This paper discusses on the new method of MWD surveying in drilling operations. It highlights the ability to take surveys faster than the conventional method while minimizing drilling risks. This resulted in a significant time reduction of the overall survey operations. The MWD survey package normally requires the BHA to be stationary before it can start to acquire new survey data. Previous MWD survey systems monitored drilling fluid flow rate to trigger the MWD survey acquisition. This new MWD survey technique monitors rotation, optimising low noise detection, earlier. The new method takes less survey time, the pumps off time removed from the survey period. This new method has been utilized in 4 out of 5 wells throughout the drilling campaign. The benefits can be clearly quantified from the comparison between the conventional and new approach. Based on the Drilling Mechanical Logs, the new method has proven to be able to shorten the surveying time by up to 80% compared to conventional. This translated to approximately 8.7 hours of rig time savings for the drilling phase of the project. Apart from time saving, it reduces stuck pipe risk by not having to stop pumping while also minimizing pipe stationary time. With the simplified survey operations, there is less likelihood of facing survey problems related to pump, signal and any other issues that may lead to the need of repeating survey. Companies operating the exploration and production of oil, gas and water energy resources are continually looking for methods and techniques to reduce the time taken to drill and construct wells. The drilling phase is typically where there is a higher cost due to the drilling rig daily spread cost and the associated added environmental, health and safety risk aspects. Typically wellbore construction process is designed with a specified minimum tolerance for placing the wellbore inside the desired geologic zone or horizon, avoiding offset wellbores and geohazards and surveying the wellbore position sufficiently accurately to enable a relief well to be drill in the event of a well blow out. Wells drilled during the recent five well campaign, offshore Malaysia have utilised this new method for taking surveys with reduced survey time as part of the new operator Operational Excellence and Drilling the Limit initiatives.

Along-hole Depth (AHD) is the most fundamental subsurface wellbore measurement made. Well depth is the main descriptor of wellbore position, measured from zero depth point (ZDP). This is translated into vertical depth (V) using inclination (I). V is the main descriptor subsurface wellbore events and then North (N) and East (E) act as the Qualifying descriptions of V. Well depth is commonly described as measured depth (MD) and is used to describe well construction, navigation and collision avoidance, drilled geologies, reservoir properties, fluid gradients and interfaces, production, and subsurface positioning of well services. AHD is a calibrated and corrected well depth measurement defined using a specific rig-state and can deliver improved subsurface position and positional uncertainty. Well depth, I and azimuth (A) are used to calculate subsurface 3D position. Well depth is measured at surface, represented by drillpipe or wireline length. I and A are subsurface measurements referenced to the provided well depth. These together provide the navigation information required to arrive at the 3D positions of N, E, and V. These positions are used to define the location of subsurface events such as well placement, geological horizons and fluid contacts. This paper outlines a method ("3D method") for defining 3D subsurface positional locations using "way-points" (Bolt 2021). Way-points represent a sequential series of specific, calibrated, 3D positional locations each defined by calibrated and corrected AHD. Based on Pythagorean geometry using AHD, I, and A measurements, these are converted into N, E, and V positions. Each way-point has a specific N, E, and V positional uncertainty. Four component accuracies are used to describe the individual AHD, I and A measurement uncertainties at each way-point: calibration and observation, applied correction, model-fit, and a fixed-term applicable to all observations. AHD, I, and A measurement uncertainties which are converted into individual interval N, E, and V positional uncertainties and sequentially concatenated. The method provides a simplified yet accurate solution to 3D positional and positional uncertainty. The calculations demonstrate the dependency of the positional and positional uncertainty results on both interval spacing between way-points and measurement accuracy. The example results demonstrate that each well has its own specific and unique N, E and V positional uncertainty description. Specific positional uncertainty requirements of operators can be answered to through instrumentation accuracies and way-point interval spacing defined in the well survey program. Well placement can be more easily portrayed, reservoir characteristics more confidently reported, and asset volume estimation improved.

Drilling oil and gas wells is a complex process involving many disciplines and stakeholders. This process occurs in a context where some pieces of information are unknown, or are often incomplete, erroneous or at least uncertain. Yet, during drilling engineering and construction of a well, drilling data quality and uncertainty are barely addressed in an auditable and scientific way. Currently, there are few or no placeholders in engineering and operational databases to document uncertainty and its propagation.The SPE has formed a cross-disciplinary technical sub-committee to investigate how to describe and propagate drilling data quality and uncertainty. The sub-committee is a cooperation between the Drilling System Automation, Wellbore Positioning, and Drilling Uncertainty Prediction Technical Sections. As the topic is vast and complex, a systematic method was adopted, where multiple user stories or pain points were generated, and ranked with the most compelling user story analyzed in detail. From this approach, a series of multi-disciplinary workflow - drilling data generators - can now be captured and described in terms of data quality and propagation of uncertainty.The paper presents details of one "user story" focused on capturing the description of the quality and uncertainty of depths. Multiple "use cases" have been extracted from this single "user story" exemplifying how multiple stakeholders and disciplines manage, communicate, and understand the notion of wellbore depth and its relative uncertainty. Current data stores have the main objective of recording the results of processes but have very limited capabilities to store how the interdisciplinary processes generated and cross-related these results. The study explores the use of semantic graphs to capture those multidisciplinary data relationships. A minimum vocabulary has been created using just a few tens of concepts that has sufficient expressiveness to describe all the extracted "use cases", showing that the semantic graph method has the potential to describe a broad range of complex drilling related processes. The study also demonstrates that use of a parallel graph, employing other notions that do not expressly refer to the processes that generated the data can capture the description of how uncertainty propagates between each of those concepts.This paper describes the development of an initial reference implementation of semantic graph manipulation, the associated vocabulary and the description of uncertainty and quality notions and their linkage in terms of uncertainty propagation. This reference implementation will be available as open source to the industry drilling community allowing software solutions that capture and describe the generation of drilling data through multi-disciplinary workflows, and how they relate in terms of uncertainty propagation.

Summary Drilling oil and gas wells is a complex process involving many disciplines and stakeholders. This process occurs in a context where some pieces of information are unknown, or are often incomplete, erroneous, or at least uncertain. Yet, during drilling engineering and construction of a well, drilling data quality and uncertainty are barely addressed in an auditable and scientific way. Currently, there are few or no placeholders in engineering and operational databases to document uncertainty and its propagation. The Society of Petroleum Engineers (SPE) has formed a cross-disciplinary technical subcommittee to investigate how to describe and propagate drilling data quality and uncertainty. The subcommittee is a cooperation between the drilling system automation, wellbore positioning, and drilling uncertainty prediction technical sections. As the topic is vast and complex, a systematic method was adopted, where multiple user stories or pain points were generated and ranked with the most compelling user story analyzed in detail. From this approach, a series of multidisciplinary workflows (drilling data generators) can now be captured and described in terms of data quality and propagation of uncertainty. The paper presents details of one user story focused on capturing the description of the quality and uncertainty of depth measurements. Multiple use cases have been extracted from this single user story exemplifying how multiple stakeholders and disciplines manage, communicate, and understand the notion of wellbore depth and its relative uncertainty. Current data stores have the main objective of recording the results of processes but have very limited capabilities to store how the interdisciplinary processes generated and cross-related these results. The study explores the use of semantic networks to capture those multidisciplinary data relationships. A minimum vocabulary has been created using just a few tens of concepts that has sufficient expressiveness to describe all the extracted use cases, showing that the semantic network method has the potential to describe a broad range of complex drilling-related processes. The study also demonstrates that use of a multilayered graph, employing other notions that do not expressly refer to the processes that generated the data, can capture the description of how uncertainty propagates between each of those concepts.

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