A wave prediction system for real-time sea state forecasting

1983 ◽  
Vol 109 (460) ◽  
pp. 393-416 ◽  
Author(s):  
B. Golding
Author(s):  
Yusuke IGARASHI ◽  
Akira IMAI ◽  
Atsushi ITO ◽  
Hiroyuki KAITSU

2009 ◽  
Vol 24 (3) ◽  
pp. 812-828 ◽  
Author(s):  
Young-Mi Min ◽  
Vladimir N. Kryjov ◽  
Chung-Kyu Park

Abstract A probabilistic multimodel ensemble prediction system (PMME) has been developed to provide operational seasonal forecasts at the Asia–Pacific Economic Cooperation (APEC) Climate Center (APCC). This system is based on an uncalibrated multimodel ensemble, with model weights inversely proportional to the errors in forecast probability associated with the model sampling errors, and a parametric Gaussian fitting method for the estimate of tercile-based categorical probabilities. It is shown that the suggested method is the most appropriate for use in an operational global prediction system that combines a large number of models, with individual model ensembles essentially differing in size and model weights in the forecast and hindcast datasets being inconsistent. Justification for the use of a Gaussian approximation of the precipitation probability distribution function for global forecasts is also provided. PMME retrospective and real-time forecasts are assessed. For above normal and below normal categories, temperature forecasts outperform climatology for a large part of the globe. Precipitation forecasts are definitely more skillful than random guessing for the extratropics and climatological forecasts for the tropics. The skill of real-time forecasts lies within the range of the interannual variability of the historical forecasts.


2021 ◽  
Author(s):  
Klemens Katterbauer ◽  
Waleed Dokhon ◽  
Fahmi Aulia ◽  
Mohanad Fahmi

Abstract Corrosion in pipes is a major challenge for the oil and gas industry as the metal loss of the pipe, as well as solid buildup in the pipe, may lead to an impediment of flow assurance or may lead to hindering well performance. Therefore, managing well integrity by stringent monitoring and predicting corrosion of the well is quintessential for maximizing the productive life of the wells and minimizing the risk of well control issues, which subsequently minimizing cost related to corrosion log allocation and workovers. We present a novel supervised learning method for a corrosion monitoring and prediction system in real time. The system analyzes in real time various parameters of major causes of corrosion such as salt water, hydrogen sulfide, CO2, well age, fluid rate, metal losses, and other parameters. The data are preprocessed with a filter to remove outliers and inconsistencies in the data. The filter cross-correlates the various parameters to determine the input weights for the deep learning classification techniques. The wells are classified in terms of their need for a workover, then by the framework based on the data, utilizing a two-dimensional segmentation approach for the severity as well as risk for each well. The framework was trialed on a probabilistically determined large dataset of a group of wells with an assumed metal loss. The framework was first trained on the training dataset, and then subsequently evaluated on a different test well set. The training results were robust with a strong ability to estimate metal losses and corrosion classification. Segmentation on the test wells outlined strong segmentation capabilities, while facing challenges in the segmentation when the quantified risk for a well is medium. The novel framework presents a data-driven approach to the fast and efficient characterization of wells as potential candidates for corrosion logs and workover. The framework can be easily expanded with new well data for improving classification.


1981 ◽  
Vol 107 (2) ◽  
pp. 419-435
Author(s):  
Floyd A. Huff ◽  
Stanley A. Changnon ◽  
John L. Vogel
Keyword(s):  

2015 ◽  
Vol 20 (2) ◽  
pp. 192-204 ◽  
Author(s):  
Eleni I. Vlahogianni ◽  
Konstantinos Kepaptsoglou ◽  
Vassileios Tsetsos ◽  
Matthew G. Karlaftis

2021 ◽  
Author(s):  
Stefan Dinger ◽  
Andrei Casali ◽  
Frank Lind ◽  
Azwan Hadi Keong ◽  
Johnny Bårdsen ◽  
...  

Abstract Coiled tubing (CT) operations in the Norwegian continental shelf (NCS) often require a long and large-outside-diameter pipe due to big diameter completions, deep wells, and the need for high annular velocity during fluid circulation. However, getting the CT string onboard becomes a challenge when the crane lifting limit is 35 t, and using a standalone crane barge increases the cost of the operation. The alternative is spooling the CT from a vessel to the platform. Boat spooling is done by placing the CT string on a floating vessel with dynamic positioning while the standard CT injector head is secured at the edge of the platform to pull the pipe from the vessel to an empty CT reel on the platform. The boat is equipped with a CT guide; special tension clamps; and an emergency disconnect system, which consists of a standard CT shear-seal blowout preventer. The technique requires careful study of the platform structure for placement of the injector head support frame, metocean data of the field, and equipment placement on the vessel and platform. The boat spooling operation of a 7,700-m long, 58.7-t, 2.375-in.-outside-diameter CT string was successfully executed for a platform at 70-m height from mean sea level. The total operating time from hooking up the vessel to successfully spooling the string only took 12 hours. Historically for the region, the method has been attempted in sea state of up to 4-m wave height and 16 knots maximum wind speed. For this operation, the spooling was carried out during an average sea state of 2-m wave height and 15-knot wind speed. The continuous CT string allows a telemetry cable to be installed inside the pipe after the CT is spooled onto the platform reel, enabling real-time downhole measurements during the intervention. Such installation is not possible or presents high risk if the CT string is taken onboard by splicing two sections of pipe together with a spoolable connector or butt welding. From a cost perspective, the boat-spooling operation had up to 80% direct cost saving for the operator when compared to other methods of lifting a single CT string onboard, such as using a motion-compensated barge crane. The planning for the boat spooling included several essential contingency plans. Performing a CT boat spooling operation in a complex environment is possible and opens new opportunities to use longer and heavier CT strings, with lower mobilization costs. Such strings enable more advanced and efficient interventions, with the option of using real-time CT downhole measurements during the execution of a wide range of production startup work. This, in turn, is critical to support the drilling of more extended reach wells, which allow access to untapped reservoirs.


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