Zobrazeno 1 - 10
of 184
pro vyhledávání: '"ALEXANDER G. KEMP"'
Autor:
Harvie, Chris
Publikováno v:
Northern Scotland. May2013, Vol. 4 Issue 1, p66-77. 12p.
Autor:
Chris Harvie
Publikováno v:
Northern Scotland. 4:66-77
Autor:
Harvie, Chris
Publikováno v:
Northern Scotland; May 1981, Vol. 4 Issue: 1 p66-77, 12p
Publikováno v:
Safety Science. 148:105634
Publikováno v:
Journal of Petroleum Science and Engineering. 207:109109
Many recent discoveries in the UKCS have been economically marginal and comparatively small such that they are unable to be developed on a standalone basis. Nevertheless, there is a proliferation of production facilities and transport infrastructure
Publikováno v:
Energy Policy. 155:112354
Anecdotal evidence from the United Kingdom's offshore oil and gas industry indicates that risk-based safety regulations, introduced in the aftermath of the 1988 Piper Alpha disaster which killed 167 offshore workers, have improved safety outcomes suc
Publikováno v:
Energy Economics. 97:105233
Hundreds of newly discovered or previously appraised but undeveloped UKCS fields are small. As standalone developments, many of these fields are economically unviable. Meanwhile to extend the term of exploration and production activities in the matur
Autor:
Linda Stephen, Alexander G. Kemp
Publikováno v:
SSRN Electronic Journal.
This study employs financial simulation modelling, including use of the Monte Carlo technique, to project oil and gas activity levels in the UK Continental Shelf to 2050 with an oil price scenario gradually rising from 2019 onwards to reach $100 per
Autor:
Linda Stephen, Alexander G. Kemp
Publikováno v:
SSRN Electronic Journal.
This paper examines the effects of different investment hurdle rates on capital expenditure and production relating to new oil and gas fields in the UK Continental Shelf over the period 2017-2050. Financial simulation modelling, including the use of
Autor:
Alexander G. Kemp, Jingzhen Liu
Publikováno v:
SSRN Electronic Journal.
In this study, we investigate whether we can identify a probit model with macroeconomic variables to forecast the monthly excess return signs of the U.S. oil and gas industry index by mining a big macroeconomic variable dataset designed by McCracken