There are various factors that contribute to the Well planning. Be it cost, complexity of the reservoir, safety measures, isolating problem areas, engineering, etc., The whole process of well analysis takes a lot of time and efforts, as the method used is mostly manual. In this abstract, we explain the Big Data approach used to perform Well Planning which significantly reduces the drilling engineer time. Future, possible suggestions to the existing system are also discussed in this paper. Over the past few years, the concept of Big Data has gradually matured. Drilling Engineers, Data Management and the Solution Development Team have jointly discussed the potential and the functionality if this concept to optimize the Drilling Engineer performance and timeframe for preparing and delivering drilling programs for the new development wells. EDM (Enterprise Drilling Management System), drilling suite of applications, In-House drilling data extraction tool with Web based interface, and many different types of excel sheets, were considered as the input sources. Well planning process was automated for offset and related data acquisition, results and knowledge were captured in a central repository, which will be used in future endaovers. Fig 1. Shows existing architecture and proposed roadmap to develop a robust system for predicting the new drilling well location. For example, all the data related to NPT records for the wells in the delimited area, their reports, and daily drilling records were brought together. Then, a cutoff value was decided and color coding was used to highlight wells near the offset wells. This layer was overlaid on GIS map to see the exact location and on the In-House web based tool. The criticality was highlighted using the color code. Based on the above, this solution aims to enhance the drilling engineer performance and represents a major contribution towards increasing the efficiency, as wells as the improvement of the drilling operations. In Future, the team plans to add more complex algorithms based on refining the search criteria, extracting data for the offset wells and implementing Artificial Neural Network. The team is also working on connecting corporate datastore for the exploration, production, and development data to EDM. As of now, the EDM is connected to Corportate database through views to access Directional surveys for Wells. Bringing all the data types and sources together has made the analysis of offset wells simpler. The process is more automatic and efficient. It has transformed the process from having local copies of the data, copying data from different sources, and manually applying formulas and generating reports into a centralized repository, in addition to dynamic and automatic reporting. It also, introduces better accessibility from different drilling engineers for enhanced communication, collaboration and knowledge sharing.

The challenges of drilling new wells are increasingly associated with minimizing HSE risks, that relate to chemical radioactive sources in the Bottom Hole Assembly for formation evaluation. Drilling risks such as differential sticking, also necessitates investigation of alternative petrophysical data gathering methodologies that can fulfil these requirements. Surface Data Logging presents a viable alternative in mature fields, satisfying petrophysical data gathering and interpretation in real-time as well, as traditional geological applications and offset well correlations in a way, to optimize well construction costs. During the planning phase, a fully integrated approach was adopted including advanced cutting and advanced gas analysis to be deployed, in this case study, well together with experienced well site personnel. A comprehensive pre-well study was conducted reviewing all offset nearby wells data. The workflow included provision of full real-time advanced cuttings and gas analysis for formation evaluation and reservoir fluid composition, lithology description, and addressing effective hole cleaning concerns. The advanced Mud Logging services was run in parallel to the Logging While Drilling services for a few pilot wells, in order to correlate downhole tool parameters, with respect to data quality control, to identify the petrophysical character of the formation markers for benchmarking future data gathering requirements. In addition to the potential use of standalone fully integrated advanced Mud Logging to reduce risks and minimize field development costs. With the help of experienced wellsite geologist on location and real time advanced gas detection utilizing high resolution mass spectrometer and X-Ray fluorescence (XRF) and X-Ray Diffraction (XRD) data, geological boundaries and formations tops were accurately identified across the whole drilled interval. Modern and advanced interpretation techniques for the integrated analysis were proven to be effective in determining sweet spots of the reservoir, fluid type, and overall reservoir quality. Deployment of fully integrated mud logging solutions with new interpretation methodologies can be effective in providing a better understanding of reservoir geological and petrophysical characteristics in real-time, offering viable alternative for minimizing formation evaluation sensors in the BHA, particularly eliminating radioactive sources, while reducing overall developments costs, without sacrificing formation evaluation requirements.