APPLICATION OF ARTIFICIAL INTELLIGENCE FOR CO2 STORAGE IN SALINE AQUIFER (SMART PROXY FOR SNAP-SHOT IN TIME)

In recent years, artificial intelligence (AI) and machine learning (ML) technology have grown in popularity. Smart Proxy Models (SPM) are AI/ML based data-driven models which have proven to be quite crucial in petroleum engineering domain with abundant data, or operations in which large surface/ subsurface volume of data is generated. Climate change mitigation is one application of such technology to simulate and monitor CO2 injection into underground formations. The goal of the SPM developed in this study is to replicate the results (in terms of pressure and saturation outputs) of the numerical reservoir simulation model (CMG) for CO2 injection into saline aquifers. In so doing, the artificial intelligence model was used to particularly predict the pressure distribution as well as carbon dioxide plume at any time-step throughout the period of injection and post-injection. There are four injectors injecting approximately two million metric tons of CO2 per year for a period of ten years. The project seeks to unravel what happens to CO2 and pressure during and after the injection process, commonly referred to as injection and post-injection periods. This process was monitored for 10 years of injection and 190 years of post-injection. There are 46 geologic realizations of the porosity and permeability distributions which along with some 300 static and dynamic data and features extracted from the model are used as the main input to the artificial neuron network for training, calibration and validation. The dataset produced is then distributed into three major parts; the training dataset, which is majorly aimed at training smart proxy model, the calibration dataset which is majorly a watchdog, and a blind validation which is used to perform the final evaluation on the model after it achieves the desired training accuracy. The results show that the developed SPM can successfully mimic the pressure and CO2 behavior of the CMG outputs which are determining factors of the amount and safety of CO2 sequestration. When implemented on a large scale, this technology has the potential to be very competitive with existing numerical reservoir simulators, providing an additional toolbox for petroleum engineers and CO2 sequestration specialists to monitor the pressure and CO2 plume, as well as perform uncertainty quantification and optimization

USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TO DEVELOP SYNTHETIC WELL LOGS

There has been an increase in the need for energy in the recent past. Oil and gas stand as the source of energy that are widely used. The oil and gas reservoirs are targeted for the purposes of field development. The conventional methods of reservoir characteristics require computing techniques that are unique and complex, some of which are labor and time intensive. Mohaghegh argues that all efforts must be tried and made possible to apply Petroleum Data analytics in production and management of reservoir so as to earn a maximum return (Mohaghegh, Shale Analytics, 2017). Different methodologies have been applied to derive synthetic well logs from existing logs using technologies such as the artificial neural networks which can be used when well logs are absent due to several factors such as difficulty in the logging operation and the tool timing. The aim of this research is to explore the form and the nature of artificial intelligence and machine learning (neural network systems) to develop synthetic well logs and to explore this technology’s capabilities of building new strategies seeking development of oil and gas fields. By obtaining the data and feed it to the neural network the results demonstrate that developing synthetic well logs using artificial intelligence and machine learning is a feasible approach for the enhancement of formation evaluation and reservoir characterization. Artificial intelligence is a reliable and promising technology that can significantly contribute to solving petroleum engineering related problems especially when it comes to the importance of fast decision-making processes

Ett agroekologiskt perspektiv för att förbättra torktoleransen för vetekulturer för Sverige

Drought stress is one of the major abiotic stresses that cause losses in cereal production around the world. Drought stress causes several morphological, physiological, biochemical and molecular transformations in plants. All aspects of plant growth (leaf size, leaf index area and plant height) will be reduced when drought stress is imposed on a plant during all stages of growth. The plant’s physiology under severe drought stress could reduce the transpiration rate and water consumption, which could lead to dried and dead plants, and also affect the quality of grain and cause losses in yield. The drought that happened in the south of Sweden in the 2018 season caused considerable losses in grain yield, primarily winter wheat. The aim of this study was to analyze the effects of drought stress on wheat production in the south of Sweden in the 2018 drought season and then to assess whether new technologies such as phenotyping can provide solutions for the agricultural sector in general and wheat production in particular. The study included two parts: the first part consisted of a five face-to-face interviews. Three interviews were with farmers from different locations in the south of Sweden. The aim of these interviews was to understand the farmers’ perceptions of the drought that happened in 2018 and to explore if they have made plans to handle or prepare for future droughts. The other two interviews were made with plant breeders who work at Lantmännen. The aim of these interviews was to understand how breeders preparing their breeding programs related to climate changing in Sweden and if there are any trials or research relating to drought. The second part of the study consisted of a Biotron experiment to evaluate early vigour and drought stress responses of genotypes. Finally, the analyzed data from the Biotron experiment was compared to drought tolerance scoring obtained from the field trial performed in 2018 for another project. These field score data correlated well with the results of the Biotron experiment. In conclusion, there is a possibility to develop drought-tolerant varieties in wheat which can survive during the drought season. Also, the development in technology sector can provide more accurate tools for phenotyping crops in coming years

High accuracy walking motion trajectory generation profile based on 6-5-6-PSPB polynomial segment with polynomial blend

Many robots, such as humanoid robot, biped robot, and robotic exoskeleton, need human guide. Particularly, there is a strong need for devices to assist individuals who lost limb function due to illnesses or injuries. Thus, several methods of generating walking motion have been implemented in order to generate walking motion according to natural human behaviour for the exoskeleton robot system. Polynomial blend technique has implemented to generate the walking motion trajectory, where the polynomial blend refers to the combination of more than one polynomial. However, three constraints (angular position, velocity, and acceleration) have been imposed by the polynomial blend techniques where the constraint of angular jerk was neglected because involving the jerk constrain will be caused problem of the non-ideal match of kinematic constraints at via point. Based on the aforementioned problem, there are three objectives to be achieved in this project. The first objective is to investigate the trajectory profile for various kinematic constraints of walking motion condition when using polynomial equation. The second objective is to modify a technique for improving a trajectory generation method to solve the problem of non-ideal match of the kinematic constraints through via points that connects between successive segments of the human walking motion. The last objective is to validate the trajectory generation method by testing the trajectory generation methods based on simulation using SimMechanics as well as to ensure that the coefficients values of the polynomial equations are correctly obtained. In this project, 5th polynomial segment with the 6th polynomial blend (6-5-6 PSPB) trajectory is proposed that aims to reduce the error that increases because of non-ideal match between kinematic constraints at the via points of successive segments. The trajectory planning of the 6-5-6 PSPB is generated based on the stance and swing phases. Each phase is presented by one full of the 6-5-6 PSPB trajectory. In order to validate the 6-5-6 PSPB trajectory, simulation using SimMechanics is conducted to ensure that the coefficients values of the polynomial equations are correctly obtained. The result shows that the error was improved almost 0.1445 degree based on the proposed 6-5-6 PSPB compared with the 4-3-4 PSPB and 5-4-5 PSPB. Thus, the 6th -5th -6th Polynomial blend leads to impose the angular jerk kinematic constraint beside the angular position, velocity, and acceleration kinematic constraints during the whole walking motion trajectory. Minimizing the maximum jerk in joint space has a beneficial effect in terms of reducing the actuator and mechanical strain and joint wear and to limit excessive wear on the robot and the excitation of resonances so that the robot life-span is expanded

Wireless Sensor Network Security: Approaches to Detecting and Avoiding Wormhole Attacks

This paper explores Wireless Sensor Networks (WSNs) and the related security issues and complications arising from a specific type of security breach, the wormhole attack. Wormhole attacks against WSNs are classified as passive, external laptop-class threats. Because malicious wormhole attacks are increasing, these attacks pose a serious security threat and increase the costs to maintain a Wireless Sensor Network. Research into preventing wormhole attacks yields two distinct model approach types: Administrator-Viewpoint models and User-Viewpoint models. While the modalities vary, the four Administrator-Viewpoint models reviewed were designed in the early 2000s and suggest defending against wormhole attacks through the use of expensive hardware, packet leashes, or topology visualization systems. On the other hand, the four proposed User-Viewpoint models have become the current theoretical models of choice.  While existing as simulation approaches to defend against wormhole attacks, the User-Viewpoint models use internally calculated routing algorithms to suggest routes to avoid or evade, not defend against, established wormhole routes. This paper confirms the efficacies of the User-Viewpoint models in the lab simulations are viewed as the most promising cost-effective, future security solutions to wormhole attacks

Prévenir les délinquants ou se taire face aux policiers

Dans les discours publics mais également dans de nombreuses œuvres cinématographiques, l’omerta repose essentiellement sur le risque de représailles. L’exposition aux violences constituerait ainsi le principal ressort de ce silence auquel se confrontent régulièrement les forces de police dans leur travail judicaire. Le silence serait subi car la parole ne serait pas libre. Pourtant, la délinquance enracinée dans les cités populaires françaises repose moins sur une organisation de type mafieuse que sur des bandes ou des réseaux de revente de stupéfiants de taille limitée. Le travail de la police n’en demeure pas moins soumis à de nombreuses obstructions dont l’explication ne peut se réduire aux risques – bien réels – qui pèsent sur le témoignage. Cet article rend compte d’un travail de recherche construit à partir de l’idée que le lien entre silence et peur est trop réducteur et propose une analyse sur des formes de soutien social, dont l’intensité varie selon les types de délits qui sont poursuivis.In political discourses as well as in many popular movies, omerta often relies on the risks of retaliation. The risk of violence is therefore seen as the main explanation for the silence the police officers are confronted with when trying to carry out their investigations. This article shows that, even though the forms of delinquency found in the French popular suburbs point out more to gangs and networks involved in drug trafficking, limited in scope, rather than mafia-type organisations, the work of the police officers is nonetheless constrained by various obstructions to testimonies that cannot be reduced to the risks of retaliation and anticipated violence. This article thus analyses the relationships between silence and fear, taking into account the forms of social support that varies according to the types of crimes committed