A novel pulsed photoconductive THz source is presented that is able to radiate mW-level average powers, over a large bandwidth by exploiting both the optical and electrical properties of photoconductive sources and the ultrawideband properties of connected antenna arrays. An optical system composed of a micro-lenses array splits the laser beam into N × N spots that host the active excitation of the antenna arrays. An 'ad hoc' network has been adopted to bias the array active spots in order to implement a connected antenna array configuration. The array feeds a silicon lens to increase the directivity of the radiated THz beam. A slot array prototype has been designed, fabricated, and measured. The proposed solutions achieve excellent power radiation levels by making use of an accurate electromagnetic design. This solution can offer enhancements to any active system relying on pulsed photoconductive antennas.

Simultaneous source shooting or blended acquisition, which allows a temporal overlap between shot records, has been proposed as a method for substantially reducing the acquisition cost and improving data quality (e.g., denser shooting/efficient wide-azimuth shooting). Deblending allowed by traditional processing steps is still the dominant way of dealing with blended data. However, most of the deblending algorithms only utilize the blended input data without aliasing. In addition, it will be more challenging if the aliasing blended data traces are irregularly sampled, resulting in the failure of some deblending algorithms. In this paper we investigated the interpolation problem of irregularly blended seismic data using the focal transformation. Synthetic data example demonstrates the validity of its application for joint deblending and interpolation of the irregularly blended data.

The main challenge for predictive simulation of carbonate reservoirs is associated with large uncertainties in the geological characterization with multiple features including fractures and cavities. This type of reservoirs requires robust and efficient forward-simulation capabilities to apply data assimilation or optimization technique under uncertainties. The interaction between reservoir matrix and various features introduces a complex multi-scale flow response driven by global boundary conditions. The Discrete Fracture Models (DFM), which represent fractures explicitly, is capable to accurately depict all important features of flow behavior. However, these models are constrained by many degrees of freedom when the fracture network becomes complicated. The Embedded DFM, which represents the interaction between matrix and fractures analytically, is an efficient approximation. However, it cannot accurately reproduce the effect of local flow conditions, especially when the secondary fractures are present. In this study, we applied a numerical upscaling of DFM a triple continuum model where large features are represented explicitly using the numerical EDFM and small features are upscaled as a third continuum. In this approach, we discretize the original geo-model with unstructured grid based on DFM and associate the mesh geometry with large features in the model. Using the global solution, we generate local boundary conditions for the model capturing the response of primary features to the flow. Applying local boundary conditions, we resolve all secondary features using a fine scale solution and update the local boundary conditions. This procedure is applied iteratively using the local-global-upscaling formalism. To demonstrate the accuracy of the Multi-Level Discrete Fracture Model, several realistic cases have been tested. By comparing with fine scale DFM solution and the traditional EDFM technique, we demonstrate that the proposed model is accurate enough to capture the flow behavior in complex fractured systems with advanced computational efficiency.