverted for each of three frequencies individually and then for the three frequencies jointly, the MT data alone were inverted, and finally the multi-frequency CSEM and MT data were jointly inverted. Each of these data sets was subject to isotropic inversion, and then the joint CSEM/MT data were the subject of anisotropic inversion. Target misfits were varied and the results compared. Inversions were carried out with a half-space starting model as well as with more complex starting models. The results provide insight into the inversion outcome based on the effects of choice of data component to be used as input, the choice of starting model, target misfit selected, and the degree of anisotropy. The results imply that for CSEM and MT data collected at multiple frequencies, inverted models can change radically as different subsets of data are inverted individually or in combination, and with varying target misfit and/or anisotropy penalty.
Abstract An extensive marine controlled source electromagnetic (CSEM) data set was collected in the Gulf of Mexico targeting gas hydrate deposits at four geologically distinct areas within water depths that varied from 900 to 3000 m. The Joint Industry Project 2 drilled two of these locations, Green Canyon 955 and Walker Ridge 313, providing ground truth for the CSEM data. A third survey location, Mississippi Canyon 118 (MC118), is a designated hydrate observatory. We collected both traditional ocean bottom electromagnetic receiver data as well as continuous profiling data using a novel towed three-axis electric field receiver. The towed receiver measured data at a fixed offset of 300 m behind the transmitter, while the ocean bottom receivers recorded data over a range of offsets as the transmitter passed by each receiver. We inverted the CSEM data using a newly developed parallel goal-oriented adaptive finite element-modeling algorithm for efficient 2.5D imaging of the CSEM data. 2D inversions from MC118 are consistent with 1D apparent resistivity pseudosections and reveal resistive areas associated with the carbonate/hydrate mound. An extensive conductive region exists below this, associated with conductive brines sourced from a deeper more resistive salt body. Away from the mound the resistivity structure is a fairly uniform and homogeneous. We present new 2D inversions of the CSEM data that consider electrical anisotropy and constrained inversions that leverage structural control using key seismic horizons along the profiles.
Uncertainty in the transmitter position, theory error and insufficient model parameterization amongst various other factors can lead to significant correlated error in observed controlled source electromagnetic data. These errors come to light by an examination of the residuals after performing inversion. Since correlated error violates the assumption of independent data noise it can manifest in spurious structure in inverted models. We demonstrate this using both synthetic data and real data from Scarborough gas field, North West Australia. In this work we propose a method which uses a hierarchical Bayesian framework and reversible jump Markov chain Monte Carlo to account for correlated error. We find that this removes suspect structure from the inverted models and within reasonable prior bounds, provides information on the resolution of resistivity at depth.