... lower brushy canyon interval porosity brushy canyon water saturation log analysis machine learning cercion truman correlation coefficient neural network weiss well logging architecture information brushy canyon interval stubb core information spe 70041 balch artificial...

... geological modeling vertical variogram spe 70012 simulation variability artificial intelligence geologic modeling variogram cumulative distribution function horizontal-well log hassi messaoud field information lag distance pressure data upstream oil & gas histogram...

... neural network exploration tool well log risk assessment presentation spe 70054 interface expert system risk reduction online database information prrc nm tech fuzzy logic fuzzy-expert exploration tool risk management artificial intelligence geophysical data risk and uncertainty...

... pressure transient testing relative pipe roughness drillstem testing friction factor flow regime pressure drop conductivity solution horizontal well well length conductivity upstream oil & gas wellbore artificial intelligence Copyright 2001, Society of Petroleum Engineers Inc. This paper...

.... 1 beam pumping artificial intelligence real time monitoring electricity cost upstream oil & gas volatility asset and portfolio management power cost supply agreement artificial lift system supplier agreement electricity customer spe 70033 oil field electric power cost...

... history fracture criteria artificial intelligence waterflooding producer team member permeability upstream oil & gas placement technique communication SPE 70068 Conformance Water-Management Team Developments and Solutions on Projects in the Permian Basin P. Creel, SPE, and G. Vavrek, SPE...

... two different approaches. artificial intelligence porosity texas spe 70034 reservoir characterization well logging log response cluster analysis machine learning carbonate reservoir permeability prediction correlation upstream oil & gas permeability north robertson unit...

... porosity at the Dagger Draw and better predictions are expected, as the process is refined and neural network algorithms are improved. The use of artificial intelligence to generate core porosity data using only wire-line log data can provide data that could only be attained previously using expensive...

... instantaneous frequency 0 zmap artificial intelligence seismic horizon frequency 0 machine learning spe 59555time-to-depth conversion prediction neural network reservoir characterization energy half time upstream oil & gas reservoir property fuzzy curve depth map Copyright 2000, Society...

.... Pressure readings are corrected by means of a tool internal Platinum RTD for accuracy. artificial intelligence collar locator micro-smart system safety parameter upstream oil & gas completion installation and operations innovation well condition flowmeter correlation stephen arnold...

... oil & gas weiss old gamma ray testing correlation coefficient artificial intelligence deep resistivity Copyright 2000, Society of Petroleum Engineers Inc. This paper was prepared for presentation at the 2000 SPE Permian Basin Oil and Gas Recovery Conference held in Midland, Texas, 21 23...

... cumulative water production prediction neural network creek field 2-month cumulative water production porosity information well prediction granite wash artificial intelligence completion production value SPE 39814 Granite Wash r m. 9 .Society of Petroleum Engineers Completion Optimization...

... testing pressure transient testing pressure transient analysis formation testing tight zone buildup artificial intelligence upstream oil & gas formation pressure efp compressibility spherical solution storage exact solution drillstem/well testing probe source radius permeability...

... & gas spe 39781 hydraulic fracturing application simulator simulation information reservoir characterization johnson artificial intelligence in-situ stress equation fracture propagation in-fill development reservoir pressure reservoir pressure gradient mm. Socie~=f Petroleum Engineere...

... the rod/coupling and fluid can be represented in terms of four parameters: the rod to tubing radius ratio, the coupling to tubing radius ratio, the fluid Reynolds number, and the relative rod velocity. P. 397 coupling production monitoring flow region friction factor turbulent flow artificial...

... university linear regression correlation structural geology machine learning drive mechanism net pay permeability noise artificial intelligence saturation nonlinearity SPE 39805 Modeling Nonlinear Phenomena Loveena Kapur, Larry W. Lake, and Kamy Sepehrnoori, The University of Texas at Austin...

... demonstration spe 35223 hn-p process enhanced recovery wellbore injection reservoir simulation soak period artificial intelligence production rate co 2 machine learning permeability Society of Petroleum Engineers SPE 35223 CO2 Huff-n-Puff: Initial Results from a Waterflooded sse Reservoir s. C...

... permeability, heterogeneous reservoir. One of the objectives is to develop methodologies by which other operators can perform the descriptions in other fields. well logging wettability core data reservoir artificial intelligence project welch field machine learning permeability mixed...

... oil & gas artificial intelligence spe 35184 assumption exploratory data analysis watercut pressure support well 103 Society of Petroleum Engineers SPE 35184 Exploratory Data Analysis of Production Data By: F.E. Jansen, SPE, and M.G. Kelkar, SPE, The University of Tulsa Copyright 1996...

... of the depositional sequences of the ramp and the shelf is helpful for the reservoir characterization. P. 927^ enhanced recovery andre reservoir depositional energy sedimentology northern shelf sequence machine learning artificial intelligence upstream oil & gas efficiency texas decline curve...