Measuring and Analyzing the Magnetic Content of Drilling Fluid

2021 ◽  
Author(s):  
Pouya Khalili ◽  
Arild Saasen ◽  
Mahmoud Khalifeh ◽  
Bodil Aase ◽  
Geir Olav Ånesbug
Keyword(s):  
Magnetic Particles ◽  
Drilling Fluid ◽  
Measurement Data ◽  
X Ray Diffraction ◽  
Case Scenario ◽  
Magnet System ◽  
Worst Case ◽  
Drilling Rig ◽  
The North ◽  
Downhole Tool

Abstract Magnetic contamination of drilling fluid can impact the accuracy of a directional survey by shielding the magnetic field. Additionally, this contamination, such as swarf or finer magnetic particles, can agglomerate on the downhole tool or BOP and cause tool failure in the worst-case scenario. Thus, it is necessary to measure the magnetic content of drilling fluid. However, there is no recommended practice in API or ISO for this purpose. A simple experimental setup and measurement system was developed that can be easily deployed in the rig site to measure the magnetic contamination of drilling fluid. 47 drilling fluid samples were collected from a multilateral production well drilled with a semi-submersible drilling rig located in one of the North Sea's fields. The magnetic content of these samples was measured using the established method, and the microstructure of the collected content was analyzed using a scanning electron microscope (SEM) and x-ray diffraction analysis (XRD). Ditch magnets are commonly installed in the flowline on the rig to remove the swarf and finer magnetic particles, if the design is optimized. Ditch magnet measurement data of the well that the drilling fluid samples were collected from is presented. Operational details and common factors that might increase the production of the magnetic content were also investigated. By comparing the measured magnetic contamination of the drilling fluid samples and ditch magnet measurement data, it was possible to evaluate the efficiency of the ditch magnet system.

scholarly journals Identification of NLOS and Multi-Path Conditions in UWB Localization Using Machine Learning Methods

2020 ◽  
Vol 10 (11) ◽  
pp. 3980 ◽  
Author(s):  
Cung Lian Sang ◽  
Bastian Steinhagen ◽  
Jonas Dominik Homburg ◽  
Michael Adams ◽  
Marc Hesse ◽  
...  
Keyword(s):  
Machine Learning ◽  
Indoor Localization ◽  
Measurement Data ◽  
Ultra Wideband ◽  
Machine Learning Techniques ◽  
Line Of Sight ◽  
Support Vector ◽  
Case Scenario ◽  
Worst Case ◽  
Worst Case Scenario

In ultra-wideband (UWB)-based wireless ranging or distance measurement, differentiation between line-of-sight (LOS), non-line-of-sight (NLOS), and multi-path (MP) conditions is important for precise indoor localization. This is because the accuracy of the reported measured distance in UWB ranging systems is directly affected by the measurement conditions (LOS, NLOS, or MP). However, the major contributions in the literature only address the binary classification between LOS and NLOS in UWB ranging systems. The MP condition is usually ignored. In fact, the MP condition also has a significant impact on the ranging errors of the UWB compared to the direct LOS measurement results. However, the magnitudes of the error contained in MP conditions are generally lower than completely blocked NLOS scenarios. This paper addresses machine learning techniques for identification of the three mentioned classes (LOS, NLOS, and MP) in the UWB indoor localization system using an experimental dataset. The dataset was collected in different conditions in different scenarios in indoor environments. Using the collected real measurement data, we compared three machine learning (ML) classifiers, i.e., support vector machine (SVM), random forest (RF) based on an ensemble learning method, and multilayer perceptron (MLP) based on a deep artificial neural network, in terms of their performance. The results showed that applying ML methods in UWB ranging systems was effective in the identification of the above-three mentioned classes. Specifically, the overall accuracy reached up to 91.9% in the best-case scenario and 72.9% in the worst-case scenario. Regarding the F1-score, it was 0.92 in the best-case and 0.69 in the worst-case scenario. For reproducible results and further exploration, we provide the publicly accessible experimental research data discussed in this paper at PUB (Publications at Bielefeld University). The evaluations of the three classifiers are conducted using the open-source Python machine learning library scikit-learn.

scholarly journals Efficient Removal of Magnetic Contamination from Drilling Fluids - The Effect on Directional Drilling

2020 ◽  
pp. 1-14
Author(s):  
Arild Saasen ◽  
Benny Poedjono ◽  
Geir Olav Ånesbug ◽  
Nicholas Zachman
Keyword(s):  
Magnetic Particles ◽  
Barents Sea ◽  
Drilling Fluid ◽  
Drilling Fluids ◽  
Directional Drilling ◽  
The North ◽  
Uncertainty Calculation ◽  
The North Sea ◽  
Drilling Rigs ◽  
Sea Area

Abstract Magnetic debris in a drilling fluid have a significant influence on the ability of the drilling fluid to maintain its function. Down hole logging can suffer from poor signal to noise ratios. Directional drilling in areas close to the magnetic North Pole, such as in the Barents Sea, Northern Canada or Russia can suffer because of magnetic contamination in the drilling fluid. Magnetic particles in the drilling fluid introduce additional errors to the magnetic surveying compared to those normally included in the ellipsoid of uncertainty calculation. On many offshore drilling rigs, there are mounted ditch magnets to remove metallic swarf from the drilling fluid. These magnets normally only remove the coarser swarf. In this project, we use a combination of strong magnets and flow directors to significantly improve the performance of the ditch magnets. This combination, together with proper routines for cleaning the ditch magnets, significantly helps to clean the drilling fluid. Through the combined use of flow directors and ditch magnets, it was possible to extract more than five times as much magnetic contamination from the drilling fluid as normal compared with other proper ditch magnet systems. This is verified by comparing the ditch magnet efficiencies from two drilling rigs drilling ERD wells in the North Sea area. In the paper, it is discussed how the accuracy of directional drilling and well position effected by various interferences can be improved by the use of a drilling fluid with minimal effect to the MWD measurement.

An Experimental Study of the Hydrodynamic Effects of Marine Growth on Wave Energy Converters

2013 ◽  
Author(s):  
Roxana Tiron ◽  
Sarah Gallagher ◽  
Kenneth Doherty ◽  
Emmanuel G. Reynaud ◽  
Frédéric Dias ◽  
...  
Keyword(s):  
Experimental Study ◽  
Wave Energy ◽  
Large Scale ◽  
Energy Resource ◽  
Algal Growth ◽  
Scale Model ◽  
Case Scenario ◽  
Worst Case ◽  
Ocean Surface Waves ◽  
The North

Even though the outstanding energy resource provided by ocean surface waves has long been recognized, the extraction of wave power is still in its infancy. Meanwhile, the increased interest in sustainable energy alternatives could lead to large-scale deployments of wave energy convertors (WECs) worldwide in the near future. In this context, the interaction of WECs with the marine environment is an issue that has come under increased scrutiny. In particular, the accumulation of biological deposits on the device (commonly referred to as biofouling) could lead to a modification in the behaviour and performance of the device design. For coastal devices in the North-Eastern Atlantic region, the main contributors to biofouling are likely to be the brown algae from the genus Laminaria. In the experimental study described in this paper, we have investigated the effects of algal growth on a scale model of the Oyster 800 WEC, a technology developed by Aquamarine Power. The experiments were carried out in the wave tank at Queens University Belfast. The algal growth on the device has been emulated with plastic stripes attached on the surface of the device. Several configurations with various placements and stripe dimensions were tested, in sea states typical to the targeted deployment sites. Our experiments were designed as a worst-case scenario and provide first insights into the potential effects of biofouling on the performance of a WEC. The experiments indicate that the effects of biofouling could be significant and suggest the need for further investigation.

scholarly journals Modelling with Volna-OP2—Towards Tsunami Threat Reduction for the Irish Coastline

Geosciences ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 226 ◽  
Author(s):  
Daniel Giles ◽  
Brian McConnell ◽  
Frédéric Dias
Keyword(s):  
Real Time ◽  
Initial Conditions ◽  
Multiple Sources ◽  
Case Scenario ◽  
Worst Case ◽  
Arrival Times ◽  
Tsunami Waves ◽  
North East ◽  
The North ◽  
Run Up

Tsunamis are infrequent events that have the potential to be extremely destructive. The last major tsunami to effect the Irish coastline was the Lisbon 1755 event. That event acts as a candidate worst case scenario for hazard assessment and the impacts on the Irish Coastline are presented here. As there is no general consensus on the 1755 earthquake source, multiple sources highlighted in the literature are investigated. These sources are used to generate the initial conditions and the resultant tsunami waves are simulated with the massively parallelised Volna-OP2 finite volume tsunami code. The hazard associated with the event is captured on three gradated levels. A reduced faster than real time tsunami ensemble is produced for the North-East Atlantic on a regional level in 93 s using two Nvidia V100 GPUs. By identifying the most vulnerable sections of the Irish coastline from this regional forecast, some locally refined simulations are further carried out in a faster than real time setting. As arrival times on the coastline can be on the O (mins), these faster than real time reduced ensembles are of great benefit for tsunami warning. Volna-OP2’s capabilities in this respect are clearly demonstrated here. Finally, high resolution inundation simulations, which build upon the ensemble results, are carried out. To date this study provides the best estimate of assessing the hazard associated with a Lisbon-type tsunami event for the Irish coastline. The results of the inundation mapping highlight that along the vulnerable sections of coastline, inundation is constrained to low-lying areas with maximum run-up heights of 3.4 m being found.

scholarly journals Tsunami hazard potential for the equatorial southwestern Pacific atolls of Tokelau from scenario-based simulations

2016 ◽  
Vol 16 (5) ◽  
pp. 1239-1257 ◽  
Author(s):  
Alan R. Orpin ◽  
Graham J. Rickard ◽  
Peter K. Gerring ◽  
Geoffroy Lamarche
Keyword(s):  
Pacific Islands ◽  
Tsunami Hazard ◽  
Earthquake Source ◽  
Tsunami Source ◽  
Case Scenario ◽  
Worst Case ◽  
Basic Field ◽  
Earthquake Sources ◽  
Flood Depth ◽  
The North

Abstract. Devastating tsunami over the last decade have significantly heightened awareness of the potential consequences and vulnerability of low-lying Pacific islands and coastal regions. Our appraisal of the potential tsunami hazard for the atolls of the Tokelau Islands is based on a tsunami source–propagation–inundation model using Gerris Flow Solver, adapted from the companion study by Lamarche et al. (2015) for the islands of Wallis and Futuna. We assess whether there is potential for tsunami flooding on any of the village islets from a selection of 14 earthquake-source experiments. These earthquake sources are primarily based on the largest Pacific earthquakes of Mw  ≥  8.1 since 1950 and other large credible sources of tsunami that may impact Tokelau. Earthquake-source location and moment magnitude are related to tsunami-wave amplitudes and tsunami flood depths simulated for each of the three atolls of Tokelau. This approach yields instructive results for a community advisory but is not intended to be fully deterministic. Rather, the underlying aim is to identify credible sources that present the greatest potential to trigger an emergency response. Results from our modelling show that wave fields are channelled by the bathymetry of the Pacific basin in such a way that the swathes of the highest waves sweep immediately northeast of the Tokelau Islands. Our limited simulations suggest that trans-Pacific tsunami from distant earthquake sources to the north of Tokelau pose the most significant inundation threat. In particular, our assumed worst-case scenario for the Kuril Trench generated maximum modelled-wave amplitudes in excess of 1 m, which may last a few hours and include several wave trains. Other sources can impact specific sectors of the atolls, particularly distant earthquakes from Chile and Peru, and regional earthquake sources to the south. Flooding is dependent on the wave orientation and direct alignment to the incoming tsunami. Our "worst-case" tsunami simulations of the Tokelau Islands suggest that dry areas remain around the villages, which are typically built on a high islet. Consistent with the oral history of little or no perceived tsunami threat, simulations from the recent Tohoku and Chile earthquake sources suggest only limited flooding around low-lying islets of the atoll. Where potential tsunami flooding is inferred from the modelling, recommended minimum evacuation heights above local sea level are compiled, with particular attention paid to variations in tsunami flood depth around the atolls, subdivided into directional quadrants around each atoll. However, complex wave behaviours around the atolls, islets, tidal channels and within the lagoons are also observed in our simulations. Wave amplitudes within the lagoons may exceed 50 cm, increasing any inundation and potential hazards on the inner shoreline of the atolls, which in turn may influence evacuation strategies. Our study shows that indicative simulation studies can be achieved even with only basic field information. In part, this is due to the spatially and vertically limited topography of the atoll, short reef flat and steep seaward bathymetry, and the simple depth profile of the lagoon bathymetry.

scholarly journals Identification of NLOS and Multi-Path Conditions in UWB Localization Using Machine Learning Methods

2020 ◽  
Author(s):  
Cung Lian Sang ◽  
Bastian Steinhagen ◽  
Jonas Dominik Homburg ◽  
Michael Adams ◽  
Marc Hesse ◽  
...  
Keyword(s):  
Machine Learning ◽  
Indoor Localization ◽  
Measurement Data ◽  
Ultra Wideband ◽  
Line Of Sight ◽  
Support Vector ◽  
Case Scenario ◽  
Worst Case ◽  
Data Set ◽  
Worst Case Scenario

In Ultra-wideband (UWB)-based wireless ranging or distance measurement, differentiation between line-of-sight~(LOS), non-line-of-sight~(NLOS), and multi-path (MP) conditions are important for precise indoor localization. This is because the accuracy of the reported measured distance in UWB ranging systems is directly affected by the measurement conditions (LOS, NLOS or MP). However, the major contributions in literature only address the binary classification between LOS and NLOS in UWB ranging systems. The MP condition is usually ignored. In fact, the MP condition also has a significant impact on the ranging errors of the UWB compared to the direct LOS measurement results. Though, the magnitudes of the error contained in MP conditions are generally lower than completely blocked NLOS scenarios. This paper addresses machine learning techniques for identification of the mentioned three classes (LOS, NLOS, and MP) in the UWB indoor localization system using an experimental data-set. The data-set was collected in different conditions at different scenarios in indoor environments. Using the collected real measurement data, we compare three machine learning (ML) classifiers, i.e., support vector machine (SVM), random forest (RF) based on an ensemble learning method, and multilayer perceptron (MLP) based on a deep artificial neural network, in terms of their performance. The results show that applying ML methods in UWB ranging systems are effective in identification of the above-mentioned three classes. In specific, the overall accuracy reaches up to 91.9% in the best-case scenario and 72.9% in the worst-case scenario. Regarding the F1-score, it is 0.92 in the best-case and 0.69 in the worst-case scenario. For reproducible results and further exploration, we (will) provide the publicly accessible experimental research data discussed in this paper at PUB - Publications at Bielefeld University. The evaluations of the three classifiers are conducted using the open-source python machine learning library scikit-learn.

Removal of Magnetic Contamination in Drilling Fluids: Effect on Directional Drilling

2020 ◽  
Author(s):  
Arild Saasen ◽  
Benny Poedjono ◽  
Geir Olav Ånesbug ◽  
Nicholas Zachman
Keyword(s):  
Magnetic Particles ◽  
Barents Sea ◽  
Drilling Fluid ◽  
Drilling Fluids ◽  
Directional Drilling ◽  
The North ◽  
Uncertainty Calculation ◽  
The North Sea ◽  
Drilling Rigs ◽  
Sea Area

Abstract Magnetic debris in a drilling fluid have a significant influence on the ability of the drilling fluid to maintain its function. Down hole logging can suffer from poor signal to noise ratios. Directional drilling in areas close to the magnetic North Pole, such as in the Barents Sea, Northern Canada or Russia can suffer because of magnetic contamination in the drilling fluid. Magnetic particles in the drilling fluid introduce additional errors to the magnetic surveying compared to those normally included in the ellipsoid of uncertainty calculation. On many offshore drilling rigs, there is mounted ditch magnets to remove metallic swarf from the drilling fluid. These magnets normally only remove the coarser swarf. In this project, we use a combination of strong magnets and flow directors to significantly improve the performance of the ditch magnets. This combination, together with proper routines for cleaning the ditch magnets, significantly helps to clean the drilling fluid. Through the combined use of flow directors and ditch magnets, it was possible to extract more than five times as much magnetic contamination from the drilling fluid as normal compared with other proper ditch magnet systems. This is verified by comparing the ditch magnet efficiencies from two drilling rigs drilling ERD wells in the North Sea area. In the paper, it is discussed how the accuracy of directional drilling and well position effected by various interferences can be improved by the use of a drilling fluid with minimal effect to the MWD measurement.

scholarly journals A Troubled North Caucasus: What`s Ahead?

2012 ◽  
pp. 65-74
Author(s):  
V. V. Degoev
Keyword(s):  
Ad Hoc ◽  
Social Conflicts ◽  
North Caucasus ◽  
Case Scenario ◽  
Worst Case ◽  
Worst Case Scenario ◽  
The North

In the article the author revisits the neverending post-soviet discourse on the burning issue – the North Caucasus threats to Russia`s statehood. He ponders over the question whether the region is the source or just the exotic extension of the country`s troubles. Whatever the answer is prof. V. Degoev thinks it vital for the Kremlin to try its best to escape the worst-case scenario on the turbulent multiethnic periphery. This end, as he concludes, has to be achieved by carefully calculated combinations of systemic approaches and the ad hoc reaction to social conflicts fraught with the nation-wide consequences.

Reducing Probabilistic Weather Forecasts to the Worst Case Scenario: Anchoring Effects

2008 ◽  
Author(s):  
Sonia Savelli ◽  
Susan Joslyn ◽  
Limor Nadav-Greenberg ◽  
Queena Chen
Keyword(s):  
Case Scenario ◽  
Worst Case ◽  
Weather Forecasts ◽  
Worst Case Scenario ◽  
Anchoring Effects

EXPEDITION TO MALI, 2020

2020 ◽  
pp. 12-28
Author(s):  
D. V. Vaniukova ◽  
◽  
P. A. Kutsenkov ◽  
Keyword(s):  
Mass Murder ◽  
The State ◽  
Case Scenario ◽  
Worst Case ◽  
Traditional Art ◽  
Peter The Great ◽  
State Museum ◽  
Bobo Dioulasso ◽  
Oriental Studies ◽  
The Village

The research expedition of the Institute of Oriental studies of the Russian Academy of Sciences has been working in Mali since 2015. Since 2017, it has been attended by employees of the State Museum of the East. The task of the expedition is to study the transformation of traditional Dogon culture in the context of globalization, as well as to collect ethnographic information (life, customs, features of the traditional social and political structure); to collect oral historical legends; to study the history, existence, and transformation of artistic tradition in the villages of the Dogon Country in modern conditions; collecting items of Ethnography and art to add to the collection of the African collection of the. Peter the Great Museum (Kunstkamera, Saint Petersburg) and the State Museum of Oriental Arts (Moscow). The plan of the expedition in January 2020 included additional items, namely, the study of the functioning of the antique market in Mali (the “path” of things from villages to cities, which is important for attributing works of traditional art). The geography of our research was significantly expanded to the regions of Sikasso and Koulikoro in Mali, as well as to the city of Bobo-Dioulasso and its surroundings in Burkina Faso, which is related to the study of migrations to the Bandiagara Highlands. In addition, the plan of the expedition included organization of a photo exhibition in the Museum of the village of Endé and some educational projects. Unfortunately, after the mass murder in March 2019 in the village of Ogossogou-Pel, where more than one hundred and seventy people were killed, events in the Dogon Country began to develop in the worst-case scenario: The incessant provocations after that revived the old feud between the Pel (Fulbe) pastoralists and the Dogon farmers. So far, this hostility and mutual distrust has not yet developed into a full-scale ethnic conflict, but, unfortunately, such a development now seems quite likely.

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