Seismic Surveying is a geophysical survey that was conducted to measure the physicals principle in earth's geography like magnetic, gravitational and thermal. There are several simulations that have been produced to be used in oil and gas field, such as Petrel by Schlumberger and ECLIPSE. however, this simulation is confidential and cannot be used by individuals outside the company. Therefore, some of petroleum geologists are not able to use the simulations in their geology analysis. This issue is also experienced by students studying in this field as they are not able to access any simulations. Hence, making them not able to experience the real environment of the process for their future used. The existing software also do not analyse real time data, which will be covered in this project. Oil Well Detection System for Seismic Surveying is a web-based system that aims to analyse data for seismic surveying to give user better understanding on the process before conducting it in real life. This system also uses real time data in order to generate the result for the simulation. Users are able to generate the data in numeric data sets, 2D or 3D images. Notifications will be sent to users whenever there are data generating the best limestone result. This is to make sure that users have the best field for new oil reservoir and comparing the data of seismic surveying to make sure the best region to drill. The sensors technology will be used to detect the elements in limestone and send the data to user's smartphones. Prototype Model Methodology is used throughout the development process alongside Firebase Cloud Database for storing information. This project will help petroleum geologists and students to experience the real time simulation in order to have better understanding about seismic surveying before conducting it in real life. They also can use it as study purposes as it is beneficial to students.
CITATION STYLE
Puad, N. M., Siraj, M. M., & Sulaiman, N. R. (2020). Oil Well Detection System for Seismic Surveying Based on Internet of Things (IOT). In IOP Conference Series: Materials Science and Engineering (Vol. 884). IOP Publishing Ltd. https://doi.org/10.1088/1757-899X/884/1/012056
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