Drilling in Russia's Far East has always been associated with industry-defining ultra-extended-reach drilling. With the emergence of more powerful drilling rigs and advances in measurement- and logging-while-drilling (MWD and LWD) tools, these wellbores can be designed to reach farther. Therefore, accurately penetrating and exploiting distant reservoirs have resulted in critical dependence on high-accuracy surveying techniques. Successful target penetration and meeting anticollision requirements without the need for shutting production in nearby wells are key proponents for a geomagnetic referencing service (GRS). Geomagnetic referencing is the technique to minimize the lateral position uncertainties when using MWD. This is particularly important for wellbores that extend the boundary of the drilling envelope with stepouts greater than 13 km. The wellbore azimuth accuracy is highly dependent on the quality of the magnetic data used to produce the geomagnetic reference model. This model characterizes the absolute magnitude and vector direction of the natural magnetic field for every point along the wellbore. Representation of the local crustal magnetic contribution is key to the process since it constitutes a significant error in the lateral wellbore position. Since 2011, a new, highly accurate geomagnetic referencing methodology has been used in Russia's Far East. Global contributions are accounted for by a high-definition geomagnetic model (HDGM). In addition, the local crustal magnetic anomaly is represented by 3D ellipsoidal harmonic functions tracking the shape and depth of the Earth, thereby providing seamless integration with HDGM and avoiding distortions faced by conventional plane-Earth approximations. A comparison with the previous industry standard shows improvements of 0.5° in azimuth determination. This high-degree geomagnetic technique will serve well for a number of upcoming developments in Russia's Far East, continuing to push the drilling envelope and providing essential, accurate wellbore positioning, while offering significant time and cost savings.
Mind mapping is the well-known approach for visualization the complex topics in education. In [1] we propose the synthesis of active and passive ways for using mind maps in education practice. By this way we need construct the software tool for building mind maps with special requirements. First of all, this is the limitations for the set of mind map nodes. Student will select for placement on mind map only nodes from the set of items from dictionary of current lesson topic. And may be from the course main glossary. This limitation is necessary for automatic pre-evaluation the quality of student's mind maps. The value of quality will calculate on the base of the measurement of distance between original teacher's and student's mind maps. So we need to make the three solutions: 1. Haw to find the set of termins for the actual topic? Glossary is the one of typical course resource in the learning management system Moodle. In [2] we present the simple tool "wordstat 2.0" for term selections from the course content documents set. 2. Provide the easy tool for mind mapping. We assume that the fast solution can be reached on the basis of modifying the open source software. The allowable opportunity is about using text-only environment, like Text2MindMap online tool. 3. Evaluation the maps structure (dis)similarities. The mind map has the graph structure. So the mind maps quality measurement can be estimate via comparison the graph structure similarities. It is well known task. There is no problem for getting the graph structure from outline text or from XML mind map file. 1. Dubinsky, A. (2019) Mind maps for education. In: Exploring the Mind's Eye: An Interdisciplinary Conference on Imagination, October 25-26, 2019, Bilkent University, Bilkent, Ankara, Turkey. (Submitted) http://repo.dma.dp.ua/4447/ 2. Dubinsky, A. (2019) The preparation of terminological glossary for the educational course [in russian]. In: MoodleMoot Ukraine 2019, Kyiv, 24 May 2019 http://2019.moodlemoot.in.ua/course/view.php?id=23
First aid skills are the important part of medical's competency. The set of instructions for first aid operations are officially approved by the state. This instruction texts are the algorithms. Medical students are studying these algorithms in the special course. First of all, we convert the instructions from text to the graphical flowcharts (according to ISO 5807-85 standard) for checking the ambiguity and possible misunderstanding. The execution process of such algorithms is one of typical "complex open ended assignments". We have the classification of typical user errors. On the base of this errors we construct the set of alternative choices for all steps of algorithm. Every such set will convert to the answers for multiple choice question (MCQ). There are repeated cyclic question for student (executor): "what you will do?" or "what is your next operation?" We plan to build the special environment for gamification of the learning process. Short version will have only one right way - sequence of answers. Every wrong answer will lead the error message - "your patient is dead" and explanation why it happened. In the more complex model we evaluate the patient state and student can read the comments and the errors list only after the end of the algorithm execution. This year (2020) we plan to make the first iteration: text-based online adventure game, one content set, based on the first aid instructions that are approved in Ukraine. The next iteration will use first aid instructions that are accepted in other countries, starting from countries of EU. We suppose future development of this game will be like a well-known history of evolution of computer games. This project will be part of the second co-author PhD thesis
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