The first Spanish Technological Development plant for CO2 storage is currently under development in Hontomín (Spain), in a fractured carbonate reservoir. The subsurface 3D geological structures of the Hontomín site were interpreted using well-log and 3D seismic reflection data. A shallow low velocity zone affects the wave propagation and decreases the coherency of the underlying seismic reflections, deteriorating the quality of the seismic data, and thus preventing a straightforward seismic interpretation. In order to provide a fully constrained model, a geologically supervised interpretation was carried out. In particular, a conceptual geological model was derived from an exhaustive well-logging analysis. This conceptual model was then improved throughout a detailed seismic facies analysis on selected seismic sections crossing the seismic wells and in consistency with the regional geology, leading to the interpretation of the entire 3D seismic volume. This procedure allowed characterizing nine main geological levels and four main fault sets. Thus, the stratigraphic sequence of the area and the geometries of the subsurface structures were defined. The resulting depth-converted 3D geological model allowed us to estimate a maximum CO2 storage capacity of 5.85 Mt. This work provides a 3D geological model of the Hontomín subsurface, which is a challenging case study of CO2 storage in a complex fractured carbonate reservoir.Jaume Almera agreement (ALM-09-027: Characterization, Development and Validation of Seismic Techniques applied to CO2 Geological Storage Sites) and by the European Union through the Technology Demonstration Plant of Compostilla OXYCFB300 Project (European Energy Programme for Recovery). Additional support has been provided by Spanish Ministry of Education Science (CSD2006-00041), Generalitat de Catalunya (2009SGR006) and CSIC JAE-Doc postdoctoral research contract (E.S.).Peer reviewe

The crustal structure and topography of the Moho boundary beneath the Atlas Mountains of Morocco has been constrained by a controlled source, wide‐angle seismic reflection transect: the SIMA experiment. This paper presents the first results of this project, consisting of an almost 700 km long, high‐resolution seismic profile acquired from the Sahara craton across the High and the Middle Atlas and the Rif Mountains. The interpretation of this seismic data set is based on forward modeling by raytracing, and has resulted in a detailed crustal structure and velocity model for the Atlas Mountains. Results indicate that the High Atlas features a moderate crustal thickness, with the Moho located at a minimum depth of 35 km to the S and at around 31 km to the N, in the Middle Atlas. Upper crustal shortening is resolved at depth through a crustal root where the Saharan crust underthrusts the northern Moroccan crust. This feature defines a lower crust imbrication that, locally, places the Moho boundary at ∼40–41 km depth in the northern part of the High Atlas. The P‐wave velocity model is characterized by relatively low velocities, mostly in the lower crust and upper mantle, when compared to other active orogens and continental regions. These low deep crustal velocities together with other geophysical observables such as conductivity estimates derived from MT measurements, moderate Bouguer gravity anomaly, high heat flow, and surface exposures of recent alkaline volcanism lead to a model where partial melts are currently emplaced at deep crustal levels and in the upper mantle. The resulting model supports the existence of a mantle upwelling as mechanism that would contribute significantly to sustain the High Atlas topography. However, the detailed Moho geometry deduced in this work should lead to a revision of the exact geometry and position of this mantle feature and will require new modeling efforts.

ALCUDIA is a 230 km long, vertical incidence deep seismic reflection transect acquired in spring 2007 across the southern Central Iberian Zone (part of the pre‐Mesozoic Gondwana paleocontinent) of the Variscan Orogen of Spain. The carefully designed acquisition parameters resulted in a 20 s TWTT deep, 60–90 fold, high‐resolution seismic reflection transect. The processed image shows a weakly reflective upper crust (the scarce reflectivity matching structures identified at surface), a thick, highly reflective and laminated lower crust, and a flat Moho located at 10 s TWTT (∼30 km depth). The transect can be divided into three segments with different structural styles in the lower crust. In the central segment, the lower crust is imaged by regular, horizontal and parallel reflectors, whereas in the northern and southern segments it displays oblique reflectors interpreted as an important thrust (north) and tectonic wedging involving the mantle (south). The ALCUDIA seismic image shows that in an intracontinental orogenic crust, far from the suture zones, the upper and lower crust may react differently to shortening in different sectors, which is taken as evidence for decoupling. The interpreted structures, as deduced from surface geology and the seismic image, show that deformation was distributed homogeneously in the upper crust, whereas it was concentrated in wedge/thrust structures at specific sectors in the lower crust. The seismic image also shows the location of late Variscan faults in spatial association with the lower crustal thickened areas.

Traveltime seismic tomography used to aid subway tunnel drilling in Barcelona, Spain, provides a detailed characterization of the shallow subsurface, including a complex network of faults and dikes. We encountered many difficulties while working in this urban setting, such as cultural noise and the inability to deploy instruments along much of the tunnel trace because of the street layout. Furthermore, the shallow subsurface is highly heterogeneous (because of gas and water lines, building foundations, and the sewage system), obscuring deeper structures. We acquired seismic data using a 10-s vibroseis sweep that provided relatively good signal-to-noise (S/N) ratio. First-arrival traveltime tomography proved to be a key tool to differentiate rock vol-umes characterized by different physical properties — in particular, the contact between the weathered upper layer and the more competent rock below. We interpreted the seismic results using surface geologic observations and borehole cores. Low seismic velocities (600–1200m/s) characterize the shallow part of the subsurface, representing quaternary sediments and weathered granite. Several high-velocity anomalies (up to 5500m/s) are interpreted as porphyritic dikes and are surrounded by low-velocity anomalies that correspond with fault systems that cut and displace the dikes. The tomographic velocity models also provide a detailed image of an important Miocene fault that intersects the tunnel trace. These results provide insights important for the drilling process.

This study aims to assess the feasibility of delineating and identifying mineral ores from hyperspectral images of tin–tungsten mine excavation faces using machine learning classification. We compiled a set of hand samples of minerals of interest from a tin–tungsten mine and analyzed two types of hyperspectral images: (1) images acquired with a laboratory set-up under close-to-optimal conditions, and (2) a scan of a simulated mine face using a field set-up, under conditions closer to those in the gallery. We have analyzed the following minerals: cassiterite (tin ore), wolframite (tungsten ore), chalcopyrite, malachite, muscovite, and quartz. Classification (Linear Discriminant Analysis, Singular Vector Machines and Random Forest) of laboratory spectra had a very high overall accuracy rate (98%), slightly lower if the 450–950 nm and 950–1650 nm ranges are considered independently, and much lower (74.5%) for simulated conventional RGB imagery. Classification accuracy for the simulation was lower than in the laboratory but still high (85%), likely a consequence of the lower spatial resolution. All three classification methods performed similarly in this case, with Random Forest producing results of slightly higher accuracy. The user’s accuracy for wolframite was 85%, but cassiterite was often confused with wolframite (user’s accuracy: 70%). A lumped ore category achieved 94.9% user’s accuracy. Our study confirms the suitability of hyperspectral imaging to record the spatial distribution of ore mineralization in progressing tungsten–tin mine faces.