skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Computational geometry as an aid to data analysis of drilling data.


No abstract prepared.

Publication Date:
Research Org.:
Sandia National Laboratories
Sponsoring Org.:
OSTI Identifier:
Report Number(s):
TRN: US0703135
DOE Contract Number:
Resource Type:
Resource Relation:
Conference: Proposed for presentation at the Digital Electronics Conference SPE held April 10-12, 2007 in Houston, TX.
Country of Publication:
United States

Citation Formats

Knudsen, Steven Dell. Computational geometry as an aid to data analysis of drilling data.. United States: N. p., 2007. Web.
Knudsen, Steven Dell. Computational geometry as an aid to data analysis of drilling data.. United States.
Knudsen, Steven Dell. Thu . "Computational geometry as an aid to data analysis of drilling data.". United States. doi:.
title = {Computational geometry as an aid to data analysis of drilling data.},
author = {Knudsen, Steven Dell},
abstractNote = {No abstract prepared.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Feb 01 00:00:00 EST 2007},
month = {Thu Feb 01 00:00:00 EST 2007}

Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

Save / Share:
  • Abstract not provided.
  • As explained by Halliburton Services, a substantial percentage of drillstem tests cannot be analyzed by conventional methods because of insufficient data. For these situations, the recently developed type-curve matching techniques aid in analyzing the data. Halliburton Services discusses the applicability of the various type-curve techniques available and recommends specific procedures to avoid misinterpretation.
  • A substantial percentage of drillstem tests cannot be analyzed by conventional methods due to insufficient data. Numerous tests have been analyzed by several published type curves. In this paper, many examples are included where the application of the appropriate type curve aided in providing correct analysis of data which otherwise may have been misinterpreted.
  • Research involving very large sets of digital data is often difficult due to the enormity of the database. In the case of a wind turbine operating under varying environmental conditions, determining which data are representative of the blade aerodynamics and which are due to transient flow ingestion effects or errors in instrumentation, operation, and data collection is of primary concern to researchers. The National Renewable Energy Laboratory in Golden, Colorado collected extensive data on a downwind horizontal axis wind turbine (HAWT) during a turbine test project called the Combined Experiment. A principal objective of this experiment was to provide amore » means to predict HAWT aerodynamic, mechanical, and electrical operational loads based upon analytical models of aerodynamic performance related to blade design and inflow conditions. In a collaborative effort with the Aerospace Engineering Department at the University of Colorado at Boulder, a team of researchers has evolved and utilized various digital filtering techniques in analyzing the data from the Combined Experiment. A preliminary analysis of the data set was performed to determine how to best approach the data. The reduced data set emphasized selection of inflow conditions such that the aerodynamic data could be compared directly to wind tunnel data obtained for the same airfoil design as used for the HAWT`s blades. It will be shown that this reduced data set has yielded valid, reproducible results that a simple averaging technique or a random selection approach cannot achieve. These findings provide a stable baseline against which operational HAWT data can be compared.« less
  • During the past twenty years, various computational methods have been developed for estimating paleostress states from field measurements of fault populations which are assumed to be coeval. Unfortunately, there has been little critical assessment of the accuracy of such techniques or any quantitative comparisons between the different techniques which have been proposed. Fault population paleostress analysis methods usually require, as input, field measurements of fault orientations and their associated slip vectors. These methods then return a best-fit guess for the orientations of the three principal stress axes [sigma][sub 1], [sigma][sub 2], and [sigma][sub 3] and a parameter [Phi] representing theirmore » relative magnitudes [([sigma][sub 2]-[sigma][sub 3])/([sigma][sub 1]-[sigma][sub 3])]. Synthetic fault-slip data sets, as opposed to field-collected data,, are created by assuming fixed orientations for the [sigma][sub 1], [sigma][sub 2], and [sigma][sub 3] axes and a fixed value of [Phi]. A suitable population of fault planes are then adopted and the maximum resolved shear stress direction, assumed to be coincident with the slip direction, is calculated for each fault. Synthetically-generated fault-slip data sets should thus be ideal for testing computational methods of paleostress analysis since they may be created in a manner consistent with the underlying assumptions made by all paleostress analysis techniques. For testing the accuracy of several different paleostress analysis methods, fault-slip data sets were created which varied gradationally from randomly-oriented fault populations to those which has strongly-preferred orientations. With these and other types of fault-slip data sets, the accuracy of the various paleostress analysis methods may be quantified and different methods may be meaningfully compared.« less