Dry Lab – Laboratorium Virtual Untuk Anlisa Rekayasa Lumpur Pemboran

Abstract Dry Lab is a virtual laboratory design. We called also as a laboratory of the future. Dry Lab was designed because of the increasingly advanced computerized especially Artificial Intelligence for making a simulator that can function to simulate a tool wich is can similiar with the real condition so that it gets the same results as when run in a conventional laboratory. With the existence of this Simulator technology, then I try to make a virtual simulator for drilling mud analysis which is very much needed in the world of oil engineering education especially and also needed in the world of oil and gas industry, especially when conducting drilling activities. Keywords: Dry Lab, Artificial Intelligence, virtual simulator, drilling mud. Abstrak Dry Lab adalah suatu rancangan virtual laboratorium. Dapat juga dikatakan sebagai Laboratorium masa depan. Dry Lab dirancang karena semakin majunya ilmu komputerisasi Artificial intelligence dalam membuat suatu simulator yang dapat berfungsi mensimulasikan suatu alat sesuai dengan cara kerja aslinya sehingga mendapatkan hasil yang sama seperti saat dijalankan di Laboratorium konvensional.Dengan adanya teknologi Simulator ini, maka saya mencoba membuat suatu simulator virtual untuk analisa lumpur pemboran yang sangat dibutuhkan dalam dunia pendidikan Teknik perminyakan khususnya dan juga dibutuhkan di dalam dunia industri Migas terutama saat melakukan kegiatan pemboran. Kata kunci: Dry Lab, Artificial intelligence, simulator virtual, lumpur pemboran. Reference: Agusman, A. R., Rasyid, A., & Lesmana, D. L. (2022). Evaluasi Water Shut Off Dan Membuka Lapisan Baru Sumur Bagong Di Lapangan Lesma. JURNAL BHARA PETRO ENERGI, 38-43. Aly Rasyid, A. R. (2021). Seleksi Material Untuk Casing Sumur Migas & Geothermal–Buku Referensi. Composition and Properties of Drilling and Completion Fluids: Seventh Edition, Caenn, RyenDarley, H. C.H. and Gray, George R. (2016) Composion And Properties Of Drilling And Complition Fluids,  H.C.H Darley and George R. Gray J.T. Patton (New Mexico State U.) P.F. Phelan (Los Alamos Natl Laboratory), Well Damage Hazards Associated With Conventional Completion Fluids Khodja, M., Khodja-Saber, M., Canselier, J. P., Cohaut, N. and Bergaya, F. (2010) ‘Drilling fluid technology: performances and environmental considerations’, Product and Services, From R&D to final solutions, pp. 227-232. Available at: http://cdn.intechopen.com/pdfs-wm/12330.pdf Nasution, M. M., Rasyid, A., & Pahrudin, G. (2022). Desain Formulasi Lumpur Untuk Pemboran Panas Bumi Di Sumur GG-01. JURNAL BHARA PETRO ENERGI, 11-18. Rasyid, A., Mardiana, R. Y., Budiono, K., & Noviasta, B. (2021, December). Drilling optimization in geothermal exploration wells using enhanced design of conical diamond element bit. In Asia Pacific Unconventional Resources Technology Conference, Virtual, 16–18 November 2021 (pp. 1795-1808). Unconventional Resources Technology Conference (URTeC). Rasyid, A., Soesanto, E., & Nababan, E. N. (2022). Evaluasi dan Optimasi Desain Casing Sumur Pemboran dengan Metode Maximum Load di Sumur ENN-1 di Lapangan Batuwangi. JURNAL BHARA PETRO ENERGI, 1-10. Rasyid, A. (2019). Pemanfaatan Wellbore Strengthening Agent Selama Pengeboran di Onshore Sumatera Bagian Utara Indonesia. Jurnal Jaring SainTek, 1(2). Rudi Rubiandini R.S, Buku Teknik Pemboran Volume 1, Bandung, 2015 Virtual and Physical Experimentation in Inquiry-Based Science Labs: Attitudes, Performance  and Access.Journal of Science Education and TechnologyPyatt, Kevin.,Sims, Rod, 2012 Virtual laboratories in engineering education: the simulation lab and remote labComputer Applications in Engineering Education.Balamuralithara, B. Woods, P. C. 2009 Agusman, A. R., Rasyid, A., & Lesmana, D. L. (2022). Evaluasi Water Shut Off Dan Membuka Lapisan Baru Sumur Bagong Di Lapangan Lesma. JURNAL BHARA PETRO ENERGI, 38-43.  

Novel Artificial Human Optimization Field Algorithms - The Beginning

New Artificial Human Optimization (AHO) Field Algorithms can be created from scratch or by adding the concept of Artificial Humans into other existing Optimization Algorithms. Particle Swarm Optimization (PSO) has been very popular for solving complex optimization problems due to its simplicity. In this work, new Artificial Human Optimization Field Algorithms are created by modifying existing PSO algorithms with AHO Field Concepts. These Hybrid PSO Algorithms comes under PSO Field as well as AHO Field. There are Hybrid PSO research articles based on Human Behavior, Human Cognition and Human Thinking etc. But there are no Hybrid PSO articles which based on concepts like Human Disease, Human Kindness and Human Relaxation. This paper proposes new AHO Field algorithms based on these research gaps. Some existing Hybrid PSO algorithms are given a new name in this work so that it will be easy for future AHO researchers to find these novel Artificial Human Optimization Field Algorithms. A total of 6 Artificial Human Optimization Field algorithms titled "Human Safety Particle Swarm Optimization (HuSaPSO)", "Human Kindness Particle Swarm Optimization (HKPSO)", "Human Relaxation Particle Swarm Optimization (HRPSO)", "Multiple Strategy Human Particle Swarm Optimization (MSHPSO)", "Human Thinking Particle Swarm Optimization (HTPSO)" and "Human Disease Particle Swarm Optimization (HDPSO)" are tested by applying these novel algorithms on Ackley, Beale, Bohachevsky, Booth and Three-Hump Camel Benchmark Functions. Results obtained are compared with PSO algorithm.Comment: 25 pages, 41 figure

Allocation in Practice

How do we allocate scarcere sources? How do we fairly allocate costs? These are two pressing challenges facing society today. I discuss two recent projects at NICTA concerning resource and cost allocation. In the first, we have been working with FoodBank Local, a social startup working in collaboration with food bank charities around the world to optimise the logistics of collecting and distributing donated food. Before we can distribute this food, we must decide how to allocate it to different charities and food kitchens. This gives rise to a fair division problem with several new dimensions, rarely considered in the literature. In the second, we have been looking at cost allocation within the distribution network of a large multinational company. This also has several new dimensions rarely considered in the literature.Comment: To appear in Proc. of 37th edition of the German Conference on Artificial Intelligence (KI 2014), Springer LNC

Multi-layer Architecture For Storing Visual Data Based on WCF and Microsoft SQL Server Database

In this paper we present a novel architecture for storing visual data. Effective storing, browsing and searching collections of images is one of the most important challenges of computer science. The design of architecture for storing such data requires a set of tools and frameworks such as SQL database management systems and service-oriented frameworks. The proposed solution is based on a multi-layer architecture, which allows to replace any component without recompilation of other components. The approach contains five components, i.e. Model, Base Engine, Concrete Engine, CBIR service and Presentation. They were based on two well-known design patterns: Dependency Injection and Inverse of Control. For experimental purposes we implemented the SURF local interest point detector as a feature extractor and $K$-means clustering as indexer. The presented architecture is intended for content-based retrieval systems simulation purposes as well as for real-world CBIR tasks.Comment: Accepted for the 14th International Conference on Artificial Intelligence and Soft Computing, ICAISC, June 14-18, 2015, Zakopane, Polan