This paper presents a case study for improving drilling performance by maximizing penetration rate while ensuring that hole conditions are not compromised. The overall aim was to identify and prevent invisible lost time (ILT) and nonproductive time (NPT) by means of pre-drill engineering studies and real-time drilling optimization. This process was conducted to deliver continuous improvement in a three-well drilling campaign in the East Texas Basin. Prior to drilling the series of three wells in the East Texas Basin, a pre-drill study of information from offset wells was used to calibrate engineering models and identify opportunities for improvement. These were primarily identified by the analysis of mechanical specific energy (MSE) and rate of penetration (ROP) to create a driller's road map (DRM) to optimize parameters that can be controlled on the rig floor (rpm, WOB, flow rate). Calibrated torque and drag (T&D) and hydraulics models were developed to compare and monitor model versus actual (MvA) in real time. During the actual drilling of the wells, potential areas of improvement were determined by analyzing MSE and evaluating ILT/NPT. Real-time MSE analysis was conducted during drilling operations to adjust parameters to increase ROP performance. ILT and NPT were reduced by focusing on connection times, optimizing hole cleaning to reduce trip times, increasing flow rate, and improving bit hydraulics. These analyses were used to generate a focused optimization plan to monitor hole conditions at high drilling rates. This plan was incorporated into a recommended real-time process for the wellsite team. This case history is presented for a three-well development pad in the East Texas Basin. The first well of the campaign was drilled one day faster than the previous well had been drilled, and each subsequent well was delivered in a shorter time with an overall improvement of 30.9%. The Driller's Road Map was refined after each well as part of the continuous improvement process. As a result of improved hole cleaning, major sources of ILT were reduced by 47%. The improved hole cleaning was verified by real-time MvA correlation. The methodology described is being used successfully on other multi-well projects in unconventional reservoirs and other drilling market segments.
A method is presented to efficiently analyze drilling data using trend analysis to predict downhole hazards and allow proactive decision making. The workflow is a data-driven process that provides analysis on both real-time (RT) and historical drilling events. For RT application, the method provides the user with an alert functionality prior to the hazardous events occurring. This method is designed to augment the Real-Time Operation Center (RTOC) to provide additional layers of real-time predictive capabilities, historical hindsight, situational awareness, and hazard avoidance. A software program has been developed to incorporate the methodology into a real-time workflow. The core tenet of drilling hazard management (DHM) is process awareness, which is more relevant than ever in the industry. Routine activities such as daily drilling reports (DDR) analysis and manual RT data analysis such as planned versus actual (PVA) data are time consuming and not very efficient because they are highly dependent on the skill sets and experience of the personnel. By using a standardized automated trend analysis, time- or depth-based data can be analyzed to determine the risks and downhole hazards involved in the drilling and completion operations. This paper presents on-bottom analysis on historical wells to show how trend deviation is used to identify potential hazards before they occur. The trend analysis uses percent deviation for specific parameters, such as standpipe pressure, surface torque, flow rate and hookload, to alert the user when thresholds for normal operations have been exceeded. This logic was developed and validated using more than 50 wells throughout the world, and the logic's thresholds were calibrated from these test cases. Alerts are triggered only when criteria for specific hazards are met. This method champions hazards avoidance through prevention and ultimately reduces noproductive time (NPT) in well construction. This system enables efficient and standardized DHM for both real-time and historical analysis. The proactive approach in hazard avoidance helps users to be aware of trend deviation in real-time and increases the user's situational awareness through alerts. The software provides audit capabilities through documenting time-stamped acknowledgment or notes from users. This system also enables faster offset well analysis and supplements real-time data engineers to improve overall efficiency. In this paper you will see real results of how the program performed in a blind testing environment. Results from the test case demonstrate that the program can generate useable alerts well before a potentially hazardous event. The alerts prior to hazardous events could improve situational awareness for rig staff and on-site engineers.
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