Productivity in Exploration Drilling

Transcription

1 Productivity in Exploration Drilling Petter Osmundsen*, Kristin Helen Roll** and Ragnar Tveterås** 10th IAEE European Conference, Wien, * University of Stavanger / Norwegian School of Economics and Bus. Adm. ** University of Stavanger / International Research Institute of Stavanger

2 Introduction Drilling expenses have increased sharply in recent years Key causes of this increase include declining drilling productivity and higher rig rates We analyze an extensive data set on individual exploration wells on the Norwegian continental shelf to gain more knowledge on factors driving drilling productivity

3 Typical composition of drilling costs, Norwegian Continental Shelf (% shares) %&! "# "$ '()*+*,-./-*0+ 123*4)5+-6/+(6)/-5.*/7, 809*,-*:, ;*9 %$ <5.=*:5, Osmundsen, Roll og Tveterås

4 Day rates for high spec semi rigs operating on the NCS (new contracts), and high spec jackups in North West Europe, from 2004 to 2008

5 Average meters drilled per day. Exploration wells on the NCS, from 1966 to Annual number of wells in brackets. Black vertical lines indicate SD

6 Data set Source: Norwegian Petroleum Directorate Time period: Unit of observation: Well Well characteristics: Drilling depth, Water depth Drilling days Bottom hole temperature Appraisal/wildcat, discovery status (yes/no) Discovery content (gas, gas/condensate, oil, oil/gas) Name and type of drilling facility Name of operator (oil company) Location of well

7 Average drilled meters from 1970 to 2007

8 Average bottom hole temperature

9 Average water depth

10 Supply and demand conditions Access to drilling facilities and competent personnel on NCS probably an important determinant of productivity Oil price a potential proxy for scarcity Should expect drilling productivity to decline in total drilling activity level on NCS Lower productivity of marginal facilities and untrained personnel

11 Model specifications It cannot be determined a priori what is the correct model specification in terms of variables to be included We have estimated and tested a large number of model specifications Will only present econometric estimates from one of the most general models

12 Econometric translog type production function specification lny = Σ i α i lnx i + 0.5Σ i Σ j α ij lnx i lnx j + α t t + α t2 t 2 + α t3 t 3 + Σ i α it lnx i t + α tp lnoilprice + α OP lnoilprice + α OP2 lnoilprice 2 + Σ i α ip lnx i lnoilprice + Σ r µ r OilCoType r + Σ s µ s FacilityType s + Σ e µ se FacilityExperience e + µ D Discovery + µ W Purpose + µ WBS WellBoreStatusPA + Σ a µ a Area a + u

13 Dependent variable: Average meters drilled per day Total meters drilled from sea bed, not vertical drilling depth Common measure of drilling productivity in oil industry, e.g. Rushmore benchmarking Osmundsen, Roll og Tveterås

14 Explanatory variables 1 X includes well depth in meters, water depth in meters, and well temperature. Terms with the time trend variable t are included to control for technological change. OilPrice a proxy for the supply and demand conditions in the drilling market. OilCoType dummy describes the type of oil company, with mid caps am and three sisters as reference category, rest as dummy variable 1 and mid caps euro as dummy variable 2. FacilityExperience dummy variables control for drilling experience among drilling facilities, where the facilities are separated in three groups based on their drilling experience on NCS. If the drilling facility has drilled less than 10 times at NCS over the data period it is classified as less experienced, between times intermediate experienced, and above 30 times much experienced.

15 Explanatory variables 2 FacilityType dummy variable controls for the type of drilling rig. The most common facility type is semisub steel, and this is the default category. WellboreStatusPA variable controls for the wellbore status of the well. Most of the well s status is plugged and abandoned (P&A). We also control for discovery status of the well through the Discovery dummy variable, Area where the well has been drilled by the Area dummy variables. The wells are drilled in the three major offshore regions on the Norwegian Continental Shelf the North Sea, the Norwegian Sea and the Barents Sea. Purpose the drilling of specifying if the well is a wildcat or appraisal.

16 Elasticity Estimates Variable Mean t-value p-value Temperature Drilled meters Water depth Oil price TC

17 Empirical results Well temperature has a negative effect on drilling productivity. Drilling depth: Deeper wells are less productive than shallow wells Water depth: Water depth has a negative effect on productivity. Oil price: Drilling productivity slows down when oil prices increase. Technological change over time: We can trace a positive effect on productivity over time that we can attribute primarily to technological progress.

18 Future work Include well pressure data in analysis Analyze oil company performance and drilling operator performance using panel data models Analyze learning effects, from own experience and other in same exploration block Estimate technical inefficiencies using stochastic frontier production models