@article{RumpfTronicke2015,
  author    = {Rumpf, Michael and Tronicke, Jens},
  title     = {Assessing uncertainty in refraction seismic traveltime inversion using a global inversion strategy},
  series = {Geophysical prospecting},
  volume    = {63},
  journal   = {Geophysical prospecting},
  number    = {5},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {0016-8025},
  doi       = {10.1111/1365-2478.12240},
  pages     = {1188 -- 1197},
  year      = {2015},
  abstract  = {To analyse and invert refraction seismic travel time data, different approaches and techniques have been proposed. One common approach is to invert first-break travel times employing local optimization approaches. However, these approaches result in a single velocity model, and it is difficult to assess the quality and to quantify uncertainties and non-uniqueness of the found solution. To address these problems, we propose an inversion strategy relying on a global optimization approach known as particle swarm optimization. With this approach we generate an ensemble of acceptable velocity models, i.e., models explaining our data equally well. We test and evaluate our approach using synthetic seismic travel times and field data collected across a creeping hillslope in the Austrian Alps. Our synthetic study mimics a layered near-surface environment, including a sharp velocity increase with depth and complex refractor topography. Analysing the generated ensemble of acceptable solutions using different statistical measures demonstrates that our inversion strategy is able to reconstruct the input velocity model, including reasonable, quantitative estimates of uncertainty. Our field data set is inverted, employing the same strategy, and we further compare our results with the velocity model obtained by a standard local optimization approach and the information from a nearby borehole. This comparison shows that both inversion strategies result in geologically reasonable models (in agreement with the borehole information). However, analysing the model variability of the ensemble generated using our global approach indicates that the result of the local optimization approach is part of this model ensemble. Our results show the benefit of employing a global inversion strategy to generate near-surface velocity models from refraction seismic data sets, especially in cases where no detailed a priori information regarding subsurface structures and velocity variations is available.},
  language  = {en}
}
@article{RumpfTronicke2014,
  author    = {Rumpf, Michael and Tronicke, Jens},
  title     = {Predicting 2D geotechnical parameter fields in near-surface sedimentary environments},
  series = {Journal of applied geophysics},
  volume    = {101},
  journal   = {Journal of applied geophysics},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0926-9851},
  doi       = {10.1016/j.jappgeo.2013.12.002},
  pages     = {95 -- 107},
  year      = {2014},
  abstract  = {For a detailed characterization of near-surface environments, geophysical techniques are increasingly used to support more conventional point-based techniques such as borehole and direct-push logging. Because the underlying parameter relations are often complex, site-specific, or even poorly understood, a remaining challenging task is to link the geophysical parameter models to the actual geotechnical target parameters measured only at selected points. We propose a workflow based on nonparametric regression to establish functional relationships between jointly inverted geophysical parameters and selected geotechnical parameters as measured, for example, by different borehole and direct-push tools. To illustrate our workflow, we present field data collected to characterize a near-surface sedimentary environment Our field data base includes crosshole ground penetrating radar (GPR), seismic P-, and S-wave data sets collected between 25 m deep boreholes penetrating sand- and gravel dominated sediments. Furthermore, different typical borehole and direct-push logs are available. We perform a global joint inversion of traveltimes extracted from the crosshole geophysical data using a recently proposed approach based on particle swarm optimization. Our inversion strategy allows for generating consistent models of GPR, P-wave, and S-wave velocities including an appraisal of uncertainties. We analyze the observed complex relationships between geophysical velocities and target parameter logs using the alternating conditional expectation (ACE) algorithm. This nonparametric statistical tool allows us to perform multivariate regression analysis without assuming a specific functional relation between the variables. We are able to explain selected target parameters such as characteristic grain size values or natural gamma activity by our inverted geophysical data and to extrapolate these parameters to the inter-borehole plane covered by our crosshole experiments. We conclude that the ACE algorithm is a powerful tool to analyze a multivariate petrophysical data base and to develop an understanding of how a multi-parameter geophysical model can be linked and translated to selected geotechnical parameters.},
  language  = {en}
}
@article{TomasZitzmannHomannetal.2010,
  author    = {Tomas, Sara and Zitzmann, Max and Homann, Martin and Rumpf, Michael and Amour, Frederic and Benisek, Merle-Friederike and Betzler, Christian and Mutti, Maria},
  title     = {From ramp to platform : building a 3D model of depositional geometries and facies architectures in transitional carbonates in the Miocene, northern Sardinia},
  issn      = {0172-9179},
  doi       = {10.1007/s10347-009-0203-7},
  year      = {2010},
  abstract  = {The depositional geometry and facies distribution of an Early Miocene (Burdigalian) carbonate system in the Perfugas Basin (NW Sardinia) comprise a well-exposed example of a transition from a ramp to a steep-flanked platform. The carbonate succession (Sedini Limestone Unit) is composed of two depositional sequences separated by a major erosional unconformity. The lower (sequence 1) records a ramp dominated by heterozoan producers and the upper (sequence 2) is dominated by photozoan producers and displays a gradual steepening of the depositional profile into a steep- flanked platform. This paper shows the process of creating a digital outcrop model including a facies model. This process consists of combining field data sets, including 17 sedimentary logs, and a spatial dataset consisting of differential global positioning system data points measured along key stratigraphic surfaces and sedimentary logs, with the goal of locking traditional field observations into a 3D spatial model. Establishing a precise geometrical framework and visualizing the overall change in the platform geometry and the related vertical and lateral facies variations of the Sedini carbonate platform, allows us to better understand the sedimentary processes leading to the geometrical turn- over of the platform. Furthermore, a detailed facies modeling helps us to gain insight into the detailed depositional dynamics. The final model reproduces faithfully the depositional geometries observed in the outcrops and helps in understanding the relationships between facies and architectural framework at the basin scale. Moreover, it provides the basis to characterize semiquantitatively regional sedimentological features and to make further reservoir and subsurface analogue studies.},
  language  = {en}
}