March 2009 The Geomodeling Network Newsletter


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March 2009 The Geomodeling Network Newsletter

  1. 1. The Geomodeling Network Newsletter March 2009 A very warm Spring 2009 welcome to all of our Geomodeling Network members wherever you are. Earlier on this month it was looking like the newsletter was going to be delayed through a lack of articles. However I am pleased to say that after some online harassment, our members rallied and the articles magically appeared just in the nick of time – so a big thank-you for those of you who have taken the time to contribute. I am always open to suggestions regarding our growing network and the shape and direction in which it takes us. Bearing this in mind, I have had a few members bending my ear recently who are concerned about the growing influence of online recruiters using the Geomodeling Network for their own commercial purposes. Whilst I am not totally adverse to some forms of commercialism in our group (you may even have spotted the subtle Blueback advertising throughout our newsletters); the intention is that this plays a minor role in what our Network is trying to accomplish. Indeed if you carry on reading this month’s newsletter you will see that there are articles from a number of software vendors (Halliburton, Schlumberger etc) which I think are interesting, relevant and provide a lot of value to the group. That said, I will keep my beady eye on the group as to what is being posted and will take great pleasure in removing articles (and members) if they are starting to become a nuisance. Mitch Sutherland Page 1 The Geomodeling Network – Sponsored by Blueback Reservoir
  2. 2. The Geomodeling Network Newsletter March 2009 Table of Contents Member Articles, Reviews & Questions 1. Property Modeling within modeled objects .... defining that thalweg! Has anyone successfully modelled rock properties at specific locations within facies objects? Juan Cottier, Subsurface Manager at Blueback Reservoir AS This has been taken from the Geomodeling Network discussion board and is a good example of how the board can be utilized to pose questions. Page 3 2. A faster and more accurate Gaussian method for property modelling in Petrel Colin Daly – Petrel product champion, geological modelling, Schlumberger Sandra Quental – Petrel product analyst, geological modelling, Schlumberger There were questions asked recently on the discussion board about the Gaussian method – this is timely input from Schlumberger! Page 5 3. Geology & Technology What kind of technology will geologists be using in 2025? An example of technology that today is in its infancy, but which may be more prevalent in the future. Simon Haworth - Geologist at Nexen Page 11 “Civilization exists by 4. High Frequency Characterization of an Outcropping Sinuous Leveed-Channel Complex, Dad Sandstone Member, Lewis geological consent, Shale, Wyoming subject to change This paper presents the results of data collection, analysis and integration to without notice.” build a 3D geological model of an outcropping leveed channel complex. Staffan Van Dyke - Geologist at Nexen Page 14 (Abstract only – see end of article on how to access the complete paper) -Will Durant Page 2 The Geomodeling Network – Sponsored by Blueback Reservoir
  3. 3. The Geomodeling Network Newsletter March 2009 “Rocks are records of 5. Free Petrel Plugin’s! What idiot said “you get nothing for free in this world?” Check out the latest events that took place free downloadable Petrel plugin’s now available from the Blueback Reservoir at the time they formed. software development team. Blueback Reservoir Page 14 They are books. They have a different 6. Geo2Flow vocabulary, a different Reserves Estimation – software that allows you to answer 3 crucial questions: alphabet, but you learn How much? How fast? And How connected? how to read them.” Dan O’Meara – Owner, O’Meara Consulting Page 17 -John McPhee 7. Requests for newsletter No5 Page 20 Member Articles, Reviews & Questions 1. Property Modeling within modeled objects .... defining that thalweg! Has anyone successfully modeled rock properties at specific locations within facies objects? Juan Cottier, Blueback Reservoir AS Clearly some further information is required here ..... For example, I want to be able to place certain poroperm values at certain locations within channels. I am working on the UK Forties fairway and I have been provided with some excellent facies work (facies logs, facies associations and very well integrated field analogues). The challenge is that within a distribution of porosity values I want to be able to place the very best poroperms at the centre of the channels and at the top of the channels, where as the poorest poroperms go at the base and sides. there are plenty of ways of trendng/cross correlating/analysing data per zone/layer within PETREL but there does not seem to be any quot;understandingquot; of the geometry of the bodies. Page 3 The Geomodeling Network – Sponsored by Blueback Reservoir
  4. 4. The Geomodeling Network Newsletter March 2009 Schlumberger Support, though very helpful, have no straight forward answer to this question. I have already created a workflow that allows me to define channel edges per K- layer and then use the distance from the channel edge to control levee or channel porosity distributions. It works exactly as I wish it to ... except ... it is cumbersome, ineffcient, requires conformable layering, requires precise set-up and is impractical beyond a certain number of k-layers. Beautiful results but not at all practical ...... rather like an Alfa Romeo. Any ideas? Or solutions? Thanks. Juan. Dave Hardy Reservoir geologist and reservoir modeller Juan, Use RMS ;-). It 'knows' about modelled objects. Intrabody trends are very easy to set up in all directions and work really well. In the old days before RMS had this I have used a facies object ID parameter and a script to define a vertical trend (loop trhough the layers and reset the distance every time the code changes). The script approach does not handle erosion terribly well and horizontal trends are tricky unless the objects are aligned with the grid but it was passable. I have no idea if that approach would be possible in PETREL or if it is any better than the solution you already have. Russell Cooper Geologist at OXY Permian Juan, Assuming you have a 'center of channel' and 'top of channel' poroperm equation to distinguish these areas from the rest of the model, perhaps respective of facies as well, you could use zone/layer filters in combination with a polygon(s) in geometrical modeling to create a center of channel and top of channel property and use these as references in a nested 'IF' equation to derive the desired permeability property. Page 4 The Geomodeling Network – Sponsored by Blueback Reservoir
  5. 5. The Geomodeling Network Newsletter March 2009 2 A faster and more accurate Gaussian method for property modelling in Petrel. to remember the order of Colin Daly & Sandra Quental – Schlumberger the geological time Petrel 2009.1, released last February, brings a new Gaussian simulation periods: “Cows Often Sit algorithm that will please our modeling community. The so-called Gaussian Down Carefully. Perhaps random function simulation (GRFS) differs substantially from the Sequential Gaussian simulation (SGS) from GSLIB: it is not sequential; it is parallelized and Their Joints Creak? hence typically faster than SGS. Plus it has an option to run a fast collocated co- Persistent Early Oiling simulation, with an interactive correlation coefficient slide bar. Might Prevent Painful The GRFS works using the well known decomposition which states: Rheumatism.” CONDITIONAL SIMULATION = KRIGING + UNCONDITIONAL SIMULATION For the kriging part of the equation, Petrel uses the parallel kriging algorithm introduced in 2008. This kriging algorithm is substantially faster than the old kriging algorithm in Petrel, particularly in the case of a lot of well data, and so makes use of the above decomposition practical and beneficial. (For example, on a test case with 3 million cells and 500 wells, the new algorithm runs in about 10 seconds compared to about 36 minutes for the old GSLIB based algorithm for identical results). The unconditional simulation term uses a Fast Fourier Transform based algorithm which gives good variogram reproduction for a wide class of variograms. If using the collocated cosimulation option with GRFS, the user will notice that there isn’t any systematic bias in the degree of variability of the simulated variable or in the correlation between the simulated variable and the secondary variable. For SGS, it is often found that the variance of the simulated primary variable is systematically different to the desired input variance. In the typical case where the secondary variable is smoother than the primary (often the secondary variable is a smooth seismic data volume), then SGS simulations will generally have higher variability than expected. Furthermore, the calculated correlation between the simulated primary variable and the secondary variable is not equal to the input correlation. This is a problem associated to the sequential nature of SGS. Within Petrel’s GRFS there is a mechanism to overcome such a bias, called the ‘Variance Reduction Factor’, which can be used to partly remove the bias. This is no longer necessary with GRFS. Page 5 The Geomodeling Network – Sponsored by Blueback Reservoir
  6. 6. The Geomodeling Network Newsletter March 2009 Another nice feature implemented for the GRFS is the fast collocated cosimulation. This is based on a new algorithm that extends a well known decomposition from the literature (e.g. Chiles and Delfiner, Geostatistics, Wiley, 1999). This decomposition states that collocated cokriging can be split into a kriging that is done once and a simple Bayesian cokriging update. We have further developed this by coupling it with a correctly chosen unconditional cosimulation of primary and secondary variables. It can be shown that this gives an exact collocated cosimulation. Updating to try a new correlation between primary and secondary variables is quite fast, so this has been implemented on a slider bar within Petrel so that the modeler can interactively see the results when changing the correlation (Figure 1). For the 3 million cell model mentioned above, the updating takes about 0.2 seconds so is fast enough to work on the slider bar. Secondary property = porosity cc = 0.85 Permeability models using cc = 0.15 GRFS with cosimulation Figure 1 – Using the new slider bar available for cosimulation with GRFS, it is possible to change the correlation coefficient (cc) and see the results on the fly in visualization windows. Page 6 The Geomodeling Network – Sponsored by Blueback Reservoir
  7. 7. The Geomodeling Network Newsletter March 2009 Also new in Petrel 2009 is the ‘layer declustered search’ option, which is used in the kriging component of the Gaussian simulation (thus also present for the kriging method). When this is active, it ensures that the when the kriging algorithm is searching for nearest neighbours of a cell which is to be kriged, it preferentially searches for neighbours in the current layer and then progressively for neighbours in nearby layers. If selected, this overrides the default mechanism which searches for neighbours according to variogram weighted distance. The primary application of this is when the variogram exhibits a long correlation in the vertical direction. In this case, the standard search would tend to find many highly correlated neighbours along vertical, or near vertical wells. This situation, when many of the data used for kriging are highly correlated between themselves, is similar to a situation in standard regression theory called collinearity. A typical solution used for kriging is to perform a declustering of the data and to choose neighbours which are less well correlated between themselves. The layer declustered search is a simple but often effective method to perform such a declustering in the case of near vertical wells with a long vertical range. The effect is that a better spread of neighbouring data, with less correlation between one another are used for the kriging, eliminating common artifacts generated by the traditional search methods used in the market (Figure 2). Keeping long vertical variogram range Applying layer declustered search Applying layer declustered search Figure 2 – A very simple example showing a kriged porosity model using three wells. Left: common kriging artifacts are due to a long vertical variogram range Right: layer declustered search has been applied, eliminating the artifacts. Page 7 The Geomodeling Network – Sponsored by Blueback Reservoir
  8. 8. The Geomodeling Network Newsletter March 2009 Another expert option for kriging and GRFS is the ‘approximate search’, which provides a search algorithm that can often be substantially faster than the standard search algorithm. It is however not as accurate and must be used with some care. A typical application will be when used to create many realizations for kriging or Gaussian simulation. The user should test that the fast search is giving results of acceptable quality on a trial realization. If it works well for one realization then it will work just as well for all realizations using the same parameters. So when, for a choice of kriging parameters and neighbourhood size, it is deemed to be working acceptably, this option can be switched on for the time consuming activity of generation of many realizations. Finally the ‘factor of simulation extent’ is a variable associated with the unconditional simulation. When the range of the variogram becomes longer than the sides of the model, the Fast Fourier Transform based model will not give a good reproduction of the variogram (due to aliasing). This can be improved by simulating on a larger volume and then ‘cutting out’ the region of interest. The factor of simulation extent can be used in such a case. Typically the value of 1 will be good enough, but if the correlation length becomes long, then it may need to be increased to a length of 2 or 3. Very high values can cause memory problems for the machine. It should be noted that there is little reason for using correlation lengths much longer than the extent of the field as this type of low frequency variability is usually better treated as a trend. Schlumberger Information Solutions strongly suggest Petrel geomodelers to start using the new GRFS in workflows where SGS is usually applied. In large grids and/or in an uncertainty study context, if running various realizations of petrophysical properties, a great time gain will be observed, as well as a visible improvement in achieving the desired distribution statistics. An example comparing SGS and GRFS results on volume distribution We now look at an example which shows that GRFS does a better job at modeling the uncertainty in the total pore volume of the reservoir than SGS. In a test project with a regular grid of 90x90x200=1.62 million cells of 100 x 100 x 1 meters size, 200 realizations were run on the porosity model, 100 of them using GRFS and the other 100 using SGS. Only the seed has been changed, all other parameters were kept the same. The variogram was spherical with ranges Page 8 The Geomodeling Network – Sponsored by Blueback Reservoir
  9. 9. The Geomodeling Network Newsletter March 2009 2000, 2000, 5 in the X, Y and Z directions respectively. The mean porosity was 0.15 with standard deviation of 0.05. Our objective is to calculate the distribution of pore volume for each realization and then look at the distributions of such volumes for both GRFS and SGS. The resulting distributions are shown in figure 3. There is clearly a difference between the GRFS case and SGS case. Which gives the better result? Well, if we knew the expected standard deviation of the distribution we could just check and see. To help us with this, we remember from basic statistics that if we have n independent points following the same distribution then the variance of the mean of those values is just variance of a single point divided by the number of points ( V = 2/N where V is the variance of the mean reservoir porosity, the variability being from one realization to the next). We have 1.62 million points and we know that the mean of the porosity distribution is 0.15 with standard deviation of 0.05. However, we cannot just choose N=1.62M because not all the What did the rock do all data are independent (the resulting simulation is not just a pure nugget effect or day? Nothing..... white noise simulation so the values are correlated to one another). Roughly speaking we can consider points to be independent of one another when they ......I’ll get my coat! are separated by a distance equal to the range of the variogram. More accurately there is a known method in geostatistics for calculating the approximate number of truly independent points and then we can use that formula. It is called the method of integral range. We won’t go into the details here (see Lantuejoul, C., Ergodicity and Integral Range, Journal of Microscopy, 161(3)) but the integral range for a spherical variogram is A = a3 where a is the range of the variogram and the number of equivalent data is then N = V/A where V is the bulk rock volume of the reservoir. In this case we find that N=1600 approximately. We can then use the formula V = 2/N to calculate the variability we might expect over the reservoir volume. This gives the standard deviation V=0.00125. In a normal distribution, the size of the 95% confidence interval is twice the size of the standard deviation. Combining these results we should get 95% of our realizations having a mean porosity for the total reservoir of between 0.15 – 2*(0.00125) and 0.15 + 2*(0.00125), that is in the interval [0.1475,0.1525]. Since the total rock volume of the reservoir is (1.62x106)*100*100*1 = 16.2x109 m3 (number of cells multiplied by volume of cell), then the expected range of pore volumes is approximately [2.389x109, 2.471x109]. Looking at the results of figure 3 we can see that the 100 realizations of the GRFS are consistent with this estimate while the results from SGS show considerably more variability than one would expect from the theory. The following table gives a resume of the results: Page 9 The Geomodeling Network – Sponsored by Blueback Reservoir
  10. 10. The Geomodeling Network Newsletter March 2009 Lower 95% conf interval Upper 95% conf interval Theoretically correct result 2.389 2.471 GRFS – observed result 2.386 2.482 SGS – observed result 2.350 2.502 Table 1. Confidence Intervals for the Total Pore volume variation for the reservoir. 9 3 Results are in units of 10 m . Overall, this shows that the GRFS simulation gives results that are more consistent, in terms of total pore volume modeled, with the information used to develop the model (in this case the variogram, mean and standard deviations of any well data). This becomes especially important in the case where we are conditioning to well data where the GRFS does a better job of modeling the expected variability around the distributions of porosity observed in the wells. Page The Geomodeling Network – Sponsored by Blueback Reservoir 10
  11. 11. The Geomodeling Network Newsletter March 2009 Figure 3 – Above: pore volume distribution after running 100 porosity realizations using SGS. Below: pore volume distribution after running 100 porosity realizations using GRFS. “It was with unalloyed The histogram for GRFS is less spread than for SGS, because SGS tends to give higher Career Networking pleasure that I became variance results than the one from the input distribution (in this case higher porosity variance, hence higher pore volume variance). aware that a vigorous earthquake was in progress.” 3. Geology & Technology -G.K. Gilbert on the 1906 San Simon Haworth – Nexen Francisco earthquake. Have you ever wondered what it might be like working in an oil company in 2025? Will we still be working with computers and bulky, costly computer screens? What if desks were your screens? And all you had was an internet connection? There are many more questions like this, but if I wrote them all down it wouldn‟t make for an enthralling article. I‟m an avid believer that one day, in the not so distant future, we will be working, in fact geomodelling, on the walls of our office. Not just by hanging a plasma screen on it, but by interacting with the wall itself. Consider yourself interacting with digital experiences that move beyond digital tradition, that blur the boundaries between art and science, and transform social assumptions. We are already in an era where current technology offers insights into interactive techniques, projects that explore science, high-resolution digital-cinema technologies, and interactive art- science narrative. Most people have seen Minority Report- a Steven Spielberg special in which cyber cop Tom Cruise manipulates wall-sized displays powered by gesture recognition, and seamless information convergence: it‟s the stuff that interface designer dreams are made of. So how did Tom Cruise get such a nice set up? It turns out that Microsoft Research, MIT, and several design shops had a say in the interface designs found in the film. Page The Geomodeling Network – Sponsored by Blueback Reservoir 11
  12. 12. The Geomodeling Network Newsletter March 2009 Why did the biker carry a large piece of an extrusive, pyrclastic, igneous rock composed chiefly of volcanic ash as on his motorcycle? Hand and touch screen recognition devices already exist but how can we get involved? So, if the big boys are cleverly adapting and developing the hardware, He wanted to act tuff. which oil service companies are going to get their mitts on it first? Cost is likely to be an issue- nobody wants to venture into a novel arena because there is some likelihood the adaptation and, more importantly, uptake could flop. On the other hand, it could be a resounding success- „Qui Audet Adipiscitur („He who Dares Wins‟). The willingness to embrace change is heavily dependent on the decision makers and their own visions for the future. The demography of the industry is changing so rapidly that geoscience and engineering professionals are taking on more and more responsibility at a young age. It is seemingly more possible that the fully loaded virtual office will become a reality therefore allowing the industry to leverage the experience of others from the comfort of their own home. Less office space in prime locations means lower overheads. Meetings will take place in your living room with the aid of holographic projections (ref. Cisco‟s Page The Geomodeling Network – Sponsored by Blueback Reservoir 12
  13. 13. The Geomodeling Network Newsletter March 2009 Telepresence) just like R2D2‟s relay of the all important message to Luke Skywalker in Star Wars. quot;...And yet it does move.quot; - Galileo (referring to the Earth) To sum up, the technology already exists- the software doesn‟t. I‟d like to see more of an uptake in the design and adaptation of the technology for the oil industry. Petrel, RMS and others are great tools- it‟s how we use them that matters. Mitch has kindly offered to publish this article so that I can gauge interest amongst other Geoscience professionals and Software Developers alike who share my vision for taking this further. My initial thoughts are to bring together software, technology and geology professionals in a combined Special Interest Group with a view to development of bigger concepts and product development in an arena which is under-explored and under- funded. Please email me with any comments, thoughts and ideas. There are numerous societies with SIGGRAPH (Special Interest Group on GRAPHics and Interactive Techniques) being a key organisation. For anyone interested, this year‟s conference is being held in New Orleans (3rd-7th August 2009). Further details can be found below “Dreams will get you nowhere; a good kick in the pants will take you a long way”. Page The Geomodeling Network – Sponsored by Blueback Reservoir 13
  14. 14. The Geomodeling Network Newsletter March 2009 4. High Frequency Characterization of an Outcropping Q: What is the Sinuous Leveed-Channel Complex, Dad Sandstone difference between a Member, Lewis Shale, Wyoming (Abstract only) geologist and a chemist? Staffan Van Dyke – Nexen A: A chemist will drink This paper presents the results of data collection, analysis and integration to build a 3D geological model of an outcropping leveed-channel complex. Data is anything that is from more than 120 standard measured stratigraphic sections, behind-outcrop distilled. drilling/logging/coring, ground-penetrating radar and electromagnetic induction surveys and 2D shallow seismic reflection acquisition. A geologist will drink This leveed-channel complex, which is part of the Dad Sandstone Member of the anything that is Cretaceous Lewis Shale, Wyoming, consists of ten channel-fill sandstones, fermented.... confines within a master channel. The complex is 67m (200ft) thick and 500m (1500ft) wide and has a net sand content of approximately 57%. Individual channel-fills are internally lithologically complex, but in a systematic manner which provides a means of predicting orientation and width of sinuosity. Although it has not been possible to completely document the three dimensionality of the system, the 3D model that has evolved provides information on lithologic variability at scales which cannot be verified from conventional 3D seismic of subsurface analog reservoirs. This vertical and lateral variability can provide realistic lithologic input to reservoir prediction. An outcome of this study has been knowledge gained of the extent of manipulation required to obtain the spatially correct geometry and architecture of strata when integrating outcrop and shallow, behind-outcrop data sets. If anyone is interested in reading the complete paper, simply click on the link below and find the presentation called “GCS-SEPM Lewis Shale” _app_id=7544200&_applicationId=1200&appParams=%7B%22from%22%3A%22 owner_network_slideshows_home%22%2C%22view%22%3A%22canvas%22%2C %22page%22%3A%22owner_minifeed%22%7D&_ownerId=8140385&completeU rlHash=GMNx 5. The Blueback Toolbox Blueback Reservoir ( (Full download instructions for the Blueback Toolbox can be found at the end of this article) The latest software product from the software development team in Blueback Reservoir is our new Toolbox. The Blueback Toolbox is a set of smaller Petrel plug-ins for solving specific problems not supported in standard Petrel. Page The Geomodeling Network – Sponsored by Blueback Reservoir 14
  15. 15. The Geomodeling Network Newsletter March 2009 The aim with the Toolbox is to facilitate faster workflows and to provide Petrel users with functionality not already in available in Petrel. The current Toolbox is available for FREE – just send us an email with your details. The content of the Toolbox is increasing all the time as we keep adding new plug-ins to it. Most of the plug-ins have been developed upon direct requests from Petrel users, and in most cases resulting in functionality we make available to all Toolbox users. The Toolbox functionality as of 1 March’09: Make Cube Generates a seismic cube data object from a point data set. Specify resolution, min/max values and interpolation algorithm. Import/Export Support for new data formats. Export of navigation data for a seismic survey. Import of IESX interpretations as points. Import 3D seismic interpretations from a general ASCII format. Import ASCII files into a seismic cube. Sample Attribute Sample points from a seismic cube. Using a point set to sample values from a seismic cube. The sampled values will be appended as an attribute to the point set Page The Geomodeling Network – Sponsored by Blueback Reservoir 15
  16. 16. The Geomodeling Network Newsletter March 2009 Comments to data objects Easy addition of comments to the Info tab in the Settings dialog of a selected data object. No need to open the Settings dialog “The elements that unite to make the Grand Extracts points from cube Creates a point set from a seismic cube. One point per sample in the cube. Canyon the most sublime Limited by a top and bottom surface spectacle in nature are Created point set located in the same survey folder as the input cube multifarious and One of the key things about this Toolbox is that we at Blueback see it as an exceedingly diverse.” evolving set of tools. As such, the contents are expected to change quite dramatically over time when new functionality is requested and added. -John Wesley Powell For this reason it is important that all users of the Toolbox provide feedback to Blueback as without this feedback we will not be in a position to make any changes or amendments. We would therefore like to know if you find the functionality useful or whether you would like to see any tweaks made to what is already there. Also, we would like to know if you have any suggestions for any additional functionality that you would like us to add to the Toolbox, which would benefit the Petrel user community. If one of these suggestions makes it into the official Blueback Toolbox then I will happily send that member a Blueback iPod. How to download the Blueback Toolbox The Toolbox is now on our FTP site. Page The Geomodeling Network – Sponsored by Blueback Reservoir 16
  17. 17. The Geomodeling Network Newsletter March 2009 User: TOOLBOX Passwd: xxToolbox2009 There are 3 files there: 1 –“ TOOLBOX 1.1”. This is the installation file if you are running Petrel 2008 on XP. 2 – “TOOLBOX 1.1 2009.1”. This is the installation file if you are running Petrel 2009 on Vista or XP 32 bit. 3 – “TOOLBOX 1.1 2009.1”. This is the installation file for those running Petrel 2009 on Vista 64 bit. Download the file you need, unzip it and run the installation. Then start Petrel and open the Blueback License dialog from the HELP pulldown menu. To activate the Toolbox – you must send to the COMPUTER CODE. This is found if you click the Manage Licenses button. This download information can be forwarded to anyone interested in taking a look at the Toolbox. Geo2Flow Dan O’Meara For those of you who have been a member of the Geomodeling Network for a wee while you will probably recognise the name Dan O’Meara. Dan is the chap who has contributed some very eloquent articles for discussion on our very informative discussion page. To prove to you all that Dan does not spend all of his time posing technical questions to our network and that he does have an actual day job, Dan has contributed an excellent article on Geo2flow. Geo2Flow is a software product developed by O‟Meara Consulting who have gained respect for developing leading-edge, interdisciplinary tools that “raise the bar” technically in the arena of reservoir characterization. Geo2Flow uses patented technology for identifying reservoir compartments, for calculating 3D permeabilities that are consistent with saturation logs and for ensuring that 3D saturations match their corresponding logs exactly. Integrating Geo2Flow into your workflow ensures that your method for estimating reserves is “best in class” Page The Geomodeling Network – Sponsored by Blueback Reservoir 17
  18. 18. The Geomodeling Network Newsletter March 2009 Page The Geomodeling Network – Sponsored by Blueback Reservoir 18
  19. 19. The Geomodeling Network Newsletter March 2009 Page The Geomodeling Network – Sponsored by Blueback Reservoir 19
  20. 20. The Geomodeling Network Newsletter March 2009 Requests for the newsletter No5 The next newsletter is planned for a May 2009 release, so please send any articles to me at the following email address for inclusion ( Finally, please take advantage of the Geomodeling Network discussion board on LinkedIn to initiate comments on any Geomodeling subject of interest to you, or to respond to any of the articles in this newsletter – all I ask is that you respect other people’s opinions. Fin Page The Geomodeling Network – Sponsored by Blueback Reservoir 20