Integrating Various Sources of Indicators and Water Measurements Data of Different Degree of Uncertainty: Understanding Aquifer Encroachment and Resulted Water Breakthrough to Gas Producers

2021 ◽  
Author(s):  
Michael Nashaat ◽  
Kassem Ghorayeb ◽  
Murat Zhiyenkulov ◽  
Abdur Rahman Shah ◽  
Oleh Lukin ◽  
...  
Keyword(s):  
Water Analysis ◽  
Water Movement ◽  
Analysis Data ◽  
High Water ◽  
Gas Field ◽  
Water Breakthrough ◽  
Surface Water Salinity ◽  
Data Points ◽  
Water Behavior ◽  
Different Sources

Abstract Opishnyanske Field is a mature Ukrainian gas field that began producing in 1972 from three formations: Visean, Serpukhovian, and Bashkirian. A reservoir simulation study was implemented to understand the movement of the water in the reservoir and to maximize the field recovery. Some wells showed high water production at their late life and this was the key question that we wanted to understand. If this was a water breakthrough, which means that the aquifer water swept the gas in the reservoir and reached these wells, then there is little potential left in this field. If this was not a water breakthrough, there could still exist some unswept areas to be produced. The second key question was to understand the aquifer strength and direction to be integrated into the simulation model. The field has different sources of data that could be used to understand the water movement in the reservoir, which are: Observed production data Water analysis reports (surface water salinity and density measurements) Production logging data Pressure data and geological maps to understand the communication between the wells Although different sources of data are available, each one has a level of inaccuracy, which was the key challenge. The field also has some other challenges, such as: Commingled production Contradiction between the observed water/gas ratio (WGR) and water analysis data Limited water analysis data points in some wells Issues with backallocation of the observed data. Integrating all the available data had a significant effect on understating the water behavior. Data analysis and integration resulted in excluding all the data anomalies and reaching a good understating regarding: The wells that are showing a water breakthrough Aquifer strength and direction

scholarly journals Application of the CL-systems technology for water injection wells at an oil and gas field

2021 ◽  
Vol 19 (3) ◽  
pp. 848-853
Author(s):  
Liliya Saychenko ◽  
Radharkrishnan Karantharath
Keyword(s):  
Oil And Gas ◽  
Water Injection ◽  
Oil And Gas Industry ◽  
Field Studies ◽  
High Water ◽  
Injection Wells ◽  
Gas Field ◽  
Water Breakthrough ◽  
Oil And Gas Field ◽  
High Water Cut

To date, the development of the oil and gas industry can be characterized by a decline in the efficiency of the development of hydrocarbon deposits. High water cut-off is often caused by water breaking through a highly permeable reservoir interval, which often leads to the shutdown of wells due to the unprofitability of their further operation. In this paper, the application of straightening the profile log technology for injection wells of the Muravlenkovsky oil and gas field is justified. In the course of this work, the results of field studies are systematized. The reasons for water breakthrough were determined, and the main ways of filtration of the injected water were identified using tracer surveys. The use of CL-systems technology based on polyacrylamide and chromium acetate is recommended. The forecast of the estimated additional oil produced was made.

Array Production Survey Accurately Pinpoints Water Shut-Off Location and Strengthen the Understanding on Remaining Potential of a Giant Carbonate Gas Field, Offshore East Malaysia

2021 ◽  
Author(s):  
Noor Afiqah Ahmad ◽  
Zhin Houng Chieng ◽  
Anie Jelie ◽  
Hazrina Abdul Rahman ◽  
M Farid M Amin ◽  
...  
Keyword(s):  
High Water ◽  
Peninsular Malaysia ◽  
Initial Assessment ◽  
Flow Profile ◽  
Water Production ◽  
Gas Field ◽  
Horizontal Section ◽  
Water Breakthrough ◽  
Multiple Array ◽  
Array Production

Abstract Over the years, Multiple Array Production Suite (MAPS) has been run several times in Offshore Peninsular Malaysia but never in Offshore East of Malaysia. Field A is located 260km North-North West of Bintulu, Offshore Sarawak and was discovered in 1992 with first gas produced in 2004. One of the many challenges currently faced in managing the field is the prediction and handling of water breakthrough at the existing producers. Based on historical data, water breakthrough from carbonate Zone T begin around 2010 which then followed by series of Water Shut-Off (WSO) campaign. To strengthen the understanding, evaluate the remaining potential and to optimize near term well and reservoir management of the field, an integrated remedial approach is essential. Well-AA was identified for mechanical WSO in an effort to remediate high water production and improve well productivity. The target well was chosen as the well unable to sustain production after a rapid tubing pressure drop due to the highest water production in the field. Moreover, its production had to be capped due to the water production constraints at the receiving hub. Production Logging (PL) was planned across the carbonate sections to accurately identify the appropriate zones for WSO operations. The long horizontal section and high water production typically create a stratified flow regime that forces a smaller volume of hydrocarbon to flow on the high side of the well, hence the conventional PL technology would have been unable to deliver accurate and insightful results. As such, the MAPS technology was run for an initial assessment to identify the water producing zones. MAPS was deployed using wireline tractor and was combined with the Noise Tool (NTO) to provide a comprehensive 3D image of the multi-phase flow profile across the entire wellbore and to investigate the integrity of annular swell packers located in between the carbonate sections. This paper illustrates the best practices involved in the successful downhole Production Logging with a Multiple Array Production Suite and Digital Noise Tool (PL-MAPS-NTO) toolstring, which served as the key input in determining the WSO treatment depth and strategy in Well-AA, that may lead to a potential gain of 10.8MMscf/d.

scholarly journals APPLICATION OF THE CL-SYSTEMS TECHNOLOGY FOR WATER INJECTION WELLS AT AN OIL AND GAS FIELD

2021 ◽  
Vol 19 (3) ◽  
pp. 847-852
Author(s):  
Liliya Saychenko ◽  
Radharkrishnan Karantharath
Keyword(s):  
Oil And Gas ◽  
Water Injection ◽  
Oil And Gas Industry ◽  
Field Studies ◽  
High Water ◽  
Injection Wells ◽  
Gas Field ◽  
Water Breakthrough ◽  
Oil And Gas Field ◽  
High Water Cut

To date, the development of the oil and gas industry can be characterized by a decline in the efficiency of the development of hydrocarbon deposits. High water cut-off is often caused by water breaking through a highly permeable reservoir interval, which often leads to the shutdown of wells due to the unprofitability of their further operation. In this paper, the application of straightening the profile log technology for injection wells of the Muravlenkovsky oil and gas field is justified. In the course of this work, the results of field studies are systematized. The reasons for water breakthrough were determined, and the main ways of filtration of the injected water were identified using tracer surveys. The use of CL-systems technology based on polyacrylamide and chromium acetate is recommended. The forecast of the estimated additional oil produced was made.

Innovations of Gas Lift in Prolific, Long-perforations, and Multilayered Wells, Case Study in Sudan

2016 ◽  
Author(s):  
Xueqing Tang ◽  
Lirong Dou ◽  
Ruifeng Wang ◽  
Jie Wang ◽  
Shengbao Wang ◽  
...  
Keyword(s):  
High Water ◽  
Water Breakthrough ◽  
Start Up ◽  
Production Wells ◽  
Decline Curves ◽  
High Water Cut ◽  
Water Cut ◽  
Gas Lift

ABSTRACT Jake field, discovered in July, 2006, contains 10 oil-producing and 12 condensate gas-producing zones. The wells have high flow capacities, producing from long-perforation interval of 3,911 ft (from 4,531 to 8,442 ft). Production mechanisms include gas injection in downdip wells and traditional gas lift in updip, zonal production wells since the start-up of field in July, 2010. Following pressure depletion of oil and condensate-gas zones and water breakthrough, traditional gas-lift wells became inefficient and dead. Based on nodal analysis of entire pay zones, successful innovations in gas lift have been made since March, 2013. This paper highlights them in the following aspects: Extend end of tubing to the bottom of perforations for commingled production of oil and condensate gas zones, in order to utilize condensate gas producing from the lower zones for in-situ gas lift.Produce well stream from the casing annulus while injecting natural gas into the tubing.High-pressure nitrogen generated in-situ was used to kick off the dead wells, instead of installation of gas lift valves for unloading. After unloading process, the gas from compressors was injected down the tubing and back up the casing annulus.For previous high water-cut producers, prior to continuous gas lift, approximately 3.6 MMcf of nitrogen can be injected and soaked a couple of days for anti-water-coning.Two additional 10-in. flow lines were constructed to minimize the back pressure of surface facilities on wellhead. As a consequence, innovative gas-lift brought dead wells back on production, yielding average sustained liquid rate of 7,500 bbl/d per well. Also, the production decline curves flattened out than before.

Categorization of Data Clustering Techniques

2008 ◽  
pp. 568-577
Author(s):  
Baoying Wang ◽  
Imad Rahal ◽  
Richard Leipold
Keyword(s):  
Unsupervised Learning ◽  
Supervised Learning ◽  
Data Clustering ◽  
Analysis Data ◽  
Discovery Process ◽  
Data Set ◽  
Market Basket ◽  
Clustering Techniques ◽  
Data Points ◽  
Class Labels

Data clustering is a discovery process that partitions a data set into groups (clusters) such that data points within the same group have high similarity while being very dissimilar to points in other groups (Han & Kamber, 2001). The ultimate goal of data clustering is to discover natural groupings in a set of patterns, points, or objects without prior knowledge of any class labels. In fact, in the machine-learning literature, data clustering is typically regarded as a form of unsupervised learning as opposed to supervised learning. In unsupervised learning or clustering, there is no training function as in supervised learning. There are many applications for data clustering including, but not limited to, pattern recognition, data analysis, data compression, image processing, understanding genomic data, and market-basket research.

Anomaly Detection for Inferring Social Structure

2010 ◽  
pp. 1797-1803
Author(s):  
Lisa Friedland
Keyword(s):  
Data Analysis ◽  
Anomaly Detection ◽  
Social Structure ◽  
Small Groups ◽  
Analysis Data ◽  
Data Sets ◽  
Complex Data ◽  
Detection Approach ◽  
Complex Data Sets ◽  
Data Points

In traditional data analysis, data points lie in a Cartesian space, and an analyst asks certain questions: (1) What distribution can I fit to the data? (2) Which points are outliers? (3) Are there distinct clusters or substructure? Today, data mining treats richer and richer types of data. Social networks encode information about people and their communities; relational data sets incorporate multiple types of entities and links; and temporal information describes the dynamics of these systems. With such semantically complex data sets, a greater variety of patterns can be described and views constructed of the data. This article describes a specific social structure that may be present in such data sources and presents a framework for detecting it. The goal is to identify tribes, or small groups of individuals that intentionally coordinate their behavior—individuals with enough in common that they are unlikely to be acting independently. While this task can only be conceived of in a domain of interacting entities, the solution techniques return to the traditional data analysis questions. In order to find hidden structure (3), we use an anomaly detection approach: develop a model to describe the data (1), then identify outliers (2).

Measuring Agreement Among Ranks

2016 ◽  
Vol 7 (1) ◽  
pp. 45-62 ◽  
Author(s):  
Kathleen Campbell Garwood ◽  
Alicia Graziosi Strandberg
Keyword(s):  
Specific Pattern ◽  
Comparison Methods ◽  
The People ◽  
Data Points ◽  
Good For ◽  
The Individual ◽  
Measuring Agreement ◽  
Different Sources ◽  
Kendall’S W

Is it possible to compare rankings from different sources when the individual rankings of the top x elements differ? To investigate this question, 2015 sustainable rankings from 4 sources that have ranked the top globally most sustainable corporations are considered (Corporate Knights, Fortune's World's Most Admired Companies, Newsweek's Green Rankings, and Harris). These rankings are analyzed using common rank comparison methods (Spearman's ?, Kendall's t). Then, they are analyzed to see if the sources ranking the data are doing so at random or if there is a specific pattern of agreement (Kendall's W and a method by Alvo, Cabilio & Feigin (1982)). The insights from these methods as well as possible limitations are considered. A truly sustainable corporation would transcend all definitions and be good for the environment and the people relying on the company. This paper will attempt to identify data points that tend to cluster close together in one or more groups, thereby justifying the feasibility of identifying sets of companies that are truly the “most” sustainable.

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