SPE PAPER: Published on One Petro, August 31, 2020
Large-Scale Deployment of a Closed-Loop Drilling Optimization System: Implementation and Field Results
On a land-based rig, the driller has many responsibilities and is rarely able to adjust the main process controls—weight on bit (WOB) and revolutions per minute (RPM)—on a continuous basis. The result is suboptimal drilling and longer spud-to-target depth (TD) time than necessary. Automatic, closed-loop optimization removes this burden and results in better and more consistent drilling performance. In this paper, a closed-loop drilling optimization system is presented with results from more than 1,700 wells in the field.
The closed-loop system builds on industry-proven advisory technology and is designed uniquely for petroleum drilling. Because formation characteristics can change rapidly with depth, a fast optimization algorithm based on input signal dithering is used to continually adjust drilling parameters to search for the highest possible rate of penetration (ROP) and lowest possible mechanical-specific energy (MSE). Drilling dysfunctions, such as stick-slip and formation stringers, are treated as discrete time events and mitigated using software protocols triggered by accurate detection algorithms. Also, operation of the inner loop autodriller is of critical importance and controlled using a specialized set of autodriller management protocols.
Over the past 2 years, the system has been deployed on more than 270 rigs for construction of more than 1,700 land wells in North America. One of the main deployment challenges was the need for full organizational buy-in from both rig and office personnel. Another major challenge was the need for parameter limit roadmaps that define reasonable, but nonconservative, optimization limits to be used during the drilling of each well. Drilling performance on approximately 90 wells was analyzed and compared with equivalent offset wells. The result was an ROP improvement of 7.2% and 8.0% (2-year average) and 9.7% and 17.3% (last year average) for the vertical and lateral sections, respectively. A case study is presented highlighting improved ROP and decreased nonproductive time (NPT) when the optimization system was used.
Pason Systems: Stephen W. Lai,James Ng, Aaron Eddy, Sergey Khromov, Dan Paslawski,Ryan van Beurden,Lars Olesen
ExxonMobil Upstream Research Company: Gregory S. Payette, Benjamin J. Spivey
PASON RESOURCE: Published on Pason, July 16, 2020
Drilling rigs contain a staggering amount of complex equipment working in unison to keep your rig active and efficient. With so many tools and technologies working together, sometimes one equipment failure can bring a rig to a halt. How does Pason make sure it doesn’t happen again?
Pason uses Splunk, a data analysis platform, to monitor, record, and report metrics related to your rig’s activity and performance. Learn more about some of the metrics we monitor.
PASON RESOURCE: Published on Pason, July 3, 2020
Wellsite Information Transfer Specification (WITS) can be intimidating, but with Pason, navigating WITS is made easy and reliable. Our easy-to-use software makes Pason the simple solution for our customers’ energy technology needs.
ARTICLE: Published on Drilling Contractor, July 1, 2020
IADC Drilling Contractor Magazine, July/August 2020 Issue, pages 35-37.
Parameter limit roadmaps played key role in ROP/MSE optimization, while automated protocols allowed for mitigation of drilling dysfunctions.
Pason Systems: Stephen Lai, James Ng, Aaron Eddy, Sergey Khromov, Dan Paslawski, Ryan van Beurden, Lars Olesen
ExxonMobil Upstream Research Company: Gregory Payette, Benjamin Spivey
PATENT: Published on United States Patent, June 16, 2020
Method and System for Detecting at Least One of an Influx Event and a Loss Event During Well Drilling
Methods, systems, and techniques for detecting at least one of an influx event and a loss event during well drilling involve using one or both of errors between 1) estimated and measured pit volume, and 2) estimated and measured flow out, to identify or determine whether the influx or loss event is occurring, or to sound some other type of related alert. These determinations may be performed in a computationally efficient manner, such as by using one or both of a time and depth sensitive regression.
Torrione; Peter (Calgary, CA)
Morton; Kenneth (Calgary, CA)
Unrau; Sean (Calgary, CA)
PASON RESOURCE: Published on Pason, April 24, 2020
Automated KPI Reports – Daily Reports
Pason’s Daily KPI Reports provide critical statistics and valuable insights into the previous day’s operations. These KPI reports are generated using sensor data, and can be retrieved from the DataHub, Pason Live mobile app, or auto-generated daily email.
PASON RESOURCE: Published on Pason, April 24, 2020
DAS – Case Study
In 2019, we closely studied a Bakken pad rig as it drilled four offset wells. The rig drilled the wells with and without DAS, which provided excellent comparative data. The crew drilled wells 1 to 4 in sequential order: wells 1 and 2 without DAS, wells 3 and 4 with DAS.
The results speak for themselves.
SPE PAPER: Published on One Petro, April 2, 2020
An Algorithm to Automatically Zero Weight on Bit and Differential Pressure and Resulting Improvements in Data Quality
Weight on bit (WOB) and differential pressure (DIFP) are two essential parameters derived from surface sensors during the drilling process. However, there can be significant errors in these measurements due to improper zeroing of these traces. Regular zeroing of WOB is important to ensure that it is calibrated for additional stands that have been added to the drillstring. Similarly, regular zeroing of DIFP is important to ensure that added hydrostatic pressure, which increases with depth, is taken into account, and to ensure that DIFP has been calibrated to the correct pump rate. In this paper, we quantify the errors due to forgotten and incorrect zeroing, and discuss an algorithm that was developed to automatically zero WOB and DIFP to eliminate these errors.
This study has two main sections. In the first section, the current practice of zeroing WOB (prior to rotary drilling) is analyzed in 40 onshore wells. It is found for 86% of all stands that WOB is either zeroed incorrectly or not at all. An algorithm is developed to determine the appropriate time to perform the zero WOB operation. Using this algorithm, it is found that the average WOB error per stand due to improper zeroing is 16.8 and 17.6% in the vertical and lateral wellbore sections, respectively. Further, it was found that repeated forgotten zeroes could result in large errors, particularly in the vertical where 8% of stands have WOB inaccuracies of more than 30%. In the second section, the analysis is repeated for DIFP and it is found that zeroing DIFP is forgotten in 51% of all stands, resulting in errors of 17.5 and 8.9% in the vertical and lateral, respectively. In the vertical, 9.9% of stands have DIFP inaccuracies of more than 30% due to forgotten zeroing. Applying these algorithms to historic data can eliminate these errors, and improve the effectiveness of data-based drilling optimization and analytics. Further, these algorithms could be implemented in an electronic drilling recorder (EDR) to improve the quality of real-time data at the rig.
Adam C. Neufeldt (Pason Systems)
Stephen W. Lai (Pason Systems)
Sean D. Kristjansson (Pason Systems)
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