GEOTHERMAL TECHNOLOGIES LEGACY COLLECTION - Bibliographic Citation


Bibliographic Citation



Some links on this page may take you to non-federal websites. Their policies may differ from this site.
Full Text: Citation URL: http://www.osti.gov/geothermal/product.biblio.jsp?osti_id=1050872
Title: Fracture Characterization in Enhanced Geothermal Systems by Wellbore and Reservoir Analysis
Creator/Author: Roland N. Horne, Kewen Li, Mohammed Alaskar, Morgan Ames, Carla Co, Egill Juliusson, Lilja Magnusdottir
Publication Date:2012 Jun 30
OSTI Identifier:OSTI 1050872
Report Number(s):Final2012
DOE Contract Number:FG36-08GO18192
Document Type:Technical Report
Specific Type:
Coverage:Final
Resource Relation:
Other Number(s):
Research Org:Stanford University
Sponsoring Org:USDOE
Subject:15 GEOTHERMAL ENERGY
Keywords:fractures, nanosensors, resistivity, enhanced geothermal systems
Description/Abstract:This report highlights the work that was done to characterize fractured geothermal reservoirs using production data. That includes methods that were developed to infer characteristic functions from production data and models that were designed to optimize reinjection scheduling into geothermal reservoirs, based on these characteristic functions. The characterization method provides a robust way of interpreting tracer and flow rate data from fractured reservoirs. The flow-rate data are used to infer the interwell connectivity, which describes how injected fluids are divided between producers in the reservoir. The tracer data are used to find the tracer kernel for each injector-producer connection. The tracer kernel describes the volume and dispersive properties of the interwell flow path. A combination of parametric and nonparametric regression methods were developed to estimate the tracer kernels for situations where data is collected at variable flow-rate or variable injected concentration conditions. The characteristic functions can be used to calibrate thermal transport models, which can in turn be used to predict the productivity of geothermal systems. This predictive model can be used to optimize injection scheduling in a geothermal reservoir, as is illustrated in this report.
Publisher:
Country of Publication:US
Language:English
Size/Format:Medium: ED; Size: 7MB
Rights:
Availability:
System Entry Date:2014 Oct 10
  U.S. Department of Energy Vertical Bar Vertical Bar Vertical Bar