A Comprehensive Evaluation of Well Completion and Production Performance in Bakken Shale Using Data-Driven Approaches

2016 ◽  
Author(s):  
Shuhua Wang ◽  
Shengnan Chen
Keyword(s):  
Comprehensive Evaluation ◽  
Production Performance ◽  
Data Driven ◽  
Well Completion ◽  
Using Data ◽  
Bakken Shale

Data-Driven Well Pad Development Performance Review: Focus on the Role of Liner Design on Well Performance

2021 ◽  
Author(s):  
Hossein Izadi ◽  
Morteza Roostaei ◽  
Mahdi Mahmoudi ◽  
Seyed Abolhassan Hosseini ◽  
Mohammad Soroush ◽  
...  
Keyword(s):  
Oil Production ◽  
Relative Performance ◽  
Data Driven ◽  
Thickness Variation ◽  
Well Performance ◽  
Drainage Volume ◽  
Well Completion ◽  
Flow Control Devices ◽  
Using Data

Abstract Steam Assisted Gravity Drainage (SAGD) is the dominant in-situ method for oil production in Western Canada. The current study analyzed the relative performance of various well-completion practices using data from 4,000 well pairs that were drilled over a decade. The data analysis provided a unique opportunity to find best operating practices. The scope of this paper is to review the performance of major thermal projects in Canada and investigating the effect of liner design and Flow Control Devices (FCDs) on well pair performance and development. Cumulative oil production and cumulative steam oil ratio (cSOR) were used as the key metrics in comparing the well performance in a SAGD operation. However, to compare different pads and different projects, it was critical to normalize the data with geological variation, well length, well spacing, and with consideration to the well failure rate, remedial completion and re-drills. In this paper we review seven thermal projects of four key operators with almost 3,500 wells and 1,200 well pairs in operation as early as 1996. All geoscience, and production/injection data have been extracted from public databases and utilized to develop a data-driven model. The reservoir thickness variation for each well was determined using available geoscience data, and through the development of a geological model based on the available core data and well logs. The model was used to define the drainage volume for each well pair, which in turn was used to assign a geological ranking to the well. The cumulative oil production and cSOR were then normalized with the geological ranking and the size of the net drainage volume. The number of well pairs in each pad and the cumulative pad production were normalized against the number of days in production and their relative decline, which allowed for comparison between pads within the same project, as well as pads from other projects. The cumulative production of the active pads in each project was used to compare the relative performance of different projects. Also, we separated the projects and wells based on their use of FCDs in the producer and injector to compare the relative performance of each technology in the field. This paper is the initial phase of the study on the role of completion design on relative well and well pad performance. The results will help completion and production engineers to better understand the well pair and pad relative performance and how to normalize the oil production data against geological variation to compare performance.

Maintenance Task Prioritization Using Data Driven Bottleneck Detection and Maintenance Opportunity Windows

2007 ◽  
Author(s):  
Lin Li ◽  
Dragan Djurdjanovic ◽  
Jun Ni
Keyword(s):  
System Reliability ◽  
Manufacturing Systems ◽  
Task Assignment ◽  
Production Performance ◽  
Data Driven ◽  
Bottleneck Detection ◽  
Systems Maintenance ◽  
Task Prioritization ◽  
Using Data ◽  
Production Losses

Maintenance operations have a direct influence on production performance in manufacturing systems. Maintenance task prioritization is crucial and important, especially when availability of maintenance resources is limited. The decision on task assignment is often made through heuristic methods or experience, which could cause more downtime and the production losses. In this paper, a new maintenance task prioritization policy based on data driven bottleneck detection and reliability-based maintenance opportunity window calculation is introduced. An experiment in simulation of a real production line shows the proposed policy is able to improve the system reliability, increase the throughput and minimize the total cost of system operation.

Development of a Pediatric Early Warning System Using Data-Driven Vital Signs

PEDIATRICS ◽  
2016 ◽  
Vol 137 (Supplement 3) ◽  
pp. 256A-256A
Author(s):  
Catherine Ross ◽  
Iliana Harrysson ◽  
Lynda Knight ◽  
Veena Goel ◽  
Sarah Poole ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Vital Signs ◽  
Warning System ◽  
Data Driven ◽  
Using Data

Enhanced Resilient State Estimation Using Data-Driven Auxiliary Models

2020 ◽  
Vol 16 (1) ◽  
pp. 639-647 ◽  
Author(s):  
Olugbenga Moses Anubi ◽  
Charalambos Konstantinou
Keyword(s):  
State Estimation ◽  
Data Driven ◽  
Using Data

scholarly journals Integration of various scales for measurement of insomnia

2021 ◽  
pp. 263208432110100
Author(s):  
Satyendra Nath Chakrabartty
Keyword(s):  
Test Scores ◽  
Data Driven ◽  
Weighted Sum ◽  
Future Studies ◽  
Normal Probability ◽  
Equivalent Test ◽  
Item Scores ◽  
Using Data ◽  
Set Up ◽  
Different Levels

Background Scales for evaluating insomnia differ in number of items, response format, and result in different scores distributions and score ranges and may not facilitate meaningful comparisons. Objectives Transform ordinal item-scores of three scales of insomnia to continuous, equidistant, monotonic, normally distributed scores, avoiding limitations of summative scoring of Likert scales. Methods Equidistant item-scores by weighted sum using data-driven weights to different levels of different items, considering cell frequencies of Item-Levels matrix, followed by normalization and conversion to [1, 10]. Equivalent test-scores (as sum of transformed item- scores) for a pair of scales were found by Normal Probability curves. Empirical illustration given. Results Transformed test-scores are continuous, monotonic and followed Normal distribution with no outliers and tied scores. Such test-scores facilitate ranking, better classification and meaningful comparison of scales of different lengths and formats and finding equivalent score combinations of two scales. For a given value of transformed test-score of a scale, easy alternate method avoiding integration proposed to find equivalent scores of another scales. Equivalent scores of scales help to relate various cut-off scores of different scales and uniformity in interpretations. Integration of various scales of insomnia is achieved by finding one-to-one correspondence among the equivalent score of various scales with correlation over 0.99 Conclusion Resultant test-scores facilitated undertaking analysis in parametric set up. Considering the theoretical advantages including meaningfulness of operations, better comparison, use of such method of transforming scores of Likert items/test is recommended test and items, Future studies were suggested.

Prediction of industrial debutanizer column compositions using data-driven ANFIS- and ANN-based approaches

2021 ◽  
Author(s):  
Syeda Anmol Fatima ◽  
Nasser Ramli ◽  
Syed Ali Ammar Taqvi ◽  
Haslinda Zabiri
Keyword(s):  
Data Driven ◽  
Using Data
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