The Assumption of Zero Leakage from Permanently Abandoned Wells on the Norwegian Continental Shelf

2021 ◽  
Author(s):  
Rune Vikane ◽  
Jon Tømmerås Selvik ◽  
Eirik Bjorheim Abrahamsen ◽  
Hans Petter Lohne

Abstract Quality data is essential for calculations of expected leakage in wells post Permanent Plug and Abandonment (PP&A). Such data may come from surveys studying hydrocarbon leakage to the marine environment. However, recent literature suggests that current regulatory practices for environmental surveys are suboptimal, giving reason to question the assumption that wells have experienced zero leakage from the deep reservoir post PP&A on the Norwegian Continental Shelf (NCS). We investigate whether such an assumption is credible. The credibility of the assumption of zero leakages is investigated through a review of literature addressing the integrity of wells post PP&A on the NCS, with particular emphasis on a 2021 report from the Norwegian Environmental Agency (NEA). Based on the review, the strength of knowledge supporting the assumption that no wells on the NCS have experienced leakages from their deep reservoirs is discussed. The implications of the uncertainty associated with the assumption of zero leakage on the NCS, the rationale for collecting more relevant data, and how these data may be obtained is also discussed in brief. The NEA report details the current regulatory practice for environmental surveys on the NCS. This regulatory practice, as it is described in the NEA report, give limited support to a zero leakage assumption. Norwegian regulations require two environmental surveys post Cessation of Production (CoP). These surveys may however occur in the period between CoP and PP&A, and the closest test stations are generally located 250 meters from the wells. Environmental surveys carried out that far from the well, and possibly prior to PP&A, influence data quality. We argue that the environmental survey data claiming zero leakage, lack sufficient evidence. Thus, based on the reviewed literature outlining the current environmental survey practice, although PP&A well design on the NCS should build on sound principles, we are not able to conclude on the assumption of zero leakage. The interest in risk-based PP&A approaches is increasing globally, and risk-based approaches rely on credible leakage calculations. The failure rates used in these leakage calculations should be based on quality data. The NEA report and other literature indicate that the quality of post PP&A leakage data on the NCS is questionable, and in some cases the data are non-existent. The paper includes suggestions on how to improve the regulatory practice related to environmental surveys.

2019 ◽  
Author(s):  
Sarah Gasda ◽  
Ivar Aavatsmark ◽  
Bahman Bohloli ◽  
Helge Hellevang ◽  
Jan Nordbotten ◽  
...  

2021 ◽  
Author(s):  
Subhadeep Sarkar ◽  
Mathias Horstmann ◽  
Tore Oian ◽  
Piotr Byrski ◽  
George Lawrence ◽  
...  

Abstract One of the crucial components of well integrity evaluation in offshore drilling is to determine the cement bond quality assuring proper hydraulic sealing. On the Norwegian Continental Shelf (NCS) an industry standard as informative reference imposes verification of cement length and potential barriers using bonding logs. Traditionally, for the last 50 years, wireline (WL) sonic tools have been extensively used for this purpose. However, the applicability of logging-while-drilling (LWD) sonic tools for quantitative cement evaluation was explored in the recent development drilling campaign on the Dvalin Field in the Norwegian Sea, owing to significant advantages on operational efficiency and tool conveyance in any well trajectory. Cement bond evaluation from conventional peak-to-peak amplitude method has shown robust results up to bond indexes of 0.6 for LWD sonic tools. Above this limit, the casing signal is smaller than the collar signal and the amplitude method loses sensitivity to bonding. This practical challenge in the LWD realm was overcome through the inclusion of attenuation rate measurements, which responds accordingly in higher bonding environments. The two methods are used in a hybrid approach providing a full range quantitative bond index (QBI) introduced by Izuhara et al. (2017). In order to conform with local requirements related to well integrity and to ascertain the QBI potential from LWD monopole sonic, a wireline cement bond log (CBL) was acquired in the first well of the campaign for comparison. This enabled the strategic deployment of LWD QBI service in subsequent wells. LWD sonic monopole data was acquired at a controlled speed of 900ft/h. The high-fidelity waveforms were analyzed in a suitable time window and both amplitude- and attenuation-based bond indexes were derived. The combined hybrid bond index showed an excellent match with the wireline reference CBL, both in zones of high as well as lower cement bonding. The presence of formation arrivals was also in good correlation with zones of proper bonding distinguishable on the QBI results. This established the robustness of the LWD cement logging and ensured its applicability in the rest of the campaign which was carried out successfully. While the results from LWD cement evaluation service are omnidirectional, it comes with a wide range of benefits related to rig cost or conveyance in tough borehole trajectories. Early evaluation of cement quality by LWD sonic tools helps to provide adequate time for taking remedial actions if necessary. The LWD sonic as part of the drilling BHA enables this acquisition and service in non-dedicated runs, with the possibility of multiple passes for observing time-lapse effects. Also, the large sizes of LWD tools relative to the wellbore ensures a lower signal attenuation in the annulus and more effective stabilization, thereby providing a reliable bond index.


2021 ◽  
Author(s):  
Jon Gustav Vabø ◽  
Evan Thomas Delaney ◽  
Tom Savel ◽  
Norbert Dolle

Abstract This paper describes the transformational application of Artificial Intelligence (AI) in Equinor's annual well planning and maturation process. Well planning is a complex decision-making process, like many other processes in the industry. There are thousands of choices, conflicting business drivers, lots of uncertainty, and hidden bias. These complexities all add up, which makes good decision making very hard. In this application, AI has been used for automated and unbiased evaluation of the full solution space, with the objective to optimize the selection of drilling campaigns while taking into account complex issues such as anti-collision with existing wells, drilling hazards and trade-offs between cost, value and risk. Designing drillable well trajectories involves a sequence of decisions, which makes the process very suitable for AI algorithms. Different solver architectures, or algorithms, can be used to play this game. This is similar to how companies such as Google-owned DeepMind develop customized solvers for games such as Go and StarCraft. The chosen method is a Tree Search algorithm with an evolutionary layer on top, providing a good balance in terms of performance (i.e., speed) vs. exploration capability (i.e., it looks "wide" in the option space). The algorithm has been deployed in a full stack web-based application that allows users to follow an end-2-end workflow: from defining well trajectory design rules and constraints to running the AI engine and evaluating results to the optimization of multi-well drilling campaigns based on risk, value and cost objectives. The full-size paper describes different Norwegian Continental Shelf (NCS) use cases of this AI assisted well trajectory planning. Results to-date indicate significant CAPEX savings potential and step-change improvements in decision speed (months to days) compared to routine manual workflows. There are very limited real transformative examples of Artificial Intelligence in multi- disciplinary workflows. This paper therefore gives a unique insight how a combination of data science, domain expertise and end user feedback can lead to powerful and transformative AI solutions – implemented at scale within an existing organization.


2009 ◽  
Vol 44 (5) ◽  
pp. 53-58 ◽  
Author(s):  
H. Rye ◽  
M. Reed ◽  
I. Durgut ◽  
D. Ø. Eriksen ◽  
R. Sidhu ◽  
...  

2005 ◽  
Vol 18 (5-6) ◽  
pp. 428-450 ◽  
Author(s):  
M. Reistad ◽  
A.K. Magnusson ◽  
S. Haver ◽  
O.T. Gudmestad ◽  
D. Kvamme

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