This paper (SPE 51181) was revised for publication from paper SPE 35077, first presented at the 1996 IADC/SPE Drilling Conference held in New Orleans, 12-15 March. Original manuscript received for review 12 June 1996. Revised manuscript received 30 April 1997. Paper peer approved 17 April 1998. Summary This paper presents an alternative planning approach to the drilling and completion process, technical limit, which has resulted in a step change in Woodside's performance. Three new wells and six subsea completions were finished 20% under budget with this tool and with a simple philosophy characterized by the following questions.What is current performance?What is possible?What is needed to get there? The target was to drill a directional well in 20 days when the previous best time was 42 days. A target of 12 days was set on subsea completions, although a conventional approach had previously been 20+ days. The methodology was to ask what would be possible if everything went perfectly on every operation making up the well time. This is not the usual trouble free time but a well time built up of individual components, with each component representing its theoretical best performance. Details of how the approach was used to plan, and operational data that confirm that the technical limit can be approached are presented. As a result, the well construction performance delivered step change improvement when managed against the technical limit. P. 197
Step Change Improvement and High Rate Learning are Delivered by Targeting Technical Limits on Sub-Sea Wells. SPE Members Abstract This paper presents an alternative approach to the drilling and sub-sea completion process, the Technical Limit, which has resulted in a "Step Change" in Woodside's performance. Using a simple philosophy characterised by the questions:–Where are we now?–What is possible?–How do we get there? and applying this tool, three new wells and six subsea completions were completed 20% under budget. Our target was to drill a directional well in 20 days when the previous best was 42 days. On subsea completions a target of 12 days was set when a conventional approach had previously set 20+ days. The approach was to ask what would be possible if everything went perfectly with every operation making up the well time. This isn't the usual trouble free time but a well time built up of individual components, with each component performing it's theoretical best performance. Presented is operational data which confirms that the Technical Limit can be approached. As a result the well construction performance when managed against the Technical Limit delivered step change performance improvement with high rate of learning. Introduction Woodside's drilling performance offshore on the North West Shelf of Australia from 1968 to 1992 was erratic. A simple plot of time versus total depth (Figure 1), showed unacceptable scatter and a high average drilling time, particularly when benchmarked against published data (Noerager et al). The authors believed the well construction process was not in control. When faced with an upcoming development project (Wanaea and Cossack developments) we undertook to remedy this. To get the desired performance an aggressive target setting and planning methodology was developed based on the question "What is possible?" rather than the question "How can we improve?" Our approach was greatly influenced by achievements in other parts of the world. During the late 70s/early 80s, as documented by Shute et al, Conoco UK Ltd set some drilling operations standards in the North Sea which in our opinion endure today as world class. A major factor claimed in the success of this work came from time analysis which rigorously pursued the identification and removal of drilling problems. The application of this approach was extremely successful. Work by Huber et al also in the North Sea, took a similar approach which, likewise produced excellent results. Latterly Unocal in Thailand have apparently been setting standards in the Far East few can match. Unfortunately, Unocal has published very little on how this high level performance has been achieved. We understand that necessity and aggression drove their improvements. The high level objective for the Wanaea and Cossack projects the requirement for highly productive wells and low construction cost. P. 299
Drilling efficiency is an often used term for various measures that purport to represent the relative difference between current performance and some reference performance. Non Productive Time (NPT) is globally used as an analogue for efficiency. Many reported efficiency measurements are in the 90% range and NPT in the 20% range when the overall drilling and completion times are some 50% or more slower than Best In Class (BIC) as determined by external benchmarking. Current measures of drilling efficiency and NPT are both misleading and poorly defined. This paper evaluates these misleading measurements and introduces the application of a meaningful measure of drilling efficiency. The term drilling efficiency is used for a short description; the same process applies to all well operations including drilling, testing, completion, well intervention, workover and plug and abandonment operations; the well life cycle. Means to estimate overall performance potential including Technical Limit (TL), Maximum Theoretical Performance (MTP) and benchmarking are explained in their historical context and current applications. These provide the future state target for gap analysis to current state performance. This gap allows the quantification of Invisible Lost Time (ILT) whose reduction is the means to true performance improvement over deficiency correction as measured by NPT. ILT commonly gets included in Productive Time (PT) as logged in daily report data-base systems and will remain invisible without such a gap analysis. It is a more important measure of performance efficiency than both NPT and the often used ‘uptime’ of a drilling rig. Measurements of industrial process (construction, manufacturing) efficiency are presented and, through analogy, applied to drilling. The result is a robust methodology for the industry to measure drilling efficiency. This paper also includes a review of and suggestions for a normalization index for the relative complexity of various drilling operations (Appendix I). A simple and comprehensive well complexity index methodology that can be applied to adjust the calculated MTP for any well to develop a calculation based Technical Limit will benefit the industry. An industry approach to establish a defined well complexity index for universal application to drilling is suggested. A drilling efficiency model with reference to a calculation method is available for the industry to measure the real gap to 100% efficiency. This will in general produce vastly lower efficiency numbers for current performance than some of the inappropriate efficiency calculations currently used. It provides organizations with a more accurate view of the improvement potential they could aspire to reach, and become an enabler for the global oil and gas industry to improve performance and reduce cost of wells. The recommended methodologies and efficiency measure provides the first realistic number for drilling efficiency. It will be a wake-up call to the industry and initially show much lower efficiency numbers than many organizations currently calculate and report. It will be an eye opener to managers who want to truly assess the performance of their drilling operations and provide them the information to set new performance goals. The challenge will be how willing the managers are to show how badly we perform as an industry today, and how persistent they are in the needed step change and follow through with improvement steps.
Technical Limit is an approach to well construction management that has resulted in a step change in Woodside's drilling and completion performance. The method has resulted in halving average historical drilling time and executing subsea completions in less than half benchmarked times. This paper focuses on the management "soft" issues that complemented the approach and provided for achievement of outstanding performance. From goal setting to detailed planning and execution, breakthrough performance based on Technical Limit required a special environment in which all could perform. Attributes of this environment and the difficulties and emotions experienced by the team members will be described.
Drilling performance is usually benchmarked by analyzing the time spent on well construction and the degree to which planned times and budgets are achieved. Learn curve analysis can provide indicators of relative improvement over a campaign, and position on the learning curve can provide a measure of process maturity. However, the variability of the data makes it difficult to obtain a good fit to the model and assess maturity. The principal cause of the discrepancy between planned and actual times is trouble. Trouble is accounted for in planning by a multiplicative contingency factor. This implies that trouble time is dependent on well or well section length. Based on a standardized analysis of drilling performance for a wide range of wells we find that this assumption is not valid and that trouble time is not significantly correlated with well or well section length. However, we do find that the probability of trouble is significantly correlated with length, and that a probability plot of trouble time for a group of wells or well sections provides a robust measure of drilling process maturity. We present results of applying this analysis to a variety of well types and propose some metrics for assessing drilling process maturity. Introduction Drilling performance depends on many human, technical and geological factors and usually improves over time in a given region as crew experience and knowledge increases. Using the Learning Curve model first applied to drilling by Brett and Millheim1 performance is expected to plateau at a level determined only by technical factors (the Technical or Capability Limit). The rate at which performance approaches this limit provides a measure of learning rate. Using a simple exponential model derived from manufacturing, learning rate exponents between 0.3 and 1.0 are observed. Values of 0.25 or below were interpreted as showing poor or no learning and values above 0.8 as showing good learning. Reductions in drilling time for the last well in a sequence compared to the first ranged between 30 and 65%. An industry average learning rate of 0.34 was established for a wide variety of wells. Sequences of 4–19 wells were found to show learning. Irrgang et al2 noted that the reduction in time for a sequence of 7 wells arose not only from reduction in the amount of trouble time but also in the time taken for planned activities. This a manifestation of "Invisible Lost Time" as identified by Kadaster et al3. Application of the Technical Limit methodology to identify and remove this lost time is described by Bond et al4 . A Learning Curve model was used by Zoller et al5 to generate a probabilistic model for the expected time-depth curve for a well. Different learning curves were used for different clases of operations, and the effect of learning was observed to reduce the tail values in the final distribution. However, modeling parameters were not derived from historical data. Learning Curve Analysis Whilst the magnitude of reduction in time achieved and the rate at which it was achieved provide a measure of maturity of the drilling process, use of the Learning Curve for this purpose is complicated by the variability of trouble episodes and by the differences in design between wells over which performance is evaluated. Well construction time T is modeled byT=C1+C2·e−C3(1-n) whereT=TimeC1=Technical LimitC2=Learning PotentialC3=Learning Raten=Well Sequence
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