This paper will describe a new method for using a computer workflow to automatically choose the safest and lowest cost option wellbore trajectories with minimum input needed from the user. It allows oil and gas industry operators' drilling, subsurface and service provider users to plan, risk assess and lower the cost of drilling wellbores by better understanding earlier in the planning and design phase to better invest in time and money for the best wellbore trajectory options. Wellbore placement challenges include but are not limited to choosing an optimal surface location, intersection of geologic target volume, avoiding faults and geohazards, and an assessment of the wellbore commercial and engineering risks to drill successful oil and gas production wellbores. This method involves a targeted approach focusing on drilling operational parameters such as Drilling Difficulty Index (DDI) and a financial index such as Measure Depth (MD) and additional engineering limiting factors or constraints such as Dog Leg severity (DLS), Maximum Inclination (MI) and kick of depth (KOD). Utilising this technique improves the efficiency of the risk assessment and optimisation aspects for a wellbore in the design phase. One of the most important aspects of efficiency improvement is the ability for multi discipline teams to work on the same wellbore design challenges in collaboration. High risk wellbore trajectory options are highlighted early on in the design phase and removed from the viable surface to target wellbore options list.
Interactive model and wellbore data 3D visualisation helps the user choose wellbores which naturally avoid geological faults, nearby wellbores, and provide improved wellbore designs to intersect hard geologic targets. Geologic targets which represent the largest wellbore risk and cost are identified, allowing for a major manual iteration of the surface location followed by the wellbore trajectory design. In this practice, parameters are defined to separate all the possible wellbore trajectories and they are arranged individually and finally, they are merged and tested for ultimate ranking to choose the best fit. The ranking method described in this paper is non-weighted.
As part of a new operator Operational Excellence and Drilling the Limit initiative, the viability of the trajectory optimiser has been reviewed for incorporation in upcoming drilling projects. During the design and execution process for wells drilled offshore Malaysia, asset management, subsurface, geoscience and drilling teams utilise data from a large number of models and data sources to perform the numerous and time consuming trajectory design iterations. The trajectory optimiser addresses the cost and time spent in the design and execution phase by reducing the time spent by over three weeks, which equates to over 300k USD in project costs for a typical five well drilling campaign. Intangible cost savings can be significantly higher than the project users reduced time saving. This method highlights both the lowest and highest risk well trajectory options allowing for a higher degree of design Optimisation and equipment utilisation earlier in the project lifetime which promotes improved production and lower drilling and potentially HSE risks in wellsite operations.