Schlumberger - Log Interpretation Principles - ...
Schlumberger - Log Interpretation Principles - ... ---> https://cinurl.com/2tkUzo
Published in 1989, Cased Hole Log Interpretation Principles/Applicationsprovides a thorough background in cased hole log interpretation, the process bywhich parameters measured through casing, e.g., thermal decay time and intervaltransit time, are translated into the desired petrophysical parameters ofporosity, hydrocarbon saturation, producibility, lithology, and mechanical rockproperties. These parameters are used to identify potential hydrocarbon-bearingstrata.
Published in 1991, Log Interpretation Principles/Applications provides a thorough background of log interpretation. It presents a review of well logging methods and interpretation techniques. The various openhole services offered by Schlumberger are discussed in some detail, together with essential methods of interpretation and basic applications. The discussion is kept as brief and clear as possible, with a minimum of derivational mathematics. Topics include spontaneous potential and natural gamma ray logs, formation water resistivity determination, and mechanical properties of rocks.
Earlier this week we published our fourth cheatsheet, this time for well log analysis or petrophysics. (Have you seen our other cheatsheets) Why did we think this was a subject tricky enough to need a cheatsheet in the back of your notebook I think there are at least three things which make the interpretation of log data difficult:
The present research applies six empirical, three statistical, and two soft computing methods to predict water saturation of an oil reservoir. The employed empirical models are `Archie (Trans AIME 146(1):54-62, 1942),' `DeWitte (Oil Gas J 49(16):120-134, 1950),' `Poupon et al. (J Petrol Technol 6(6):27-34, 1954),' `Simandoux (Revue deI'Institut Francais du.Petrol, 1963),' `Poupon and Leveaux (1971),' and `Schlumberger (Log interpretation principles/applications, p. 235, 7th printing. Houston, 1998)'; statistical methods are `multiple variable regression,' `fine tree, medium tree, coarse tree-based regression tree,' and `bagged tree, boosted tree-based tree ensembles'; and soft computing techniques are `support vector machine (SVM)' and `Levenberg-Marquardt (LM), Bayesian regularization (BR), and scaled conjugate gradient (SCG)-based artificial neural network (ANN).' In addition, log variables are ranked based on their significance in water saturation modeling. To achieve the goals, 521 data points are selected from three wells. Each data point has laboratory-derived core water saturation information and six well log features, such as gamma ray (GR), bulk density (RHOB), sonic travel time (DT), true resistivity (LLD), neutron porosity (φN), and Depth. Statistical indexes, namely regression coefficient, mean squared error, root mean squared error, average absolute percentage error, minimum absolute error percentage, and maximum absolute error percentage, are used to compare the prediction efficiency of study methods. Results show that the empirical models provide exceedingly poor prediction efficiency. Within the study models, fine tree, medium tree-based regression tree; bagged tree, boosted tree-based tree ensembles; fine Gaussian SVM; ANN with LM; and ANN with BR are very efficient predictive strategies. The log ranking reveals that GR and DT are the most important, whereas RHOB and φN are the least vital predictor variables in water saturation prediction.
Davidson, D. M., Jr., 1982, Geological evidence relating to interpretation of the Lake Superior Basin structure; in, 2, Upper Precambrian sedimentary rocks--Oronto Group, Michigan-Wisconsin; in, Wold, R. J., and Hinze, W. J., eds., Geology and Tectonics of the Lake Superior Basin: Geological Society of America, Memoir 156, p. 5-14.
Fraser, G. D., Witkind, I. J., and Nelson, W. H., 1964, A geological interpretation of the epicentral area--the dual-basin concept: U.S. Geological Survey, Professional Paper No. 435, p. 99-106.[available online]
Serra, O., Baldwin, J. L., and Quirein, J. A., 1980, Theory, interpretation, and practical applications of natural gamma ray spectroscopy: Trans., 21st Annual Symposium, Society of Professional Well Log Analysts, Paper Q, 30 p.
Available from the Society of Petroleum Engineers Bookstore, this book introduces dynamic properties of reservoir rock and produced fluids and pressure sensors technology. Subsequent chapters describe well testing operations and data collection, test design considerations, reservoir fluid sampling and static pressure applications. Like the preceding chapters, discussions of transient testing interpretation principles and advanced applications of transient testing reinforce the value of formation testing. The book also discusses testing interpretation software. Each chapter includes references to significant technical papers for readers seeking additional information. 59ce067264
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