Title:

A Comparison of Geothermal with Oil and Gas Well Drilling Costs

Authors:

Chad Augustine, Jefferson W. Tester, Brian Anderson, Susan Petty

Key Words:

drilling costs, index, correlation

Geo Location:

United States

Conference:

Stanford Geothermal Workshop

Year:

2006

Session:

Introduction

Language:

English

Paper Number:

Augustin

File Size:

237KB

View File:

Abstract:

The costs associated with drilling and completing wells are a major factor in determining the economic feasibility of producing energy from geothermal resources. In EGS power plants, estimates place drilling costs as accounting for 42%-95% of total power plant costs (Tester et al., 1994) depending on the quality of the EGS reservoir. An earlier correlation first developed by Milora and Tester (1976) and later refined by Tester and Herzog (1990) created a drilling cost index based on oil and gas well data from the Joint Association Survey (JAS) on Drilling Costs and used this index to compare the cost of drilling hot dry rock (HDR) and hydrothermal wells to the cost of oil and gas wells drilled to similar depths. This study updates and extends their earlier work. Oil and gas well costs were analyzed based on data from the 2003 JAS for onshore, completed US oil and gas wells. A new, more accurate drilling cost index that takes into consideration both the depth of a completed well and the year it was drilled was developed using the JAS database (1976-2003). The new index, dubbed the MIT Depth Dependent (MITDD) index, shows that well costs are up to 30% lower for wells over 4 km (13,000 ft) deep than those based on previous indices. The MITDD index was used to normalize predicted and actual completed well costs for both HDR or EGS (Engineered Geothermal Systems) and hydrothermal systems from various sources to year 2003 US dollars, and then compare and contrast these costs with oil and gas well costs. Additionally, a model for predicting completed geothermal well costs, called WellCost Lite (Mansure et al., 2005), is explained and demonstrated. Results from the model agree well with actual geothermal well costs. The model is used to identify factors that lead to rapid, non-linear increases in well cost with depth, such as increases in the number of casing strings required as depth increases with a resulting increase in rig capacity (embodied in mobilization, demobilization and daily rental costs), costs of casing and cementing the well, and changes in the rate of penetration.


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