Joint inversion scheme with an adaptive coupling strategy - applications on synthetic and real data sets

Joint inversion strategies for geophysical data have become increasingly popular since they allow to combine complementary information from different data sets in an efficient way. However, for joint inversion algorithms that use methods that are sensitive to different parameters it is important that they are not restricted to specific survey arrays and subsurface conditions. Hence, joint inversion schemes are needed that 1) adequately balance data from the different methods and 2) use links between the parameter models that are suited for a wide range of applications. Here, we combine MT, seismic tomography and gravity data in a non-linear joint inversion that accounts for these critical issues. Data from the different methods are inverted separately and are joined through constrains accounting for parameter relationships. An advantage of performing the inversions separately (and not together in one matrix) is that no relative weighting between the data sets is required. To avoid that the convergence behavior of the inversions is profoundly disturbed by the coupling, the strengths of the associated constraints are re-adjusted at each iteration. As criteria to control the adaption of the coupling strengths we used a general version of the well-known discrepancy principle. Adaption of the coupling strengths makes the joint inversion scheme also applicable to subsurface conditions, for which the assumed relationships are only a rough first order approximation. So, the coupling between the different parameter models is automatically reduced if for some structures the true rock property behaviors differ significantly from the assumed relationships (e.g. the atypical density-velocity behavior of salt). We have tested our scheme first on different synthetic 2-D models for which the assumed parameter relationships are everywhere valid. We observe that the adaption of the coupling strengths makes the convergence of the inversions very robust and that the final results are close to the true models. In a next step the scheme has been applied on models for which the assumed parameter relationships are invalid for some structures. For these structures deviations from the relationships are present in the final results; however, for the remaining structures the relative behaviors of the physical parameters are still approximately described by the assumed relationship. Finally, we applied our joint inversion scheme on seismic, MT and gravity data collected offshore the Faroe Islands, where basalt intrusions are present

Seismic wave propagation around subsurface igneous sill complexes

Acknowledgements This work was undertaken during O.G.S’s PhD at Durham University, funded by Eni through the Volcanic Margins Research Consortium (Phase 2). Seismic modelling was performed using the open source SOFI2D (Bohlen 2002) and post-processed using Seismic Un*x (Stockwell & Cohen 2012). Figures were prepared using the open source Generic Mapping Tools (GMT) (Wessel & Smith W. H. F. 1998) and Seismic Un*x. Zoeppritz amplitude coefficients were calculated using the CREWES Matlab toolbox of the University of Calgary (Margrave and Lamoureux 2019). This work made use of the facilities of the Hamilton HPC Service of Durham UniversityPeer reviewe

Seismic oceanography imaging of thermal intrusions in strong frontal regions

The Naval Research Laboratory and collaborating partners carried out two dedicated seismic oceanography field experiments in two very different strong frontal regions. ADRIASEISMIC took seismic oceanography measurements at the confluence of North Adriatic Dense Water advected along the Western Adriatic Current and Modified Levantine Intermediate Water advected around the topographic rim of the Southern Adriatic basin. ARC12 took seismic oceanography measurements in and around the Agulhas Return Current as it curved northwards past the Agulhas Plateau and interacted with a large anticyclone that had collided with the current. Despite one study focused on coastal boundary currents and the other focused on a major Western Boundary Current extension, the complex horizontal structures seen through seismic imaging are tied to the processes of thermal intrusions and interleaving in both systems. Seismic Oceanography provides a unique capability of tracking the fine-scale horizontal extent of these intrusions

3-D cross-gradient joint inversion of seismic refraction and DC resistivity data

We present a 3-D cross-gradient joint inversion algorithm for seismic refraction and DC resistivity data. The structural similarity between seismic slowness and resistivity models is enforced by a cross-gradient term in the objective function that also includes misfit and regularization terms. A limited memory quasi-Newton approach is used to perform the optimization of the objective function. To validate the proposed methodology and its implementation, tests were performed on a typical archaeological geophysical synthetic model. The results show that the inversion model and physical parameters estimated by our joint inversion method are more consistent with the true model than those from single inversion algorithm. Moreover, our approach appears to be more robust in conditions of noise. Finally, the 3-D cross-gradient joint inversion algorithm was applied to the field data from Lin_an ancient city site in Hangzhou of China. The 3-D cross-gradient joint inversion models are consistent with the archaeological excavation results of the ancient city wall remains. However, by single inversion, seismic slowness model does not show the anomaly of city wall remains and resistivity model does not fit well with the archaeological excavation results. Through these comparisons, we conclude that the proposed algorithm can be used to jointly invert 3-D seismic refraction and DC resistivity data to reduce the uncertainty brought by single inversion schem

A sequential dynamic Bayesian network for pore pressure estimation with uncertainty quantification

Pore-pressure estimation is an important part of oil-well drilling, since drilling into unexpected highly pressured fluids can be costly and dangerous. However, standard estimation methods rarely account for the many sources of uncertainty, or for the multivariate nature of the system. We propose the pore pressure sequential dynamic Bayesian network (PP SDBN) as an appropriate solution to both these issues. The PP SDBN models the relationships between quantities in the pore pressure system, such as pressures, porosity, lithology and wireline log data, using conditional probability distributions based on geophysical relationships to capture our uncertainty about these variables and the relationships between them. When wireline log data is given to the PP SDBN, the probability distributions are updated, providing an estimate of pore pressure along with a probabilistic measure of uncertainty that reflects the data acquired and our understanding of the system. This is the advantage of a Bayesian approach. Our model provides a coherent statistical framework for modelling the pore pressure system. The specific geophysical relationships used can be changed to better suit a particular setting, or reflect geoscientists’ knowledge. We demonstrate the PP SDBN on an offshore well from West Africa. We also perform a sensitivity analysis, demonstrating how this can be used to better understand the working of the model and which parameters are the most influential. The dynamic nature of the model makes it suitable for real time estimation during logging while drilling. The PP SDBN models shale pore pressure in shale rich formations with mechanical compaction as the overriding source of overpressure. The PP SDBN improves on existing methods since it produces a probabilistic estimate that reflects the many sources of uncertainty present

Stochastic Heterogeneity Mapping as a tool to quantify turbulence in reflectivity layers of thermohaline staircases in the Tyrrhenian Sea

European Geosciences Union General Assembly 2013, 7-12 April 2013, Vienna, AustriaProcessed multi-channel seismic data acquired in the Tyrrhenian Sea in April-May 2010 with the B/O Sarmiento de Gamboa provide images of oceanic thermohaline staircases. Thermohaline staircases are regular, well-defined step-like variations in vertical profiles of temperature and salinity. In the ocean they are thought to be the result of double diffusion driven by the two order of magnitude difference in the diffusivities of heat and salt. Staircases are believed to have an anomalously weak internal wave-induced turbulence, making them suitable for the estimation of a lower limit of turbulent disturbances detectable by multi-channel seismics. We apply stochastic heterogeneity mapping based on the band-limited von Kármán function to post-stack time-migrated seismic data to extract stochastic parameters such as the Hurst number (a measure of reflection interface roughness) and correlation length (scale length). For scale sizes smaller than the correlation length, the von Kármán model describes a power law (fractal) process where the Hurst number is its exponent. We present the results of our analysis corroborated by benchmark tests performed on synthetic seismic data generated from random fractal surfaces. The synthetic tests are found to verify the robustness of the technique. Lower Hurst numbers represent a richer range of high wavenumbers and therefore correspond to a broader range of heterogeneity in reflection events. We interpret a broader range of heterogeneity as indicative of a greater degree of turbulence. Some areas of the seismic data show a spatial variation in Hurst number across several frequency bands that may indicate some preferential coupling of energy at different depthsPeer Reviewe

AXSIS: Exploring the frontiers in attosecond X-ray science, imaging and spectroscopy

X-ray crystallography is one of the main methods to determine atomic-resolution 3D images of the whole spectrum of molecules ranging from small inorganic clusters to large protein complexes consisting of hundred-thousands of atoms that constitute the macromolecular machinery of life. Life is not static, and unravelling the structure and dynamics of the most important reactions in chemistry and biology is essential to uncover their mechanism. Many of these reactions, including photosynthesis which drives our biosphere, are light induced and occur on ultrafast timescales. These have been studied with high time resolution primarily by optical spectroscopy, enabled by ultrafast laser technology, but they reduce the vast complexity of the process to a few reaction coordinates. In the AXSIS project at CFEL in Hamburg, funded by the European Research Council, we develop the new method of attosecond serial X-ray crystallography and spectroscopy, to give a full description of ultrafast processes atomically resolved in real space and on the electronic energy landscape, from co-measurement of X-ray and optical spectra, and X-ray diffraction. This technique will revolutionize our understanding of structure and function at the atomic and molecular level and thereby unravel fundamental processes in chemistry and biology like energy conversion processes. For that purpose, we develop a compact, fully coherent, THz-driven attosecond X-ray source based on coherent inverse Compton scattering off a free-electron crystal, to outrun radiation damage effects due to the necessary high X-ray irradiance required to acquire diffraction signals. This highly synergistic project starts from a completely clean slate rather than conforming to the specifications of a large free-electron laser (FEL) user facility, to optimize the entire instrumentation towards fundamental measurements of the mechanism of light absorption and excitation energy transfer. A multidisciplinary team formed by laser-, accelerator,- X-ray scientists as well as spectroscopists and biochemists optimizes X-ray pulse parameters, in tandem with sample delivery, crystal size, and advanced X-ray detectors. Ultimately, the new capability, attosecond serial X-ray crystallography and spectroscopy, will be applied to one of the most important problems in structural biology, which is to elucidate the dynamics of light reactions, electron transfer and protein structure in photosynthesis.United States. Air Force. Office of Scientific Research (Contract FA9550-12-1-0499)American Society for Engineering Education. National Defense Science and Engineering Graduate Fellowshi

Seismic reflection imaging of mixing processes in Fram Strait

The West Spitsbergen Current, which flows northward along the western Svalbard continental slope, transports warm and saline Atlantic water (AW) into the Arctic Ocean. A combined analysis of high-resolution seismic images and hydrographic sections across this current has uncovered the oceanographic processes involved in horizontal and vertical mixing of AW. At the shelf break, where a strong horizontal temperature gradient exists east of the warmest AW, isopycnal interleaving of warm AW and surrounding colder waters is observed. Strong seismic reflections characterize these interleaving features, with a negative polarity reflection arising from an interface of warm water overlying colder water. A seismic-derived sound speed image reveals the extent and lateral continuity of such interleaving layers. There is evidence of obliquely aligned internal waves emanating from the slope at 450–500 m. They follow the predicted trajectory of internal S2 tidal waves and can promote vertical mixing between Atlantic and Arctic-origin waters

Change in glomerular filtration rate over time in the Oxford Renal Cohort Study:observational study

Background: Decline in kidney function can result in adverse health outcomes. The Oxford Renal Cohort Study has detailed baseline assessments from 884 participants ≥60 years of age. Aim: To determine the proportion of participants with a decline in estimated glomerular filtration rate (eGFR), identify determinants of decline, and determine proportions with chronic kidney disease (CKD) remission. Design and setting: Observational cohort study in UK primary care. Method: Data were used from baseline and annual follow-up assessments to monitor change in kidney function. Rapid eGFR decline was defined as eGFR decrease &gt;5 ml/min/1.73 m2/year, improvement as eGFR increase &gt;5 ml/min/1.73 m2/year, and remission in those with CKD at baseline and eGFR &gt;60 ml/min/1.73 m2 during follow-up. Cox proportional hazard models were used to identify factors associated with eGFR decline. Results: There was a net decline in eGFR in the 884 participants over 5 years of follow-up. In 686 participants with &gt;2 eGFR tests with a median follow-up of 2.1 years, 164 (24%) evidenced rapid GFR decline, 185 (27%) experienced eGFR improvement, and 82 of 394 (21%) meeting CKD stage 1-4 at baseline experienced remission. In the multivariable analysis, smoking status, higher systolic blood pressure, and being known to have CKD at cohort entry were associated with rapid GFR decline. Those with CKD stage 3 at baseline were less likely to exhibit GFR decline compared with normal kidney function. Conclusion: This study established that 24% of people evidenced rapid GFR decline whereas 21% evidenced remission of CKD. People at risk of rapid GFR decline may benefit from closer monitoring and appropriate treatment to minimise risks of adverse outcomes, although only a small proportion meet the National Institute for Health and Care Excellence criteria for referral to secondary care.</p