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.  

Variations on a Theme: A Bibliography on Approaches to Theorem Proving Inspired From Satchmo

This articles is a structured bibliography on theorem provers, approaches to theorem proving, and theorem proving applications inspired from Satchmo, the model generation theorem prover developed in the mid 80es of the 20th century at ECRC, the European Computer- Industry Research Centre. Note that the bibliography given in this article is not exhaustive

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

ADAPTS: An Intelligent Sustainable Conceptual Framework for Engineering Projects

This paper presents a conceptual framework for the optimization of environmental sustainability in engineering projects, both for products and industrial facilities or processes. The main objective of this work is to propose a conceptual framework to help researchers to approach optimization under the criteria of sustainability of engineering projects, making use of current Machine Learning techniques. For the development of this conceptual framework, a bibliographic search has been carried out on the Web of Science. From the selected documents and through a hermeneutic procedure the texts have been analyzed and the conceptual framework has been carried out. A graphic representation pyramid shape is shown to clearly define the variables of the proposed conceptual framework and their relationships. The conceptual framework consists of 5 dimensions; its acronym is ADAPTS. In the base are: (1) the Application to which it is intended, (2) the available DAta, (3) the APproach under which it is operated, and (4) the machine learning Tool used. At the top of the pyramid, (5) the necessary Sensing. A study case is proposed to show its applicability. This work is part of a broader line of research, in terms of optimization under sustainability criteria.Telefónica Chair “Intelligence in Networks” of the University of Seville (Spain

A survey of agent-oriented methodologies

This article introduces the current agent-oriented methodologies. It discusses what approaches have been followed (mainly extending existing object oriented and knowledge engineering methodologies), the suitability of these approaches for agent modelling, and some conclusions drawn from the survey