Saudi Arabian Oil Company

Schlumberger Technology Corporation

Ramsin Yacood Eyvazzadeh

David Kersey

Denis P Schmitt

David Furse Allen

Steve F Crary

Edward Alan Clerke

George Bordakov

Charles Bradford

George Saghiyyah

Philip Savundararaj

Johannes J Buiting

Paul Smith

Jim Funk

Hilal Al-Waheed

David Grahame Kersey

A determination of the free water level for a hydrocarbon-bearing reservoir is provided that accounts for the different classified rock types (that is, facies) in the reservoir. The free water level for each unique combination of facies is determined using a least squares minimization between a reference bulk volume of oil (B) determined from well logs a bulk volume of oil (B) calculated from a saturation height function for each of the facies present in the reservoir. Systems and process for determining the free water level are provided.

Rock type based free water level inversion

A petrophysically regularized time domain nuclear magnetic resonance (NMR) inversion includes using an NMR tool to acquire NMR data and inverting the acquired NMR data in a time domain using petrophysical constraints. The inverted NMR data is analyzed. The petrophysical constraints may be identified by: determining a number of porobodons to seek, defining a plurality of zones in which only a subset of porobodon sets is present, and stacking all NMR echoes in each zone satisfying discriminators. The number of porobodons to seek may be based on knowledge of core samples, logs, and NMR sensitivity. The discriminator logs may be logs sensitive to porosity partitioning. A computing system having a processor, a memory, and a program stored in memory may be configured to perform the method. The system may be conveyed downhole on a wireline, a while-drilling drill string, a coiled tubing, a slickline, or a wired drill pipe.

Petrophysically regularized time domain NMR inversion

A system and method identify hydrocarbon productive reservoir zones using Monte Carlo numerical analysis to account for uncertainties in log measurements and petrophysical parameters. Random errors in logging tool responses and core measurements, as well as reservoir heterogeneity, are incorporated in a Monte Carlo simulation to output appropriate petrophysical models to calculate statistical distributions for saturation and permeability to define productive zones, non-productive zones and zones of undetermined productivity as a basis of deciding whether additional logging, core sampling or well test data are needed to reclassify the undetermined zones as either productive or non-productive. As uncertainties are quantified in the analysis, the degree of certainty in determining productive and non-productive zones is known and can be used to decide whether to further test, stimulate or abandon reservoir zones.

Monte Carlo simulation of well logging data

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Dhahran, Saudi Arabia

Ramsin Yacood Eyvazzadeh