Acquisition Grid Research Articles

Efficient magnetotelluric data acquisition using irregular stations and compressive sensing reconstruction

A major challenge in magnetotelluric (MT) surveys is the limited number of stations that can be collected due to the cost of receiver instrumentation and the time required to deploy them in large numbers. Many equal-distance acquisition grid used in MT surveys are either over sampling or faced with severe aliasing. We have applied the compressive sensing theory to MT acquisition and developed an efficient acquisition approach that uses optimized station layout with sparse irregular patterns. This acquisition strategy uses the optimized survey designs to acquire a sparse data set first, and then applies a compressive sensing reconstruction to obtain the equivalent dense data set on a regularly spaced grid. Once reconstructed, the dense data can be used in the traditional manner in the subsequent steps of processing, inversion, and interpretation. Our simulations show that comparable information can be obtained as that from a full regular grid in exploration settings by using as fewer as 25% stations. Furthermore, redeploying the same number of stations in a coarse grid used crustal studies can collect much more information. This new acquisition approach can lead to significant savings in both the acquisition cost and operational time and to maximized information from a given number of stations. The substantial savings in the cost, or the increase in the information content, could make many geoscientific investigations viable that might otherwise be impossible due to limited budget.

A comparative study on the effect of grid printing methods and camera hardware in automatic strain measurement through CGA

Strain analysis is an important step in sheet metal forming operations to identify the potential locations of failure. Circle grid analysis is a widely used method to evaluate the strains in sheet metal forming, where deformed circles on a formed component are measured to evaluate the strains at different locations. In this paper, two different USB cameras are used to capture the images of the deformed grids. The images are processed using the in-house software developed in MATLAB for strain measurement. The effect of image acquisition hardware and grid printing methods on strain measurement accuracy has been analyzed. For this, the sheets are printed with circular grids by screen printing, laser engraving, and electrochemical etching. The sheets are then deformed in incremental forming to produce different levels of strain in the formed components. The deformed grids on the formed components are captured using proposed USB cameras with appropriate attachments and processed by in-house strain measurement software. The strain measured using proposed hardware and software is also compared with the commercial strain measurement system. The mean absolute percentage error in strain measurement with the proposed USB cameras was found to be 0.671 and 0.761. The statistical results show that there is no evidence to support the hypothesis that the two hardware perform differently on average. Hence, the proposed hardware and software can be used in industry and research laboratories for strain analysis in sheet metal forming operations.

Machine learning for the prediction and Analysis of Bouguer Gravity anomaly of the Kiri uplift in Congo sedimentary Basin

Bouguer gravity anomalies (BGA) play an important role in exploration of mineral resources. Allowing the delineation of large geological structures, BGA participate into discovery of the deposits. However, the Kiri uplift region where several oil seeps have been recognized faces sparse coverage of data due to the difficult conditions of data acquisition on the field. This situation increases the non-uniqueness and nonlinearity problems of the solution using inverse methods. Although, potentially good at quantifying uncertainties, inverse approaches involve enormous computational tasks. We used machine-learning algorithms to predict and analyze gravity data in Kiri uplift region. The algorithms learned to perform as a multiple regression. During training steps, each independent variable included X and Y coordinates, digital elevation model (DEM) and geology. BGA values calculated by experts were provided as the dependent variables. K-fold cross-validation has been used ensure the models are well fit. Since the well-trained algorithms should result in small losses and errors, we experimented several optimizers. By comparison, testing results showed that deep neural network-based algorithm (DNN) has proven to be the most efficient with 5.37 Mean Squared Error and 1.75 Mean Absolute Error as model metrics. DNN showed the most accurate prediction, which, together with the measured BGA reported strongest Pearson correlation coefficient of 0.996. In addition, analysis showed that DNN result is one that conforms perfectly to the regional geology information of the study area. Machine learning algorithms proved their effectiveness to predict and analyze BGA in the study area.ML algorithms proved their effectiveness to predict BGA where measurements lackedThe joint analysis of predicted, measured and regional lithology meets expectationsAs predictors are X, Y, DEM and, lithology, we can customize the acquisition grids

Autonomous Airborne 3D SAR Imaging System for Subsurface Sensing: UWB-GPR on Board a UAV for Landmine and IED Detection

This work presents an enhanced autonomous airborne Synthetic Aperture Radar (SAR) imaging system able to provide full 3D radar images from the subsurface. The proposed prototype and methodology allow the safe detection of both metallic and non-metallic buried targets even in difficult-to-access scenarios without interacting with the ground. Thus, they are particularly suitable for detecting dangerous targets, such as landmines and Improvised Explosive Devices (IEDs). The prototype is mainly composed by an Ultra-Wide-Band (UWB) radar module working from Ultra-High-Frequency (UHF) band and a high accuracy dual-band Real Time Kinematic (RTK) positioning system mounted on board an Unmanned Aerial Vehicle (UAV). The UAV autonomously flies over the region of interest, gathering radar measurements. These measurements are accurately geo-referred so as to enable their coherent combination to obtain a well-focused SAR image. Improvements in the processing chain are also presented in order to deal with some issues associated to UAV-based measurements (such as non-uniform acquisition grids) as well as to enhance the resolution and the signal to clutter ratio of the image. Both the prototype and the methodology were validated with measurements, showing their capability to provide high-resolution 3D SAR images.

Unmanned aerial system for antenna measurement and diagnosis: evaluation and testing

This contribution analyses the performance of an unmanned aerial system for antenna measurement (UASAM) for different kinds of measurement scenarios. UASAM is conceived for antenna diagnostics and characterisation at the operational location of the antenna under test (AUT). The system measures the amplitude of the near field radiated by the AUT. Then, these measurements are post-processed using phase retrieval techniques and equivalent currents methods to obtain an electromagnetic model of the AUT. This model can be used for antenna diagnostics and for evaluating the far field pattern. Similar to antenna measurement systems in anechoic chamber, UASAM allows defining different acquisition grids depending on the type of AUT (planar, cylindrical, arc cylindrical), which also influences the flight time. In addition to this, the capability to measure circularly polarised antennas from amplitude-only measurements is presented, discussing the limitations found during the tests, and comparing the results with those from measurements at a spherical range in an anechoic chamber.

Advanced 3D Photogrammetric Surface Reconstruction of Extensive Objects by UAV Camera Image Acquisition.

This paper proposes a replicable methodology to enhance the accuracy of the photogrammetric reconstruction of large-scale objects based on the optimization of the procedures for Unmanned Aerial Vehicle (UAV) camera image acquisition. The relationships between the acquisition grid shapes, the acquisition grid geometric parameters (pitches, image rates, camera framing, flight heights), and the 3D photogrammetric surface reconstruction accuracy were studied. Ground Sampling Distance (GSD), the necessary number of photos to assure the desired overlapping, and the surface reconstruction accuracy were related to grid shapes, image rate, and camera framing at different flight heights. The established relationships allow to choose the best combination of grid shapes and acquisition grid geometric parameters to obtain the desired accuracy for the required GSD. This outcome was assessed by means of a case study related to the ancient arched brick Bridge of the Saracens in Adrano (Sicily, Italy). The reconstruction of the three-dimensional surfaces of this structure, obtained by the efficient Structure-From-Motion (SfM) algorithms of the commercial software Pix4Mapper, supported the study by validating it with experimental data. A comparison between the surface reconstruction with different acquisition grids at different flight heights and the measurements obtained with a 3D terrestrial laser and total station-theodolites allowed to evaluate the accuracy in terms of Euclidean distances.

Optimized survey design for electrical resistivity tomography: combined optimization of measurement configuration and electrode placement

Author(s): Uhlemann, S; Wilkinson, PB; Maurer, H; Wagner, FM; Johnson, TC; Chambers, JE | Abstract: Within geoelectrical imaging, the choice of measurement configurations and electrode locations is known to control the image resolution. Previous work has shown that optimized survey designs can provide a model resolution that is superior to standard survey designs. This paper demonstrates a methodology to optimize resolution within a target area, while limiting the number of required electrodes, thereby selecting optimal electrode locations. This is achieved by extending previous work on the 'Compare-R' algorithm, which by calculating updates to the resolution matrix optimizes the model resolution in a target area. Here, an additional weighting factor is introduced that allows to preferentially adding measurement configurations that can be acquired on a given set of electrodes. The performance of the optimization is tested on two synthetic examples and verified with a laboratory study. The effect of the weighting factor is investigated using an acquisition layout comprising a single line of electrodes. The results show that an increasing weight decreases the area of improved resolution, but leads to a smaller number of electrode positions. Imaging results superior to a standard survey design were achieved using 56 per cent fewer electrodes. The performance was also tested on a 3-D acquisition grid, where superior resolution within a target at the base of an embankment was achieved using 22 per cent fewer electrodes than a comparable standard survey. The effect of the underlying resistivity distribution on the performance of the optimization was investigated and it was shown that even strong resistivity contrasts only have minor impact. The synthetic results were verified in a laboratory tank experiment, where notable image improvements were achieved. This work shows that optimized surveys can be designed that have a resolution superior to standard survey designs, while requiring significantly fewer electrodes. This methodology thereby provides a means for improving the efficiency of geoelectrical imaging.

Estimation of primaries by sparse inversion with scattering-based multiple predictions for data with large gaps

We have solved the estimation of primaries by sparse inversion problem for a seismic record with large near-offset gaps and other contiguous holes in the acquisition grid without relying on explicit reconstruction of the missing data. Eliminating the unknown data as an explicit inversion variable is desirable because it sidesteps possible issues arising from overfitting the primary model to the estimated data. Instead, we have simulated their multiple contributions by augmenting the forward prediction model for the total wavefield with a scattering series that mimics the action of the free surface reflector within the area of the unobserved trace locations. Each term in this scattering series involves convolution of the total predicted wavefield once more with the current estimated Green’s function for a medium without the free surface at these unobserved locations. It is important to note that our method cannot by itself mitigate regular undersampling issues that result in significant aliases when computing the multiple contributions, such as source-receiver sampling differences or crossline spacing issues in 3D acquisition. We have investigated algorithms that handle the nonlinearity in the modeling operator due to the scattering terms, and we also determined that just a few of the terms can be enough to satisfactorily mitigate the effects of near-offset data gaps during the inversion process. Numerical experiments on synthetic data found that the final derived method can significantly outperform explicit data reconstruction for large near-offset gaps, with a similar computational cost and better memory efficiency. We have also found on real data that our scheme outperforms the unmodified primary estimation method that uses an existing Radon-based interpolation of the near-offset gap.

TH-CD-204-11: Three Dimensional Gradient Nonlinearity Distortion Corrections for 1.0T MR-SIM Patient Images

Purpose: Although modern MRI scanners have built-in distortion corrections, residual distortion from gradient non-linearity (GNL) may still degrade treatment planning accuracy for large field of views (FOVs). We characterized residual 3D GNL distortion for large FOVs using a novel 3D distortion phantom and developed a correction scheme for patient images. Methods: A 465×350×168mm3 3D distortion phantom with ∼4700 known landmarks was scanned with a 1.0T open MR-SIM (TE/TR/α =5.54ms/30ms/28°, voxel size =1×1×2mm 3). Reverse gradient techniques (identical parameters except read gradient polarities of ±4.48 mT/m) were used to isolate GNL. To increase the FOV in the superior-inferior direction to ∼38cm, an automated script translated the phantom to two off-axis positions yielding ∼14,000 landmarks for evaluation. Centroid analysis was performed between measured and phantom schematic landmark locations. Data were fitted to a sixth-degree polynomial to generate a 3D correction map and applied to images. To correct patient MR-SIM images, distortion maps were resampled to match the acquisition grid and registered. Using distortion maps as warping functions, images were corrected via inverse warping. Pre-and post-correction images were assessed via difference maps and visual evaluation with treatment planning contours. Results: Within a 7.5cm radial distance of isocenter, no pixels had distortions >1mm. However, for radial distances between 7.5 and 15cm from isocenter, ∼35% of pixel were distorted>1mm and 4% were distorted>2mm. Over the full sampled FOV, ∼66% were distorted>1mm, ∼28%>2mm, and 10%>3mm. Applying additional in-house corrections reduced distortions to 2mm. Patient scans showed negligible distortions near isocenter for targets and organs at risk. Conclusion: Distortion magnitudes resulting from GNL were non-negligible for large FOVs away from the magnet isocenter and necessitate additional corrections. Although corrections may be negligible near the treatment planning isocenter, effects of distortion on peripheral structures warrant further study. Research supported in part by a grant from Philips HealthCare (Best, Netherlands), and by NIH grant R01 EB016079

The impact of high‐density spatial sampling versus antenna orientation on 3D GPR fracture imaging

ABSTRACTThree‐dimensional Ground Penetrating Radar (3D GPR) surveys are necessary to reconstruct complex fracture geometries in the subsurface. Two of the most important factors controlling image quality are antenna orientation relative to fractures and density of acquisition grids. This study, conducted in the Madonna della Mazza quarry (Italy), compares two acquisition methods with the goal of optimizing the imaging of fractures and related 3D fracture networks. We acquired two very dense, orthogonal 3D GPR surveys with a 250 MHz antenna and 5 cm trace spacing on the same day, covering the same area of 20 × 20 m. By decimation of the original raw datasets, reduced survey densities of 10 cm and 20 cm spacing are simulated. The results show differences in the imaging quality of the two methods to depths of 75 cm, while for a depth of 130 cm and deeper, image quality is similar. At the same trace density/m2, a single, unidirectional survey with a densely sampled grid is the preferred method rather than two surveys with orthogonal antenna orientations but larger profile spacing. The extra effort of conducting surveys with an acquisition grid of an eighth of wavelength of the antenna centre frequency guarantees that we can properly sample the high‐frequency content of the GPR signal spectrum and results in optimum image quality regardless of fracture orientation. The simple survey design principle found in this study is universally applicable to any field condition, target geometry, and antenna frequency. Such high‐density 3D GPR survey design enables the high‐resolution characterization of 3D fracture networks on subsurface timeslices in near photographic quality.

Nationwide Digital Terrain Models for Topographic Depression Modelling in Detection of Flood Detention Areas

Topographic depressions have an important role in hydrological processes as they affect the water balance and runoff response of a watershed. Nevertheless, research has focused in detail neither on the effects of acquisition and processing methods nor on the effects of resolution of nationwide grid digital terrain models (DTMs) on topographic depressions or the hydrological impacts of depressions. Here, we quantify the variation of hydrological depression variables between DTMs with different acquisition methods, processing methods and grid sizes based on nationwide 25 m × 25 m and 10 m × 10 m DTMs and 2 m × 2 m ALS-DTM in Finland. The variables considered are the mean depth of the depression, the number of its pixels, and its area and volume. Shallow and single-pixel depressions and the effect of mean filtering on ALS-DTM were also studied. Quantitative methods and error models were employed. In our study, the depression variables were dependent on the scale, area and acquisition method. When the depths of depression pixels were compared with the most accurate DTM, the maximum errors were found to create the largest differences between DTMs and hence dominated the amount and statistical distribution of the depth error. On the whole, the ability of a DTM to accurately represent depressions varied uniquely according to each depression, although DTMs also displayed certain typical characteristics. Thus, a DTM’s higher resolution is no guarantee of a more accurate representation of topographic depressions, even though acquisition and processing methods have an important bearing on the accuracy.

Spatial sampling, migration aliasing, and migrated amplitudes

Seismic migration is a multichannel process, in which some of the properties depend on various grid spacings. First, there is the acquisition grid, which actually consists of two grids: a grid of source locations and, for each source location, a grid of receiver locations. In addition, there is a third grid, the migration grid, whose spacings also affect properties of the migration. Sampling theory imposes restrictions on migration, limiting the frequency content that can be migrated reliably given the grid spacings. The presence of three grids complicates the application of sampling theory except in unusual situations (e.g., the isolated migration of a single shot record). I analyzed the effects of the grids on different types of migration (Kirchhoff, wavefield extrapolation migration, and slant-stack migration), specifically in the context of migration operator antialiasing. I evaluated general antialiasing criteria for the different types of migration; my examples placed particular emphasis on one style of data acquisition, orthogonal source and receiver lines, which is commonly used on land and which presents particular challenges for the analysis. It is known that migration artifacts caused by inadequate antialiasing can interfere with velocity and amplitude analyses. I found, in addition, that even migrations with adequate antialiasing protection can have the side effect of inaccurate amplitudes resulting from a given acquisition, and I tested how this effect can be compensated.

Electromagnetic and ultrasonic investigations on a Roman marble slab

The archaeological museum of Rome asked our group about the physical consistency of a marble slab (second to third century AD) that recently fell during its travel as part of an exhibition. We decided to use different methodologies to investigate the slab: namely a pacometer (Protovale Elcometer) to individuate the internal coupling pins, and ground-penetrating radar (GPR) (2000 MHz) and ultrasonic (55 kHz) tomographic high-density surveys to investigate the internal extension of all the visible fractures and to search for the hidden ones. For the ultrasonic data, tests were carried out to optimize the inversion parameters, in particular the cell dimensions. Surely, the choice of cell size for the inversion process must take into account the size of the acquisition grid and the ray number acquired. We proposed to calculate a minimum Fresnel's radius using the sampling frequency instead of that of the probes. For every methodology used, the quality of the acquired data was relatively high. This was then processed and compared to provide information that was useful for some of the insurance problems of the museum. Later on, the data was processed in depth to see how to improve the data processing and interpretation. Finally, the results of this in-depth study were exposed in detail. Ultrasonic and GPR tomographies show a strong correlation, and in particular, the inhomogeneous areas are located in correspondence to the slab injuries.

On sampling functions and Fourier reconstruction methods

Random sampling can lead to algorithms in which the Fourier reconstruction is almost perfect when the underlying spectrum of the signal is sparse or band-limited. Conversely, regular sampling often hampers the Fourier data recovery methods. However, 2D signals that are band-limited in one spatial dimension can be recovered by designing a regular acquisition grid that minimizes the mixing between the unknown spectrum of the well-sampled signal and aliasing artifacts. This concept can be easily extended to higher dimensions and used to define potential strategies for acquisition-guided Fourier reconstruction. The wavenumber response of various sampling operators is derived and sampling conditions for optimal Fourier reconstruction are investigated using synthetic and real data examples.

Investigating the exploration potential for 3D CSEM using a calibration survey over the Troll Field

We demonstrate the ability of the controlled source electromagnetic (CSEM) technique to reveal hydrocarbon reservoirs by reinvestigating the North Sea Troll field with a 3D acquisition grid. Unlike previous applications of 2D CSEM surveys over this field, which have shown a large electromagnetic response over the gas province, the focus in this study is on the thinner and smaller oil reservoir. A weak but consistent anomaly enables detection and delineation of the oil zone and reduces the ambiguity associated with traditional 2D lines. This holds true even for a sparse receiver grid where the target is located between the receiver and source lines. The 3D data show the extent of the oil zone and that it is matched to the top reservoir structural high as well as north-south aligned faults. Variation in magnitude of the anomaly is qualitatively in good correlation with resistivity logs at the well locations. This suggests that 3D CSEM data pave the way for exploration use because of its superiority over 2D data in terms of reduced sensitivity to survey layouts.

Monte Carlo-based diffusion tensor tractography with a geometrically corrected voxel-centre connecting method

Diffusion tensor tractography (DTT) allows one to explore axonal connectivity patterns in neuronal tissue by linking local predominant diffusion directions determined by diffusion tensor imaging (DTI). The majority of existing tractography approaches use continuous coordinates for calculating single trajectories through the diffusion tensor field. The tractography algorithm we propose is characterized by (1) a trajectory propagation rule that uses voxel centres as vertices and (2) orientation probabilities for the calculated steps in a trajectory that are obtained from the diffusion tensors of either two or three voxels. These voxels include the last voxel of each previous step and one or two candidate successor voxels. The precision and the accuracy of the suggested method are explored with synthetic data. Results clearly favour probabilities based on two consecutive successor voxels. Evidence is also provided that in any voxel-centre-based tractography approach, there is a need for a probability correction that takes into account the geometry of the acquisition grid. Finally, we provide examples in which the proposed fibre-tracking method is applied to the human optical radiation, the cortico-spinal tracts and to connections between Broca's and Wernicke's area to demonstrate the performance of the proposed method on measured data.

Non-parametric seismic data recovery with curvelet frames

SUMMARY Seismic data recovery from data with missing traces on otherwise regular acquisition grids forms a crucial step in the seismic processing flow. For instance, unsuccessful recovery leads to imaging artefacts and to erroneous predictions for the multiples, adversely affecting the performance of multiple elimination. A non-parametric transform-based recovery method is presented that exploits the compression of seismic data volumes by recently developed curvelet frames. The elements of this transform are multidimensional and directional and locally resemble wave fronts present in the data, which leads to a compressible representation for seismic data. This compression enables us to formulate a new curvelet-based seismic data recovery algorithm through sparsity-promoting inversion. The concept of sparsity-promoting inversion is in itself not new to geophysics. However, the recent insights from the field of ‘compressed sensing’ are new since they clearly identify the three main ingredients that go into a successful formulation of a recovery problem, namely a sparsifying transform, a sampling strategy that subdues coherent aliases and a sparsity-promoting program that recovers the largest entries of the curvelet-domain vector while explaining the measurements. These concepts are illustrated with a stylized experiment that stresses the importance of the degree of compression by the sparsifying transform. With these findings, a curvelet-based recovery algorithms is developed, which recovers seismic wavefields from seismic data volumes with large percentages of traces missing. During this construction, we benefit from the main three ingredients of compressive sampling, namely the curvelet compression of seismic data, the existence of a favourable sampling scheme and the formulation of a large-scale sparsity-promoting solver based on a cooling method. The recovery performs well on synthetic as well as real data by virtue of the sparsifying property of curvelets. Our results are applicable to other areas such as global seismology.

TEMPLATE-BASED ISOCONTOURING

Different isocontour extraction methods use different cell types (tetrahedral, hexahedral, etc.) depending on the nature of the acquisition grids (structured, unstructured, etc.). The existing isocontouring methods have the following pre-steps for the actual extraction process: (a) identification of cell types, (b) identification of topologically independent instances for each cell type, (c) determination of surface primitives contained in the topologically independent instances and (d) generation of a lookup table such that the name of the entry is an instance of a cell and the entry is the triangle set for that instance. The extraction process outputs the triangles from the lookup table. In this paper we present a novel generic method that enables us to list topologically independent surface primitives called "templates" within any n-polytope cell namely tetrahedra, hexahedra etc. We have also modified the traditional lookup table such that name is the cell instance and the entry is face index representations of all template instances contained in that cell. To show an example, we have applied this approach on a hexahedron and listed the templates and subsequently we have showed how to construct a lookup table. Most modern graphics hardware render triangles faster if they are rendered collectively as triangle strips as opposed to individual triangles. With our modified lookup table approach we can identify triangles in the neighboring cell in a linear time and hence we are able to connect two triangle strips into a longer triangle strip on the fly during the extraction process. We have compared our approach with some existing methods. The following are some of the important features of the method: (1) Simplicity, (2) procedural triangulation and (3) face-index representation.

Data Processing and Imaging in GPR System Dedicated for Landmine Detection

Improvements of GPR technology can be attained by making adjustments specific for the application of landmine detection on three levels: system design, data acquisition and data processing. In this paper we describe data processing algorithms specially developed for a novel video impulse ultra-wide band front end. With this front end, three-dimensional measurements (C-scans) have been carried out over a controlled test site, using a non-metallic scanner. The test site contained surface-laid and shallow buried landmines, both antitank and antipersonnel, made of plastic, wood, and metal. Because of practical limitations, the data have been acquired on an irregular grid. We have designed data preprocessing and imaging algorithms such that they take into account the specific antenna geometry and its elevation above the ground as well as the irregularity of the data acquisition grid. We show that by tuning the data pre-processing and imaging to the newly designed radar front end and to the particular data acquisition strategy, we obtain clear subsurface images. The resulting images show the ability of the GPR system to detect and visualize small surface laid and shallow buried targets.

2-D and 3-D processing and interpretation of multi-fold ground penetrating radar data: a case history from an archaeological site

A 2.5-D and 3-D multi-fold GPR survey was carried out in the Archaeological Park of Aquileia (northern Italy). The primary objective of the study was the identification of targets of potential archaeological interest in an area designated by local archaeological authorities. The second geophysical objective was to test 2-D and 3-D multi-fold methods and to study localised targets of unknown shape and dimensions in hostile soil conditions. Several portions of the acquisition grid were processed in common offset (CO), common shot (CSG) and common mid point (CMP) geometry. An 8×8 m area was studied with orthogonal CMPs thus achieving a 3-D subsurface coverage with azimuthal range limited to two normal components. Coherent noise components were identified in the pre-stack domain and removed by means of FK filtering of CMP records. Stack velocities were obtained from conventional velocity analysis and azimuthal velocity analysis of 3-D pre-stack gathers. Two major discontinuities were identified in the area of study. The deeper one most probably coincides with the paleosol at the base of the layer associated with activities of man in the area in the last 2500 years. This interpretation is in agreement with the results obtained from nearby cores and excavations. The shallow discontinuity is observed in a part of the investigated area and it shows local interruptions with a linear distribution on the grid. Such interruptions may correspond to buried targets of archaeological interest. The prominent enhancement of the subsurface images obtained by means of multi-fold techniques, compared with the relatively poor quality of the conventional single-fold georadar sections, indicates that multi-fold methods are well suited for the application to high resolution studies in archaeology.