A Data Analytics Framework for Analyzing the Effect of Frac Hits on Parent Well Production

2021 ◽  
Author(s):  
Yifei Guo ◽  
Pradeepkumar Ashok ◽  
Eric van Oort ◽  
Ross Patterson ◽  
Dandan Zheng ◽  
...  

Abstract Well interference, which is commonly referred to as frac hits, has become a significant factor affecting production in fractured horizontal shale wells with the increase in infill drilling in recent years. Today, there is still no clear understanding on how frac hits affect production. This paper aims to develop a process to automatically identify the different types of frac hits and to determine the effect of stage-to-well distance and frac hit intensity on long-term parent well production. First, child well completions data and parent well pressure data are processed by a frac hit detection algorithm to automatically identify different frac hit intensities and duration within each stage. This algorithm classifies frac hits based on the magnitude of the differential pressure spikes. The frac stage to parent well distance is also calculated. Then, we compare the daily production trend before and after the frac hits to determine the severity of its influence on production. Finally, any evident correlations between the stage-to-well distance, frac hit intensity and production change are identified and investigated. This work utilizes 3 datasets covering 22 horizontal wells in the Bakken Formation and 37 horizontal wells in the Eagle Ford Shale Formation. These sets included well trajectories, child well completions data, parent well pressure data and parent well production data. The frac hit detection algorithm developed can accurately detect frac hits in the available dataset with minimal false alerts. The data analysis results show that frac hit severity (production response) and intensity (pressure response) are not only affected by the distance between parent and child wells, but also affected by the directionality of the wells. Parent wells tend to experience more frac hits from the child frac stages with smaller direction angles and shorter stage-to-parent distances. Formation stress change with time is another factor that affects frac hit intensity. Depleted wells are more susceptible to frac hits even if they are further from the child wells. Also, we observe frac hits in parent wells due to a stimulation of a child well in a different shale formation. This paper presents a novel automated frac hit detection algorithm to quickly identify different types of frac hits. This paper also presents a novel way of carrying out production analysis to determine whether frac hits in a well have positive or negative influence long-term production. Additionally, the paper introduces the concept of the stage-to-well distance as a more accurate metric for analyzing the influence of frac hits on production.

2010 ◽  
Vol 24 (4) ◽  
pp. 249-252 ◽  
Author(s):  
Márk Molnár ◽  
Roland Boha ◽  
Balázs Czigler ◽  
Zsófia Anna Gaál

This review surveys relevant and recent data of the pertinent literature regarding the acute effect of alcohol on various kinds of memory processes with special emphasis on working memory. The characteristics of different types of long-term memory (LTM) and short-term memory (STM) processes are summarized with an attempt to relate these to various structures in the brain. LTM is typically impaired by chronic alcohol intake but according to some data a single dose of ethanol may have long lasting effects if administered at a critically important age. The most commonly seen deleterious acute effect of alcohol to STM appears following large doses of ethanol in conditions of “binge drinking” causing the “blackout” phenomenon. However, with the application of various techniques and well-structured behavioral paradigms it is possible to detect, albeit occasionally, subtle changes of cognitive processes even as a result of a low dose of alcohol. These data may be important for the consideration of legal consequences of low-dose ethanol intake in conditions such as driving, etc.


2020 ◽  
Author(s):  
John J Shaw ◽  
Zhisen Urgolites ◽  
Padraic Monaghan

Visual long-term memory has a large and detailed storage capacity for individual scenes, objects, and actions. However, memory for combinations of actions and scenes is poorer, suggesting difficulty in binding this information together. Sleep can enhance declarative memory of information, but whether sleep can also boost memory for binding information and whether the effect is general across different types of information is not yet known. Experiments 1 to 3 tested effects of sleep on binding actions and scenes, and Experiments 4 and 5 tested binding of objects and scenes. Participants viewed composites and were tested 12-hours later after a delay consisting of sleep (9pm-9am) or wake (9am-9pm), on an alternative forced choice recognition task. For action-scene composites, memory was relatively poor with no significant effect of sleep. For object-scene composites sleep did improve memory. Sleep can promote binding in memory, depending on the type of information to be combined.


2021 ◽  
Vol 22 (3) ◽  
pp. 1411
Author(s):  
Caterina Fede ◽  
Carmelo Pirri ◽  
Chenglei Fan ◽  
Lucia Petrelli ◽  
Diego Guidolin ◽  
...  

The fascia can be defined as a dynamic highly complex connective tissue network composed of different types of cells embedded in the extracellular matrix and nervous fibers: each component plays a specific role in the fascial system changing and responding to stimuli in different ways. This review intends to discuss the various components of the fascia and their specific roles; this will be carried out in the effort to shed light on the mechanisms by which they affect the entire network and all body systems. A clear understanding of fascial anatomy from a microscopic viewpoint can further elucidate its physiological and pathological characteristics and facilitate the identification of appropriate treatment strategies.


Polymers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1598
Author(s):  
Chih-Yu Chung ◽  
Yu-Ju Chen ◽  
Chia-Hui Kang ◽  
Hung-Yun Lin ◽  
Chih-Ching Huang ◽  
...  

Carbon quantum dots (CQDs) are emerging novel nanomaterials with a wide range of applications and high biocompatibility. However, there is a lack of in-depth research on whether CQDs can cause acute or long-term adverse reactions in aquatic organisms. In this study, two different types of CQDs prepared by ammonia citrate and spermidine, namely CQDAC and CQDSpd, were used to evaluate their biocompatibilities. In the fish embryo acute toxicity test (FET), the LD50 of CQDAC and CQDSpd was about 500 and 100 ppm. During the stage of eleutheroembryo, the LD50 decreased to 340 and 55 ppm, respectively. However, both CQDs were quickly eliminated from embryo and eleutheroembryo, indicating a lack of bioaccumulation. Long-term accumulation of CQDs was also performed in this study, and adult zebrafish showed no adverse effects in 12 weeks. In addition, there was no difference in the hatchability and deformity rates of offspring produced by adult zebrafish, regardless of whether they were fed CQDs or not. The results showed that both CQDAC and CQDSpd have low toxicity and bioaccumulation to zebrafish. Moreover, the toxicity assay developed in this study provides a comprehensive platform to assess the impacts of CQDs on aquatic organisms in the future.


Author(s):  
Samuel Humphries ◽  
Trevor Parker ◽  
Bryan Jonas ◽  
Bryan Adams ◽  
Nicholas J Clark

Quick identification of building and roads is critical for execution of tactical US military operations in an urban environment. To this end, a gridded, referenced, satellite images of an objective, often referred to as a gridded reference graphic or GRG, has become a standard product developed during intelligence preparation of the environment. At present, operational units identify key infrastructure by hand through the work of individual intelligence officers. Recent advances in Convolutional Neural Networks, however, allows for this process to be streamlined through the use of object detection algorithms. In this paper, we describe an object detection algorithm designed to quickly identify and label both buildings and road intersections present in an image. Our work leverages both the U-Net architecture as well the SpaceNet data corpus to produce an algorithm that accurately identifies a large breadth of buildings and different types of roads. In addition to predicting buildings and roads, our model numerically labels each building by means of a contour finding algorithm. Most importantly, the dual U-Net model is capable of predicting buildings and roads on a diverse set of test images and using these predictions to produce clean GRGs.


Coatings ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 207
Author(s):  
Pavel Koštial ◽  
Zora Koštialová Jančíková ◽  
Robert Frischer

These days there are undeniably unique materials that, however, must also meet demanding safety requirements. In the case of vehicles, these are undoubtedly excellent fire protection characteristics. The aim of the work is to experimentally verify the proposed material compositions for long-term heat loads and the effect of thickness, the number of laminating layers (prepregs) as well as structures with different types of cores (primarily honeycomb made of Nomex paper type T722 of different densities, aluminum honeycomb and PET foam) and composite coating based on a glass-reinforced phenolic matrix. The selected materials are suitable candidates for intelligent sandwich structures, usable especially for interior cladding applications in the industry for the production of means of public transport (e.g., train units, trams, buses, hybrid vehicles).


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