Improved Treatment Distribution Through Oriented Perforating

2021 ◽  
Author(s):  
Jon Snyder ◽  
David Cramer ◽  
Matt White
Keyword(s):  
Horizontal Well ◽  
Data Entry ◽  
South Texas ◽  
Statistical Process ◽  
Straight Line ◽  
Standard Design ◽  
Limited Entry ◽  
Treatment Volume ◽  
Multi Phase ◽  
Hole Dimensions

Abstract Perforation-imaging studies have indicated highly variable results on effectively treating all perforation clusters within a given fracturing stage in horizontal well plug-and-perf applications, even when limited entry designs were used. A field test was executed to trial differing perforating designs and levels of perforation friction for identifying a preferred technique for evenly distributing treatment volume along the lateral. The test was implemented in a horizontal well in the Eagle Ford formation of south Texas. After treatment and plug drill-out operations were completed, a downhole camera was run to visualize perforation entry holes along the entire lateral section. Shaped perforating charges described as equal entry hole charges were used in all stages. The resulting images were analyzed to determine entry hole dimensions and erosion characteristics to determine if alternate perforating strategies provided improved results, as compared to the standard design of multi-phase perforating with 1200 psi of perforation friction. Test results indicate that orienting perforations in a straight line (zero-phase) along the high side of the wellbore significantly improved treatment distribution among perforation clusters. Oriented perforating achieved this benefit without needing to increase initial perforation friction beyond the area standard of 1200 psi. Another result from this project was development of a statistical process for evaluating perforation entry hole erosion data. Entry hole erosion datasets are complex and difficult to analyze. The statistical process presented in this paper demonstrates a clear way to compare the effectiveness of different perforation designs. This paper also covers the operational difficulties encountered during the project which added complexity to analyzing the results. Lastly, this paper offers suggestions for future modifications for oriented perforation designs to further improve limited entry effectiveness.

scholarly journals Using a network organisational architecture to support the development of Learning Healthcare Systems

2018 ◽  
Vol 27 (11) ◽  
pp. 937-946 ◽  
Author(s):  
Maria T Britto ◽  
Sandra C Fuller ◽  
Heather C Kaplan ◽  
Uma Kotagal ◽  
Carole Lannon ◽  
...  
Keyword(s):  
Healthcare System ◽  
Point Of Care ◽  
Data Entry ◽  
Regulatory Compliance ◽  
Clinical Encounter ◽  
Learning System ◽  
National Academy Of Sciences ◽  
Statistical Process ◽  
Learning Healthcare System ◽  
Communication Policies

The US National Academy of Sciences has called for the development of a Learning Healthcare System in which patients and clinicians work together to choose care, based on best evidence, and to drive discovery as a natural outgrowth of every clinical encounter to ensure innovation, quality and value at the point of care. However, the vision of a Learning Healthcare System has remained largely aspirational. Over the last 13 years, researchers, clinicians and families, with support from our paediatric medical centre, have designed, developed and implemented a network organisational model to achieve the Learning Healthcare System vision. The network framework aligns participants around a common goal of improving health outcomes, transparency of outcome measures and a flexible and adaptive collaborative learning system. Team collaboration is promoted by using standardised processes, protocols and policies, including communication policies, data sharing, privacy protection and regulatory compliance. Learning methods include collaborative quality improvement using a modified Breakthrough Series approach and statistical process control methods. Participants observe their own results and learn from the experience of others. A common repository (a ‘commons’) is used to share resources that are created by participants. Standardised technology approaches reduce the burden of data entry, facilitate care and result in data useful for research and learning. We describe how this organisational framework has been replicated in four conditions, resulting in substantial improvements in outcomes, at scale across a variety of conditions.

A Medical Data Trustworthiness Assessment Model

2011 ◽  
pp. 130-150 ◽  
Author(s):  
Bandar Alhaqbani ◽  
Colin Fidge
Keyword(s):  
Data Entry ◽  
Medical Practitioner ◽  
Medical Data ◽  
Assessment Model ◽  
Health Record ◽  
Digital Repository ◽  
Statistical Process ◽  
Medical Practitioners ◽  
Data Trustworthiness ◽  
Electronic Health

Electronic Health Record systems are being introduced to overcome the limitations associated with paper-based and isolated Electronic Medical Record systems. This is accomplished by aggregating medical data and consolidating them in one digital repository. Though an EHR system provides obvious functional benefits, there is a growing concern about reliability trust (trustworthiness) of Electronic Health Records. Security requirements such as confidentiality, integrity, and availability can be satisfied by traditional data security mechanisms. However, measuring data trustworthiness is an issue that cannot be solved with traditional mechanisms, especially since degrees of trust change over time. In this chapter, a Medical Data Trustworthiness Assessment model to assist an EHR system to validate the trustworthiness of received/stored medical data based on who entered the data and when is presented. The MDTA model uses a statistical approach that depends on the observed experiences available to the EHR system. In order to provide an accurate trustworthiness estimate for historical medical data, a time scope around the time when the data was entered was used. This scope enables the model to capture the dynamic behavior of the data entry agent’s trustworthiness. To conduct this assessment medical metadata is used to extract information about the medical data sources (e.g. timestamps, and the identities of healthcare agents and medical practitioners) and, thereafter, this information is used in a statistical process to derive a trustworthiness value for the medical data. The result can then be expressed in the displayed health record by manipulating the EHR’s metadata to alert the medical practitioner to possible trustworthiness problems.

Study on Horizontal Well Fracture in Low Permeability Reservoirs

2012 ◽  
Vol 524-527 ◽  
pp. 1587-1590
Author(s):  
Wen Bin Cai ◽  
Guo Wei Qin ◽  
Yong Fu An ◽  
Yun Long Zhang
Keyword(s):  
Production Rate ◽  
Horizontal Well ◽  
Development Process ◽  
Low Permeability ◽  
Improve Production ◽  
Vertical Permeability ◽  
Limited Entry ◽  
Mechanical Isolation ◽  
Low Permeability Reservoirs

In the low permeability reservoirs development process, some times horizontal well is not meet the anticipant production for low vertical permeability or serious reservoir damage, so the horizontal well fracture is needed to improve production rate, several fractures would be created along the length of horizontal well to get the more production rate and ultimate recovery. The fracture shapes was introduced, the principle, characteristics and treatment steps of different Multi-interval fracturing technique was analyzed such as chemical isolation, mechanical isolation, hydraulic sand blast, and limited entry fracturing technology, the feature of limited entry treatment and staged fracturing treatment were discussed for providing some suggestion to field fracturing technology choosing.

Case History of an Opposed-Bore, Dual Horizontal Well in the Austin Chalk Formation of South Texas

1993 ◽  
Vol 8 (01) ◽  
pp. 14-20
Author(s):  
M.F. Cooney ◽  
C.T. Rogers ◽  
E.S. Stacey ◽  
R.N. Stephens
Keyword(s):  
Case History ◽  
Horizontal Well ◽  
South Texas ◽  
Austin Chalk ◽  
History Of

A Sharp Interface Method for Compressible Multi-Phase Flows Based on the Cut Cell and Ghost Fluid Methods

2017 ◽  
Vol 9 (5) ◽  
pp. 1052-1075 ◽  
Author(s):  
Xiao Bai ◽  
Xiaolong Deng
Keyword(s):  
Level Set ◽  
Sharp Interface ◽  
Reconstruction Method ◽  
Topological Change ◽  
Sharp Interface Method ◽  
Cut Cell ◽  
Straight Line ◽  
Variable Domains ◽  
Mixing Method ◽  
Multi Phase

AbstractA new sharp interface method with the combination of Ghost Fluid Method (GFM) and Cut Cell scheme is developed to study compressible multi-phase flows with clear interfaces. Straight-line cutting is applied on the cells passed by the interface. A new real-ghost mixing method is presented and applied around the cut cells to deal with very small cut cells. A cut face reconstruction method similar to volume of fluid is applied to deal with topological change problems. A high order Level Set (LS) method is applied to evolve the free interface, with the Level Set velocities from exact Riemann solver on the cut faces. Various 1D and 2D numerical examples are tested to show the robustness and ability of the present method in wide flow variable domains. This method benefits from cut cell on the sharp interface description, shows good conservation performance, and does not have the topological change difficulty of the full cut cell method presented in Chang, Deng & Theofanous, J. Comput. Phys., 242 (2013), pp. 946–990.

scholarly journals Applying Persuasive Design Techniques to Change Data Entry Behaviour in Primary Care (Preprint)

2017 ◽  
Author(s):  
Justin St-Maurice ◽  
Catherine Burns ◽  
Justin Wolting
Keyword(s):  
Primary Care ◽  
Data Quality ◽  
Systems Analysis ◽  
Data Entry ◽  
Systems Design ◽  
Statistical Process ◽  
Registry System ◽  
Viable Approach ◽  
Entry Behavior ◽  
Persuasive Systems

BACKGROUND Persuasive design (PD) is an approach that seeks to change the behaviours of users by using design and social influence. In primary care, clinician behaviours and attitudes are important precursors to structured data entry, and there is an impact on overall data quality. This research hypothesizes that PD could change data entry behaviours in clinicians and improve data quality. OBJECTIVE Our objective was to use PD principles to change clinician data-entry behaviours in a primary care environment and to increase data quality within a registry system. METHODS We performed a detailed systems analysis of the data-entry task by using cognitive work analysis (CWA). We used the results of this analysis with the Persuasive Systems Design (PSD) framework to describe the persuasion context. We identified several PD principles to be introduced in a new summary screen, which became part of the data entry workflow. As part of our experimental design, we defined three data quality measures (same-day entry, record completeness, and data validity) to measure changes in data quality and entry behaviour. We measured the impacts of the new screen with a paired pre/post t-test and generated XmR charts to contextualize the results. RESULTS 53 users were shown the new screen during their data entry over the course of 10 weeks. Based on a pre-post analysis, the new summary screen successfully encouraged users to enter more of their data on the same day as their encounter. The percentage of same-day entries increased by 10.34% (P < 0.001). During the first month of the new screen, users compensated by sacrificing aspects of data completeness, before returning to normal in the second month. Improvements to record validity were marginal over the study period (P = 0.045). Statistical process control techniques allowed us to study the XmR charts to contextualize our results and understand trends throughout the study period. CONCLUSIONS By conducting a detailed systems analysis and introducing new PD elements into a data entry system, we demonstrated it was possible to change data-entry behavior and influence data quality in a reporting system. The results show that using PD concepts may be effective at influencing data entry behaviours in clinicians. There may be opportunities to continue improving this approach, and further work is required to perfect and test additional designs. Persuasive design is a viable approach to encourage clinician user change and could support better data capture in the field of medical informatics.

Numerical simulation of limited-entry multi-cluster fracturing in horizontal well

2017 ◽  
Vol 152 ◽  
pp. 443-455 ◽  
Author(s):  
Yang Li ◽  
Jingen Deng ◽  
Wei Liu ◽  
Wei Yan ◽  
Yongcun Feng ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Horizontal Well ◽  
Limited Entry

A Medical Data Trustworthiness Assessment Model

2012 ◽  
pp. 1425-1445
Author(s):  
Bandar Alhaqbani ◽  
Colin Fidge
Keyword(s):  
Data Entry ◽  
Medical Practitioner ◽  
Medical Data ◽  
Assessment Model ◽  
Health Record ◽  
Digital Repository ◽  
Statistical Process ◽  
Medical Practitioners ◽  
Data Trustworthiness ◽  
Electronic Health

Electronic Health Record systems are being introduced to overcome the limitations associated with paper-based and isolated Electronic Medical Record systems. This is accomplished by aggregating medical data and consolidating them in one digital repository. Though an EHR system provides obvious functional benefits, there is a growing concern about reliability trust (trustworthiness) of Electronic Health Records. Security requirements such as confidentiality, integrity, and availability can be satisfied by traditional data security mechanisms. However, measuring data trustworthiness is an issue that cannot be solved with traditional mechanisms, especially since degrees of trust change over time. In this chapter, a Medical Data Trustworthiness Assessment model to assist an EHR system to validate the trustworthiness of received/stored medical data based on who entered the data and when is presented. The MDTA model uses a statistical approach that depends on the observed experiences available to the EHR system. In order to provide an accurate trustworthiness estimate for historical medical data, a time scope around the time when the data was entered was used. This scope enables the model to capture the dynamic behavior of the data entry agent’s trustworthiness. To conduct this assessment medical metadata is used to extract information about the medical data sources (e.g. timestamps, and the identities of healthcare agents and medical practitioners) and, thereafter, this information is used in a statistical process to derive a trustworthiness value for the medical data. The result can then be expressed in the displayed health record by manipulating the EHR’s metadata to alert the medical practitioner to possible trustworthiness problems.

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