New Well-Testing Methods for Rod-Pumping Oil Wells - Case Studies

2002 ◽  
Vol 17 (04) ◽  
pp. 204-211 ◽  
Author(s):  
John Guoynes ◽  
Mehdi Azari ◽  
Robert Gillstrom ◽  
Bret Friend ◽  
Mike Fairbanks
2000 ◽  
Author(s):  
John C. Guoynes ◽  
Mehdi Azari ◽  
R. Gillstrom ◽  
B.L. Friend ◽  
M.D. Fairbanks

2021 ◽  
Author(s):  
Ildar Radikovich Abdrakhmanov ◽  
Evgenii Alekseevich Kanin ◽  
Sergei Andreevich Boronin ◽  
Evgeny Vladimirovich Burnaev ◽  
Andrei Aleksandrovich Osiptsov

Abstract We propose a novel approach to data-driven modeling of a transient production of oil wells. We apply the transformer-based neural networks trained on the multivariate time series composed of various parameters of oil wells measured during their exploitation. By tuning the machine learning models for a single well (ignoring the effect of neighboring wells) on the open-source field datasets, we demonstrate that transformer outperforms recurrent neural networks with LSTM/GRU cells in the forecasting of the bottomhole pressure dynamics. We apply the transfer learning procedure to the transformer-based surrogate model, which includes the initial training on the dataset from a certain well and additional tuning of the model's weights on the dataset from a target well. Transfer learning approach helps to improve the prediction capability of the model. Next, we generalize the single-well model based on the transformer architecture for multiple wells to simulate complex transient oilfield-level patterns. In other words, we create the global model which deals with the dataset, comprised of the production history from multiple wells, and allows for capturing the well interference resulting in more accurate prediction of the bottomhole pressure or flow rate evolutions for each well under consideration. The developed instruments for a single-well and oilfield-scale modelling can be used to optimize the production process by selecting the operating regime and submersible equipment to increase the hydrocarbon recovery. In addition, the models can be helpful to perform well-testing avoiding costly shut-in operations.


2011 ◽  
Author(s):  
Wiriya Kiatpadungkul ◽  
Saifon Daungkaew ◽  
Suchart Chokthanyawat ◽  
Soontorn Promkhot ◽  
Cosan Ayan ◽  
...  

2019 ◽  
Vol 3 (2) ◽  
pp. 41-51
Author(s):  
Maha Hamoudi ◽  
Akram Humoodi ◽  
Bashdar Mohammed

Production logging tools (PLTs) in oil and gas industries are used for obtaining fluid types and measuring fluid rates in the borehole for both production and injection wells and to better understand the well productivity or the well injectivity of the interest zones. Additionally, it can be used to detect well problems, such as early water or gas breakthrough, channeling behind casing or tubing, and water or gas coning. The Khurmala field is a big oil field in the Kurdistan region of Iraq. PLTs have been acquired in many of the Khurmala oil wells, and the log records took into consideration the production technique decisions. In this study, results of the PLT log will be discussed in one of the Khurmala oil wells. Owing to the long history of production of oil or gas wells, many problems have been seen, such as coning either water or gas, formation damage, casing corrosion, and well obstruct. This research will evaluate the production profile across the slotted liner interval of (W1) well in the Khurmala oil field in the Iraq-Kurdistan region and detect possible water entry points, verify the distribution and nature of fluids, and estimate fluid segregation after the shut-in period. This was done by applying PLTs and interpreting the data by using Emeraude software. The performance of each choke size was studied and assessed. It was found that a choke size of 48/64̎gives the best favorable production gas, oil ratio, and profile. Results from the PL survey showed that no water entry was detected across the logged interval. All the water was coming from below a depth of 990 m; most of the hydrocarbons were coming from the slotted interval across 981.8-982.9 m, and the flowing pressure across the logged interval using maximum choke was less than the saturation pressure.


2012 ◽  
Vol 4 (1) ◽  
Author(s):  
Francesco Mazzini ◽  
Steven Dubowsky

This research investigates using a manipulator to tactilely explore objects and environments when significant backlash affects its joint’s positions. A typical application is the exploration of rough environments, such as oil wells, where the harsh conditions dictate the use of tactile exploration. These conditions can result in large, unknown, and variable backlash in the manipulator’s transmissions, which strongly affects the measurement precision. Here, a method is developed to simultaneously map the unknown surface and identify the joint backlash. The robot probes the surface and uses its encoder readings to construct a partial map of the environment as a combination of geometric primitives. While the surface is built, the same data are also used to estimate backlash in the joints and to correct the surface measurements for backlash error. The effectiveness of the approach is demonstrated in simulation case studies and laboratory experiments.


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