scholarly journals Impact of inclusive hadron production data on nuclear gluon PDFs

2021 ◽  
Vol 104 (9) ◽  
Author(s):  
P. Duwentäster ◽  
L. A. Husová ◽  
T. Ježo ◽  
M. Klasen ◽  
K. Kovařík ◽  
...  
Keyword(s):  
Hadron Production ◽  
Production Data ◽  
Nuclear Gluon

scholarly journals Extraction of Transversity from COMPASS and Belle Data

2016 ◽  
Vol 40 ◽  
pp. 1660034
Author(s):  
Franco Bradamante
Keyword(s):  
Inelastic Scattering ◽  
Deep Inelastic Scattering ◽  
Hadron Production ◽  
Production Data

The valence transversity distributions of the u- and the d-quarks have been extracted point-by-point from single-hadron production and dihadron production data measured in semi-inclusive deep inelastic scattering and in [Formula: see text] annihilation. The transversity distributions are found to be compatible with each other and with previous analyses.

scholarly journals Phenomenological Extraction of Transversity from COMPASS SIDIS and Belle e+e- Data

2015 ◽  
Vol 37 ◽  
pp. 1560062
Author(s):  
Franco Bradamante
Keyword(s):  
Inelastic Scattering ◽  
Deep Inelastic Scattering ◽  
Hadron Production ◽  
Production Data

The valence transversity distributions of the u- and the d-quarks have been extracted point-by-point from single-hadron production and dihadron production data measured in semi-inclusive deep inelastic scattering and in e+e annihilation. The extraction is based on some simple assumptions and does not require any parametrization. The transversity distributions are found to be compatible with each other and with previous analyses.

RESULTS ON HADRON PRODUCTION AT CESR

1982 ◽  
Vol 43 (C3) ◽  
pp. C3-40-C3-41 ◽  
Author(s):  
F. M. Pipkin
Keyword(s):  
Hadron Production

Mahakam Field Characterization Using Production Type-Curve With Business Intelligence Application

2020 ◽  
Author(s):  
P. Noverri
Keyword(s):  
Business Intelligence ◽  
Data Gathering ◽  
Production Data ◽  
Type Curve ◽  
Type Curves ◽  
Production Type ◽  
Efficient Data ◽  
Production Behavior ◽  
Factor Type ◽  
Mahakam Delta

Delta Mahakam is a giant hydrocarbon block which is comprised two oil fields and five gas fields. The giant block has been considered mature after production for more than 40 years. More than 2,000 wells have been drilled to optimize hydrocarbon recovery. From those wells, a huge amount of production data is available and documented in a well-structured manner. Gaining insight from this data is highly beneficial to understand fields behavior and their characteristics. The fields production characterization is analyzed with Production Type-Curve method. In this case, type curves were generated from production data ratio such as CGR, WGR and GOR to field recovery factor. Type curve is considered as a simple approach to find patterns and capture a helicopter view from a huge volume of production data. Utilization of business intelligence enables efficient data gathering from different data sources, data preparation and data visualization through dashboards. Each dashboard provides a different perspective which consists of field view, zone view, sector view and POD view. Dashboards allow users to perform comprehensive analysis in describing production behavior. Production type-curve analysis through dashboards show that fields in the Mahakam Delta can be grouped based on their production behavior and effectively provide global field understanding Discovery of production key information from proposed methods can be used as reference for prospective and existing fields development in the Mahakam Delta. This paper demonstrates an example of production type-curve as a simple yet efficient method in characterizing field production behaviors which is realized by a Business Intelligent application

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