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September 2022 Meeting – Formation Testing
8th September 2022 @ 3:30 pm - 5:30 pm CESTFree
The next DPS meeting will be on Thursday 8th September 2022 with the topic “Formation Testing”.
The meeting will be held at our usual venue KIVI in Den Haag (Prinsessengracht 23, 2514 AP Den Haag) with doors opening for pre-meeting coffees at 15:30, and the meeting commencing at 16:00.
You can register for the meeting below or by emailing firstname.lastname@example.org with your details and affiliation.
We will have two presenters: Thomas Pfeiffer, Senior Staff Petrophysicist, Fluid Evaluation and Sampling Technology Team, Shell and Mirano Spalburg, Retired (formerly of Shell), who will share their expertise in two talks. Abstracts and presenter bios are below.
After the meeting there will be our usual social with drinks at a local cafe.
As always, thanks to the generosity of our sponsors, attendance is free for members of the DPS.
Looking forward to seeing you there,
The Dutch Petrophysical Society Board
Talk 1: Integrating Fluid Data for Optimum Decision Quality
Thomas Pfeiffer, Senior Staff Petrophysicist, Fluid Evaluation and Sampling Technology Team, Shell
Integration of formation testing and fluid data needs to be viewed in the subsurface context to arrive at the most probable and consistent answer about fluid grading and reservoir architecture.
We discuss how predrill information and advanced mud gas data help to plan pretest acquisition and gradient interpretation and how they guide sample acquisition. Sample data quality control identifies outliers and bad data. An instance of advanced sample analysis illustrates how the data can be used beyond its original purpose to further understanding of subsurface complexity. A discussion of acceptable contamination levels and special aspects when sampling water leads to interpretation techniques that identify the most consistent scenario.
Thomas Pfeiffer is currently a senior staff Petrophysicist in Shell’s Fluid Evaluation and Sampling Technology Team based in The Hague.
He holds Master of Science degrees in Petroleum Engineering from Texas A&M University and in Electrical Engineering from the Technical University of Munich, Germany.
Prior to joining Shell, Thomas has worked for 18 years at Schlumberger in various roles including Wireline Field Engineer, MDT specialist Engineer, Field Service Manager and Principal Reservoir Domain Champion.
Thomas has over 20 years’ experience in designing, executing and interpreting Wireline Formation Testing. In his position with Shell, he collaborates with all major wireline service companies and laboratory vendors.
Talk 2: Bayesian Formation Pressure Analysis
Mirano Spalburg, Retired
Formation pressure gradient analysis usually relies on the application of least squares linear regression to the measured data over the water, the oil, and the gas bearing sections, separately. Fluid density values are inferred from the slope of the regression lines. Free fluid level depths are inferred from the intercept positions
between the regression lines. Fluid density and free fluid level uncertainty may then be estimated using the slope and intercept uncertainty of the individual regression lines. However, this uncertainty analysis is cumbersome and does not provide a flexible statistical means to include prior knowledge on fluid density values and free fluid levels. To improve the situation, a new method, based on least squares linear- spline regression is presented. The method uses, as a pressure versus depth model, a single linear spline. A linear spline consists out of multiple linear line sections
connected at knots. The line sections represent pressure versus depth gradients per fluid section. The knots represent free fluid level positions. Disadvantage of this method is that mathematics does not (seem to) supply an analytical solution for fitting a linear spline to formation pressure data. Therefore, numerical methods are
applied that rely on generating a very large number of possible spline solutions, calculating the least squares fit value for each spline to the measured data, and summarizing the result as statistical distributions of free fluid levels depths and
formation fluid density values. These numerical methods enable a Bayesian interpretation, whereby each spline is given a prior probability that, together with its least squares fit result, yields a posterior probability. The analysis results are the
posterior probability distributions. In practice, many millions spline solutions are required to generate results with sufficient granularity and statistical resolution. Generating and analyzing that many splines takes less than a few seconds and that allows this new method to be applied interactively to formation pressure data
analysis. In addition to the method’s principles, application to a few field cases will be presented.
Mirano Spalburg is retired. He enjoyed working for Shell as a petrophysical assurer, a studies and operational petrophysicist, and as a researcher, over a 30+ years period. Research topics included dielectrics and resistivity interpretation, resolution enhancement of resistivity tools, modeling of logging while drilling tools, and the application of Bayesian belief networks to value of information cases. Operational and studies work included postings to the United Kingdom and Canada. Petrophysical assurance was focused on the worldwide work of studies teams in the Netherlands. He has a PhD in Mathematics and Physics and an almost lifelong affection for Bayesian methods.