Unlocking Growth Opportunities Through Saturation Evaluation Behind Complex Completion by Applying State-of-Art Pulsed Neutron Technology

Perseverance in quantifying the remaining hydrocarbon saturation, in cased boreholes, remains critical to take business decisions and prioritize operations in brownfield waterflood development. Challenges with cased hole saturation evaluation acquired in certain complex completions such as those completed in multiple casing-tubing strings, slotted-liners and sand-screens require advanced tool technology. Pulsed Neutron Logging (PNL) is one such technology used successfully to analyze behind casing saturation evaluation. The PNL device provide accurate and precise measurement, and with robust processing and environmental compensation corrections, the saturation uncertainty can be delineated. A robust cased hole hydrocarbon saturation and uncertainty estimation enables informed decision making and value driven workover prioritization. The new generation PNL tool features a high-output electronic neutron source and four signal detectors. Near and far Gamma Ray (GR) detectors are made of Cerium-doped Lanthanum Bromide (LaBr3: Ce) featuring high-count rate efficiency and high-spectral resolution (largely insensitive to temperatures variations). A deep-reading GR detector made of Yttrium Aluminum Perovskite (YAP) in combination with a compact fast neutron monitor placed adjacent to the neutron source, enables a new measurement of the fast neutron cross section (FNXS) which provides sensitivity to gas-filled porosity. A newly devised pulsing scheme allows simultaneous measurement in both time and energy domains. The time-domain measurement aid in analyzing the self-compensated capture cross section (SIGM), neutron porosity (TPHI), and FNXS. The energy-domain measurement provides a detailed insight for high-precision mineralogy, total organic carbon (TOC), and carbon/oxygen ratio (COR). The high statistical precision energy-domain capture and inelastic spectral yield data are interpreted using an oxide-closure model which when combined with an extensive tool characterization database provide lithology and saturation measurements compensated for wellbore and completion contributions. This paper shares the advanced features of the new multi-detector PNL tool run in a horizontal well targeting the aeolian Mahwis Formation, consisting of unconsolidated sands and the glacial Al Khlata Formation (Porosity ranges 0.25 – 0.29 p.u.). In this case-study, the well was completed with uncemented sand screens and production tubing to mitigate sanding related risk. The absence of cement behind casing and the presence of screens adds considerable complexity to the saturation analysis. Furthermore, due to low water salinity (∼7000 ppm NaCl equivalent), saturation must be determined using carbon spectroscopy-based techniques - namely the COR and TOC. Logging conventional PNL tools in horizontal wells can lead to lengthy acquisition times, thus adding considerable operational complexity and cost. With the new PNL technology advancements, the time required to acquire high-quality data can be halved. Saturation outputs computed independently from COR and TOC methods showed close agreement and allowed for the direct compensation of changes in borehole oil hold-up without which the computed saturation would have been overestimated. The remaining oil saturation estimation behind cased hole and uncertainty quantification enable a proper understanding of well production performance and uncovered further opportunities. In addition, decision based strategic data acquisition to quantify remaining hydrocarbon saturation enables unlocking growth and ‘no further action’ (NFA) opportunities, impacting production recovery and meeting bottom-line targets in brownfield assets.

Study on Electromagnetic Radiation Interference Caused by Rocket Fuel

During the launch and return of a spacecraft, the intense combustion of propellants generates strong electromagnetic radiation, which interferes with the operation of electronic equipment in the spacecraft. To improve the electromagnetic compatibility of electronic equipment in spacecraft, it is necessary to study the electromagnetic radiation characteristics of rocket fuel. An electromagnetic radiation measurement system based on antennas is designed to measure the electromagnetic radiation generated by rocket fuel, and the electromagnetic radiation characteristics are obtained through data analysis. The mechanism of the electromagnetic radiation generated by rocket fuel is comprehensively analysed through the spatial, time-domain, frequency-domain, and energy-domain characteristics. A characterization model is established to provide a reliable scheme for evaluating the influence of rocket fuel electromagnetic radiation on electronic equipment in spacecraft.

A Novel Feature Representation for Prediction of Global Horizontal Irradiance Using a Bidirectional Model

Complex weather conditions—in particular clouds—leads to uncertainty in photovoltaic (PV) systems, which makes solar energy prediction very difficult. Currently, in the renewable energy domain, deep-learning-based sequence models have reported better results compared to state-of-the-art machine-learning models. There are quite a few choices of deep-learning architectures, among which Bidirectional Gated Recurrent Unit (BGRU) has apparently not been used earlier in the solar energy domain. In this paper, BGRU was used with a new augmented and bidirectional feature representation. The used BGRU network is more generalized as it can handle unequal lengths of forward and backward context. The proposed model produced 59.21%, 37.47%, and 76.80% better prediction accuracy compared to traditional sequence-based, bidirectional models, and some of the established states-of-the-art models. The testbed considered for evaluation of the model is far more comprehensive and reliable considering the variability in the climatic zones and seasons, as compared to some of the recent studies in India.

Machine Learning Techniques in the Energy Consumption of Buildings: A Systematic Literature Review Using Text Mining and Bibliometric Analysis

The high level of energy consumption of buildings is significantly influencing occupant behavior changes towards improved energy efficiency. This paper introduces a systematic literature review with two objectives: to understand the more relevant factors affecting energy consumption of buildings and to find the best intelligent computing (IC) methods capable of classifying and predicting energy consumption of different types of buildings. Adopting the PRISMA method, the paper analyzed 822 manuscripts from 2013 to 2020 and focused on 106, based on title and abstract screening and on manuscripts with experiments. A text mining process and a bibliometric map tool (VOS viewer) were adopted to find the most used terms and their relationships, in the energy and IC domains. Our approach shows that the terms “consumption,” “residential,” and “electricity” are the more relevant terms in the energy domain, in terms of the ratio of important terms (TITs), whereas “cluster” is the more commonly used term in the IC domain. The paper also shows that there are strong relations between “Residential Energy Consumption” and “Electricity Consumption,” “Heating” and “Climate. Finally, we checked and analyzed 41 manuscripts in detail, summarized their major contributions, and identified several research gaps that provide hints for further research.

Study on Electromagnetic Radiation Interference Caused by Rocket Fuel

During the launch and return of a spacecraft, the intense combustion of propellants generates strong electromagnetic radiation, which interferes with the operation of electronic equipment in the spacecraft. To improve the electromagnetic compatibility of electronic equipment in spacecraft, it is necessary to study the electromagnetic radiation characteristics of rocket fuel. An electromagnetic radiation measurement system based on antennas is designed to measure the electromagnetic radiation generated by rocket fuel, and the electromagnetic radiation characteristics are obtained through data analysis. The mechanism of the electromagnetic radiation generated by rocket fuel is comprehensively analysed through the spatial, time-domain, frequency-domain, and energy-domain characteristics. A characterization model is established to provide a reliable scheme for evaluating the influence of rocket fuel electromagnetic radiation on electronic equipment in spacecraft.

Towards FAIR Data for Low Carbon Energy - Current State and Call for Action

With the continued digitization of the energy sector, the problem of sunken scholarly data investments and forgone opportunities of harvesting existing data is exacerbating. It adds to the problem that the reproduction of knowledge is incomplete, impeding the transparency of science-based evidence for the choices made in the energy transition. We comprehensively test FAIR data practices in the energy domain with the help of automated and manual tests. We document the state-of-the art and provide insights on bottlenecks from the human and machine perspectives. We propose action items for overcoming the problem with FAIR and open energy data and suggest how to prioritize activities.

Time-of-flight photoelectron momentum microscopy with 80–500 MHz photon sources: electron-optical pulse picker or bandpass pre-filter

The small time gaps of synchrotron radiation in conventional multi-bunch mode (100–500 MHz) or laser-based sources with high pulse rate (∼80 MHz) are prohibitive for time-of-flight (ToF) based photoelectron spectroscopy. Detectors with time resolution in the 100 ps range yield only 20–100 resolved time slices within the small time gap. Here we present two techniques of implementing efficient ToF recording at sources with high repetition rate. A fast electron-optical beam blanking unit with GHz bandwidth, integrated in a photoelectron momentum microscope, allows electron-optical `pulse-picking' with any desired repetition period. Aberration-free momentum distributions have been recorded at reduced pulse periods of 5 MHz (at MAX II) and 1.25 MHz (at BESSY II). The approach is compared with two alternative solutions: a bandpass pre-filter (here a hemispherical analyzer) or a parasitic four-bunch island-orbit pulse train, coexisting with the multi-bunch pattern on the main orbit. Chopping in the time domain or bandpass pre-selection in the energy domain can both enable efficient ToF spectroscopy and photoelectron momentum microscopy at 100–500 MHz synchrotrons, highly repetitive lasers or cavity-enhanced high-harmonic sources. The high photon flux of a UV-laser (80 MHz, <1 meV bandwidth) facilitates momentum microscopy with an energy resolution of 4.2 meV and an analyzed region-of-interest (ROI) down to <800 nm. In this novel approach to `sub-µm-ARPES' the ROI is defined by a small field aperture in an intermediate Gaussian image, regardless of the size of the photon spot.

Innovative Analytical Method for X-Ray Imaging and Space-Resolved Spectroscopy of ECR Plasmas

At INFN-LNS, and in collaboration with the ATOMKI laboratories, an innovative multi-diagnostic system with advanced analytical methods has been designed and implemented. This is based on several detectors and techniques (Optical Emission Spectroscopy, RF systems, Interfero-polarimetry, X-ray detectors) and here we focus on high resolution spatially-resolved X-ray spectroscopy, performed by means of a X-ray pin-hole camera setup operating in the 0.5&minus;20 keV energy domain. The diagnostic system was installed at a 14 GHz Electron Cyclotron Resonance (ECR) ion source (ATOMKI, Debrecen), enabling high precision X-ray spectrally-resolved imaging of ECR plasmas heated by hundreds of Watts. The achieved spatial and energy resolution were 0.5 mm and 300 eV at 8 keV, respectively. We here present the innovative analysis algorithm that we properly developed for obtaining Single Photon-Counted (SPhC) images providing the local plasma emitted spectrum in a High-Dynamic-Range (HDR) mode, by distinguishing fluorescence lines of the materials of the plasma chamber (Ti, Ta) from plasma (Ar). This method allows a quantitative characterization of warm electrons population in the plasma (and its 2D distribution) which are the most important for ionization, and also to estimate local plasma density and spectral temperatures. The developed post-processing analysis is also able to remove the readout noise, that is often observable at very low exposure times (msec). The setup is now under update including fast shutters and trigger systems in order to allow simultaneously space and time-resolved plasma spectroscopy during transients, stable and turbulent regimes.

A smarthome conversational agent performing implicit demand-response application planning

In recent years, the growing use of Intelligent Personal Agents in different human activities and in various domains led the corresponding research to focus on the design and development of agents that are not limited to interaction with humans and execution of simple tasks. The latest research efforts have introduced Intelligent Personal Agents that utilize Natural Language Understanding (NLU) modules and Machine Learning (ML) techniques in order to have complex dialogues with humans, execute complex plans of actions and effectively control smart devices. To this aim, this article introduces the second generation of the CERTH Intelligent Personal Agent (CIPA) which is based on the RASA framework and utilizes two machine learning models for NLU and dialogue flow classification. CIPA-Generation B provides a dialogue-story generator that is based on the idea of adjacency pairs and multiple intents, that are classifying complex sentences consisting of two users’ intents into two automatic operations. More importantly, the agent can form a plan of actions for implicit Demand-Response and execute it, based on the user’s request and by utilizing AI Planning methods. The introduced CIPA-Generation B has been deployed and tested in a real-world scenario at Centre’s of Research & Technology Hellas (CERTH) nZEB SmartHome in two different domains, energy and health, for multiple intent recognition and dialogue handling. Furthermore, in the energy domain, a scenario that demonstrates how the agent solves an implicit Demand-Response problem has been applied and evaluated. An experimental study with 36 participants further illustrates the usefulness and acceptance of the developed conversational agent-based system.

Study on Electromagnetic Radiation Interference Caused by Rocket Fuel

During the launch and return of a spacecraft, the intense combustion of propellants generates strong electromagnetic radiation, which interferes with the operation of electronic equipment in the spacecraft. To improve the electromagnetic compatibility of electronic equipment in spacecraft, it is necessary to study the electromagnetic radiation characteristics of rocket fuel. An electromagnetic radiation measurement system based on antennas is designed to measure the electromagnetic radiation generated by rocket fuel, and the electromagnetic radiation characteristics are obtained through data analysis. The mechanism of the electromagnetic radiation generated by rocket fuel is comprehensively analysed through the spatial, time-domain, frequency-domain, and energy-domain characteristics. A characterization model is established to provide a reliable scheme for evaluating the influence of rocket fuel electromagnetic radiation on electronic equipment in spacecraft.