Characterisation of the transmissivity field of a fractured and karstic aquifer, Southern France

International audienceGeological and hydrological data collected at the Terrieu experimental site north of Montpellier, in a confined carbonate aquifer indicates that both fracture clusters and a major bedding plane form the main flow paths of this highly heterogeneous karst aquifer. However, characterising the geometry and spatial location of the main flow channels and estimating their flow properties remain difficult. These challenges can be addressed by solving an inverse problem using the available hydraulic head data recorded during a set of interference pumping tests.We first constructed a 2D equivalent porous medium model to represent the test site domain and then employed regular zoning parameterisation, on which the inverse modelling was performed. Because we aim to resolve the fine-scale characteristics of the transmissivity field, the problem undertaken is essentially a large-scale inverse model, i.e. the dimension of the unknown parameters is high. In order to deal with the high computational demands in such a large-scale inverse problem, a gradient-based, non-linear algorithm (SNOPT) was used to estimate the transmissivity field on the experimental site scale through the inversion of steady-state, hydraulic head measurements recorded at 22 boreholes during 8 sequential cross-hole pumping tests. We used the data from outcrops, borehole fracture measurements and interpretations of inter-well connectivities from interference test responses as initial models to trigger the inversion. Constraints for hydraulic conductivities, based on analytical interpretations of pumping tests, were also added to the inversion models. In addition, the efficiency of the adopted inverse algorithm enables us to increase dramatically the number of unknown parameters to investigate the influence of elementary discretisation on the reconstruction of the transmissivity fields in both synthetic and field studies.By following the above approach, transmissivity fields that produce similar hydrodynamic behaviours to the real head measurements were obtained. The inverted transmissivity fields show complex, spatial heterogeneities with highly conductive channels embedded in a low transmissivity matrix region. The spatial trend of the main flow channels is in a good agreement with that of the main fracture sets mapped on outcrops in the vicinity of the Terrieu site suggesting that the hydraulic anisotropy is consistent with the structural anisotropy. These results from the inverse modelling enable the main flow paths to be located and their hydrodynamic properties to be estimated

Performances of the Italian seismic network, 1985-2002: the hidden thing

Seismic data users and people managing a sesimic network are both interested in the potentiality of the data, with the difference that the former look at stability, the second at improvements. In this work we measure the performances of the Italian Telemetered Seismic Network in 1985-2002 by defining basic significant parameters and studying their evolution during the years. Then, we deal with the geological methods used to characterise or to plan a seismic station deployment in a few cases. Last, we define the gain of the network as the percentage of located earthquakes with respect to the total recorded earthquakes. By analysing the distribution of non-located ("missed") earthquakes, we suggest possible actions to take in order to increase the gain. Results show that completeness magnitude is 2.4 in the average over the analysed period, and it can be as low as 2.2 when we consider non-located earthquakes as well. Parameters such as the distance between an earthquake and the closest station, and the RMS location decrease with time, reflecting improvements in the location quality. Methods for geologic and seismological characterisation of a possible station site also proved to be effective. Finally, we represent the number of missed earthquakes at each station, showing that nine stations control more that 50% of all missed earthquakes, and suggesting areas in Italy where the network might be easily improved.Comment: 17 pages, 1 table, 11 figures. Submitted to Annals of Geophysic

Stratigraphic variations control deformation patterns in evaporite basins : Messinian examples, onshore and offshore Sicily (Italy)

Acknowledgements and Funding We are grateful to Ente Minerario Siciliano and Italkali for the provision of extensive subsurface data from Realmonte, Corvillo and Mandre areas. We thank F. Peel and an anonymous referee for comments. Seismic reflection data are available for inspection and interpretation at the Virtual Seismic Atlas (www. seismicatlas.org). R.M. acknowledges a MIUR Cofin-PRIN 2010–2011 grant.Peer reviewedPublisher PD

Quasi-Newton inversion of seismic first arrivals using source finite bandwidth assumption: Application to subsurface characterization of landslides

International audienceCharacterizing the internal structure of landslides is of first importance to assess the hazard. Many geophysical techniques have been used in the recent years to image these structures, and among them is seismic tomography. The objective of this work is to present a high resolution seismic inversion algorithm of first arrival times that minimizes the use of subjective regularization operators. A Quasi-Newton P-wave tomography inversion algorithm has been developed. It is based on a finite frequency assumption for highly heterogeneous media which considers an objective inversion regularization (based on the wave propagation principle) and uses the entire source frequency spectrum to improve the tomography resolution. The Fresnel wavepaths calculated for different source frequencies are used to retropropagate the traveltime residuals, assuming that in highly heterogeneous media, the first arrivals are only affected by velocity anomalies present in the first Fresnel zone. The performance of the algorithm is first evaluated on a synthetic dataset, and further applied on a real dataset acquired at the Super-Sauze landslide which is characterized by a complex bedrock geometry, a layering of different materials and important changes in soil porosity (e.g. surface fissures). The seismic P-wave velocity and the wave attenuation are calculated, and the two tomographies are compared to previous studies on the site

A locally adaptive kernel regression method for facies delineation

Facies delineation is defined as the separation of geological units with distinct intrinsic characteristics (grain size, hydraulic conductivity, mineralogical composition). A major challenge in this area stems from the fact that only a few scattered pieces of hydrogeological information are available to delineate geological facies. Several methods to delineate facies are available in the literature, ranging from those based only on existing hard data, to those including secondary data or external knowledge about sedimentological patterns. This paper describes a methodology to use kernel regression methods as an effective tool for facies delineation. The method uses both the spatial and the actual sampled values to produce, for each individual hard data point, a locally adaptive steering kernel function, self-adjusting the principal directions of the local anisotropic kernels to the direction of highest local spatial correlation. The method is shown to outperform the nearest neighbor classification method in a number of synthetic aquifers whenever the available number of hard data is small and randomly distributed in space. In the case of exhaustive sampling, the steering kernel regression method converges to the true solution. Simulations ran in a suite of synthetic examples are used to explore the selection of kernel parameters in typical field settings. It is shown that, in practice, a rule of thumb can be used to obtain suboptimal results. The performance of the method is demonstrated to significantly improve when external information regarding facies proportions is incorporated. Remarkably, the method allows for a reasonable reconstruction of the facies connectivity patterns, shown in terms of breakthrough curves performance

Look ahead of the bit while drilling: potential impacts and challenges in the McMurray Formation

International audienceThe oil and gas industry, operating and service companies, and academia are actively looking for ways to see ahead of the drillbit while drilling to reduce the risks and costs of the operation and improve the well-placement process. Optimal drilling in the challenging and highly heterogeneous reservoirs, where geological interpretations overlook the high-frequency variations in the rock properties, requires reliable subsurface information from around and ahead of the drillbit. To provide this, we have developed a seismic-while-drilling imaging algorithm based on signal processing, drillstring modeling, and pre-stack wave-equation migration. To extend the visibility ahead-of-the-bit, we use the drillbit as a seismic source and image the changes in acoustic properties of rocks both around and ahead of the drillbit. The common practice is to build a reverse vertical seismic profile (R-VSP) gathers. Here, we use a blind deconvolution algorithm to estimate the drillbit source signature from the data directly. Alternatively, we can estimate such a signature through drillstring modeling and top-drive measurements (i.e., force and velocity). The drillstring dynamics is modeled by using Riemann's invariants and a backstepping approach. Next, we input the estimated source signature to the pre-stack wave-equation depth imaging workflow. Our simulations show that providing drillbit source signature to the pre-stack wave equation depth migration consistently delivers reliable subsurface images around and ahead of the drillbit. The output of our workflow is a high-resolution subsurface image that provides vital information in oil sands reservoirs for placement of steam assisted gravity drainage (SAGD) well pairs. Compared to conventional practices, the proposed methodology images around and ahead of the drillbit enabling interactive decision making and optimal well-placement. The key feature of the presented methodology is that instead of cross-correlating the seismic-while-drilling data with the pilot trace and building R-VSP gathers, we use the estimated drillbit source signature and deliver high-resolution pre-stack depth migrated images. Through numerical modeling, we tested the potential impacts, validity, and challenges of the proposed methodology in drilling horizontal wells in SAGD settings with an emphasis on the McMurray Formation. We further compared the results with the conventional drilling practice. In contrast to existing tools that have limited depth of penetration, interpreting seismic-while-drilling data in real-tim

Surrogate regression modelling for fast seismogram generation and detection of microseismic events in heterogeneous velocity models

This is the author accepted manuscript. The final version is available from Oxford University Press (OUP) via the DOI in this record.Given a 3D heterogeneous velocity model with a few million voxels, fast generation of accurate seismic responses at specified receiver positions from known microseismic event locations is a well-known challenge in geophysics, since it typically involves numerical solution of the computationally expensive elastic wave equation. Thousands of such forward simulations are often a routine requirement for parameter estimation of microseimsic events via a suitable source inversion process. Parameter estimation based on forward modelling is often advantageous over a direct regression-based inversion approach when there are unknown number of parameters to be estimated and the seismic data has complicated noise characteristics which may not always allow a stable and unique solution in a direct inversion process. In this paper, starting from Graphics Processing Unit (GPU) based synthetic simulations of a few thousand forward seismic shots due to microseismic events via pseudo-spectral solution of elastic wave equation, we develop a step-by-step process to generate a surrogate regression modelling framework, using machine learning techniques that can produce accurate seismograms at specified receiver locations. The trained surrogate models can then be used as a high-speed meta-model/emulator or proxy for the original full elastic wave propagator to generate seismic responses for other microseismic event locations also. The accuracies of the surrogate models have been evaluated using two independent sets of training and testing Latin hypercube (LH) quasi-random samples, drawn from a heterogeneous marine velocity model. The predicted seismograms have been used thereafter to calculate batch likelihood functions, with specified noise characteristics. Finally, the trained models on 23 receivers placed at the sea-bed in a marine velocity model are used to determine the maximum likelihood estimate (MLE) of the event locations which can in future be used in a Bayesian analysis for microseismic event detection.This work has been supported by the Shell Projects and Technology. The Wilkes high performance GPU computing service at the University of Cambridge has been used in this work