/* Please refer to readme.html for full Instructions Text[...]=[title,text] Style[...]=[TitleColor,TextColor,TitleBgColor,TextBgColor,TitleBgImag,TextBgImag,TitleTextAlign,TextTextAlign, TitleFontFace, TextFontFace, TipPosition, StickyStyle, TitleFontSize, TextFontSize, Width, Height, BorderSize, PadTextArea, CoordinateX , CoordinateY, TransitionNumber, TransitionDuration, TransparencyLevel ,ShadowType, ShadowColor] */ var FiltersEnabled = 1 // if your not going to use transitions or filters in any of the tips set this to 0 Text[0]=["Me Email","Click here to send me an email "] Text[1]=["Home Page","Click here to go to my Web site."] Text[2]=["This is the title","Well How do you find this Tip message to be?"] Text[3]=["Right","This tip Is right positioned"] Text[4]=["Center","This tip Is center positioned"] Text[5]=["Left","This tip Is left positioned"] Text[100]=["John Anderson, Maurice Ewing Professor of Oceanography, Rice University","With the recent attention given to global warming, many studies have focused on the incipient rise in sea level and its potential impact on coastal systems. Most studies have focused on the impact of increasing rates of sea-level rise on coastal systems. However, coastal systems are dynamic and some of the most dramatic changes occur as a result of a combination of sea-level rise and other factors such as climate change and the flooding of antecedent topography. The purpose of this study was to document the changes that occurred within the Corpus Christi Bay and Mustang Island coastal system over the last 10 ka, a time period that is known to have experienced varying rates of sea-level rise and climatic changes.

Over 400 kilometers of high-resolution seismic data and 53 sediment cores up to 30 meters in length were collected from the bay, and nine long sediment cores were collected through the barrier island. The overall landward migration of the bay during the Holocene sea-level rise was punctuated by four major flooding events when significant re-organization of bay environments occurred. These included the onset and termination of bayhead delta and tidal delta formation, and widespread destruction of oyster reefs. The flooding events occurred at 9.6, 8.0, 4.8 and 2.6 ka and lasted only a few centuries. The causes of these flooding events include flooding of relatively flat antecedent topography (fluvial terraces) and changes in climate that led to major reductions in sediment supply.

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"] Text[101]=["Bill Fahmy Exxon Mobil Exp. Co. 'DH/AVO Best Practices'","In 1997, ExxonMobil developed a company wide best practice to evaluate and understand the risk for DHI-dependent plays. Within this best practice, a robust controlled amplitude/phase processing strea, rigorous analysis, and a calibrated DHI-rating system using both data quality and observed DHI characteristics were designed. The methodology is not dependant on evaluating just a single DHI attribute; e.g. AVO, but on a multitude of seismic characteristics. The rating system provides a consistent approach for evaluating DHIs and data quality and integrating it with risk analysis. Two case histories from different geologic and business settings illustrate the application of the best practice. The data used in both cases were processed with the prescribed controlled amplitude, controlled phase stream which was a key factor for our analysts.

The first example is from an exploration setting. The example shows how applying best practices can help identify the risks correctly and set expectations prior to drilling the fist well in frontier basin. By using our best practice methodology the main risk identified here was how low gas saturation, even though no low gas saturation sands had previously been encountered in the area. Subsequent drilling confirmed this prediction.

The second example is from a development setting. This example illustrates application of an emerging technology, Spectral Decomposition to a high-grade an anomaly not observed on traditional seismic data. Identification of the anomaly with the correct DHI attributes enabled us to successfully position and drill a key development well. The well results helped us gain confidence in the reserve estimate for the field and develop an optimized depletion plan.

In summary, for each case history we will present our pre-drill analysis and predictions and share the learnings from the post well drilling results. Also, as an audit of the process, we will show the overall statistics of how the best practices have fared since its implementation."] Text[102]=["Cindy Yeilding - IS THE WORK STATION KILLING GEOLOGY","What a question! Of course, the resounding answer to this question is 'NO'. Access to digital data, visualization tools and interpretation software provides the geoscientist with the ability to visualize, display, and capture interpretations faster and more robustly than ever before. We can optimize end enhance display parameters, store and scroll through multiple datasets, transfer large volumes of data in seconds and 'share' interpretations across sites in ways we could only dream of a decade ago.

But you’re still reading this overview, so perhaps we have touched a sensitive element here. With the plethora of tools and views available for geoscientists, might we sometimes lose track of some of the basics? A few questions for us to explore...
So, what can we do to assure that we are honoring our data appropriately and accurately reflecting data and uncertainty? Reminding ourselves of a few simple practices can make a huge difference in underpinning the highest quality integration and interpretations.

Tried but true methods including knowing your data quality, utilizing paper & pencils, asking for help and ideas, carrying multiple models and- most important- always testing interpretations against the first principles of geoscience are keys to success.

Digital data and software/hardware available today are more powerful and provocative than ever before. When combined with the best quality data (or understanding of the data quality and its limitations) and the best knowledge, we can generate better geoscience than ever before."] Text[103]=["Mike Lucente - ANATOMY OF A NEW FIELD DISCOVERY","LMP Petroleum successfully explored for and discovered North Los Torritos Field; EUR 45 BCF gas equivalent. The area was mature; land problems were severe; well costs were high; and analogous fields were marginal. What a perfect place for a discovery! (Note: this presentation is available on D VD from the SIPES Foundation Video Film Library).

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"] Text[104]=["George E. Tanner and Paul Goranson - Newest in situ Uranium Mine in South Texas","The Alta Mesa Project
The First Year of Commercial Operations of the North America’s Newest Uranium Mine

Since the mid 1980’s, the uranium industry, particularly in the United States of America, has been in a significant decline. The result of that decline was excess inventory and low commodity prices. Until 2003, the domestic industry suffered continued retraction in production and expenditures to the extent that there was an exodus of trained personnel to other industries and careers. Starting in 2003, and rapidly accelerating in 2004, there was a sharp increase in activity in the uranium industry, and several properties that were known to be amenable ISL uranium recovery were looked at again to meet the need for uranium and respond to increasing prices. The Alta Mesa Project, located in Southern Brooks County, Texas, fits this profile.

The Alta Mesa Project was discovered in mid 1970’s, and some exploration drilling and monitor well installation was started in the 80’s and early 90’s. However, due to low uranium prices, the project was not developed. Mesteña Uranium LLC continued licensing and permitting program in 1999 and carried that effort through 2004. In late 2004, development activities started, and construction of the production facilities started in January 2005. Despite challenges due to three hurricanes, short supply of materials, equipment, and trained personnel, the Alta Mesa Project started up as planned in October 2005.

The mining operation uses the in-situ leach recovery process that eliminates the need for large excavations, large milling facilities and tailings disposal. The in-situ recovery process utilizes the geochemistry of uranium in its natural geological environment for the extractive process. In its natural state, uranium exists in a solid reduced form (U4+), and to extract the uranium, the in-situ recovery process uses oxidized injected water to convert uranium to its soluble oxidized state (U6+). Using a series of injection and production well patterns, the uranium bearing water is collected and transported to an ion-exchange plant where the uranium is stripped before the water is re-injected into the ore body as part of the recovery process. The uranium is then concentrated from the ion exchange beds and converted to a dry solid uranyl peroxide powder for transport to the conversion facility.

After one year of commercial operation, the Alta Mesa Project recovered its first 1,000,000 lbs of uranium and placed Mesteña Uranium LLC as the number one uranium producer in the State of Texas and the number two uranium producer in the United States."] Text[105]=["Alan R. Huffman PhD - Recent Advances and Future Challenges in Pore Pressure Prediction from Geophysical Data","Pre-drill pressure prediction using geophysical data and methods has historically been done using very simple models and has been restricted by overly simplistic estimates of the Earth’s velocity field. The advent of the effective stress concept and the pressure prediction methods that developed from that concept led to a much-needed inclusion of fundamental physics into the art of pressure prediction. Geopressure prediction techniques have started incorporating more sophisticated velocity methods such as AVO-based phase mismatch algorithms, tomography and pre-stack inversion. These technologies allow the geophysicist to obtain higher resolution estimates of the velocity field in the subsurface that can significantly improve the results of pressure prediction. These technologies permit more robust analysis of P-wave velocities in the presence of contamination from hydrocarbon effects and non-clastic rocks that have been a problem in the past.

In recent years, methods have been developed to enable robust pressure prediction in the presence of multiple pressure mechanisms including undercompaction, unloading processes (secondary pressure mechanisms) and at great depth, the onset of secondary chemical compaction. These models utilize geological and geophysical information to constrain the calibration models and the depths at which they must be applied to develop a multi-layer pressure calibration model that will accurately predict pressures for prospect-level analysis and pre-drill prediction. These models are then integrated with the velocity field and the geological and geophysical information to predict pore pressures and fracture pressures at greater depths than have been previously feasible. This methodology has been tested in multiple basins and has been proven to be effective in helping drilling engineers improve well performance through more effective mud and casing program designs that significantly reduces well costs and rig time. The methodology also provides a greatly improved feedback loop for basin modeling as it can predict reasonably accurately the current pressure regimes in the subsurface under a wide range of physical conditions that can be used as an end-constraint on basin models."] Text[106]=["Frank Cornish - Discovery and Development of the Lower Wilcox Speaks Field Lavaca Cty, Texas","The United Oil and Minerals #1 Pilgreen discovery in January, 1996 opened up a significant Lower Wilcox play throughout Lavaca and Colorado Counties, TX. The play concept involved finding undrilled Lower Wilcox structures beneath Upper Wilcox dip trending structural axes. At the Southwest Speaks prospect a large shallow Upper Wilcox high-side fault trap had been drilled by three unsuccessful wells, all of which had tested gas from different Lower Wilcox sands. Adjacent downthrown Lower Wilcox production was noncommercial, and the primary target sands had never produced anywhere in Lavaca or Colorado counties.

Production from Lower Wilcox sands at Southwest Speaks will exceed 230 BCFG from 10 different sands. The main pays are the Roeder (a misnomer), Rainbow, and Magnolia. The single best well (Eaves #1) has produced 16 BCF from the Rainbow which is the best zone with over 84 BCFG produced (10/2006). The Rainbow Sand includes two upthrown fault closures, the largest of which covers 1490 acres and has over 515 feet of column.

The original prospect was developed on 2D data. Five wells were drilled before 3D seismic over the field was completed in 1997, finding the absolute structural high in an unexpected area. The data was part vibroseis and dynamite acquired at different times. Fault shadows caused sag and relative amplitude problems.

All wells required fracture treatment and some had second fracs which prolonged their life. Lower Wilcox gas had varying amount of H2S and CO2 requiring treatment for sales. Generally speaking, the highest wells are the best producers with the best porosity and permeability, but they are off structure 'sweet spots' in the Rainbow and Simpson sands.

Regional geology prior to 1995 showed a lack of production along the Lower Wilcox Fault Trend between Dry Hollow Field and Provident City Field in Lavaca County. At Southwest Speaks the best production came from Lower Wilcox sands that had not produced in the county. Explorationists should always be looking for new reservoirs and not be led only to those prospects with nearby look-alikes in the same target sands."] Text[107]=["Mr. Edward Feragen - South Texas Sub-Regional Evaluation: Area-Wide Integrated Structural and Stratigraphic Framework of the Frio and Vicksburg Yields New Plays and Leads","ExxonMobil recently completed an area-wide evaluation of the South Texas Oligocene Frio and Vicksburg Formations. This evaluation resulted in the identification of new plays and leads within this mature gas-producing region The foundation of the evaluation was the development of an integrated structural and stratigraphic framework. This framework was developed through integrated interpretation of extensive well, 2D and 3D seismic,and biostratigraphic data.

Due to the influence of growth faults during a time of high sedimentation rates, the Frio and Vicksburg stacking patterns generally do not reflect the global sea level curves for most 3rd-order assemblages. The extensive use of biostratigraphic data, integratd with well and Growth faults in the early Oligocene (Lower Vicksburg) were initiated by loading and subsequent failure of the Eocene (Jackson) shelf margin. The growth fault systems continued to be a primary control on sedimentation through the Vicksburg and Frio. Mapping indicates that throughout the Frio and Vicksburg sand-prone delta systems are spatially related to active, age-equivalent fault systems. Additional prospectivity was identified through recognition of sand-prone deltaic assemblages associated with growth faults downdip of shaled-out packages, emplaced via bypass over portions of the shelf.

Detailed EOD evaluations led to the identification of Frio upper slope sands, which may offer a new play type in South Texas. These fan deposits appear to be fed by large (>500 ft. deep), updip submarine canyons."] Text[108]=["Planting the Seeds of Geologic Curiosity","Jarad Cummings, a King High School graduate, came up to me today (7/31/07). He remembered me from my speech at the Ortiz Center in June that I gave to all the High School graduates, and he wanted to tell me that he changed his major to Geology because of it! He has registered for Geology classes at DelMar and then plans to finish at TAMUCC. I am very proud of that, and I am proud that when he saw me again he told me. This is what I am talking about for us all to do 'Plant the Seeds of Geologic Curiosity' -- It will work to inspire new geologists."] Style[0]=["white","black","#000099","#E8E8FF","","","","","","","","","","",200,"",2,2,10,10,51,1,0,"",""] Style[1]=["white","black","#000099","#E8E8FF","","","","","","","center","","","",200,"",2,2,10,10,"","","","",""] Style[2]=["white","black","#000099","#E8E8FF","","","","","","","left","","","",200,"",2,2,10,10,"","","","",""] Style[3]=["white","black","#000099","#E8E8FF","","","","","","","float","","","",200,"",2,2,10,10,"","","","",""] Style[4]=["white","black","#000099","#E8E8FF","","","","","","","fixed","","","",200,"",2,2,1,1,"","","","",""] Style[5]=["white","black","#000099","#E8E8FF","","","","","","","","sticky","","",200,"",2,2,10,10,"","","","",""] Style[6]=["white","black","#000099","#E8E8FF","","","","","","","","keep","","",200,"",2,2,10,10,"","","","",""] Style[7]=["white","black","#000099","#E8E8FF","","","","","","","","","","",200,"",2,2,40,10,"","","","",""] Style[8]=["white","black","#000099","#E8E8FF","","","","","","","","","","",200,"",2,2,10,50,"","","","",""] Style[9]=["white","black","#000099","#E8E8FF","","","","","","","","","","",200,"",2,2,10,10,51,0.5,75,"simple","gray"] Style[10]=["white","black","black","white","","","right","","Impact","cursive","center","",3,5,200,150,5,20,10,0,50,1,80,"complex","gray"] Style[11]=["white","black","#000099","#E8E8FF","","","","","","","","","","",200,"",2,2,10,10,51,0.5,45,"simple","gray"] Style[12]=["white","black","#000099","#E8E8FF","","","","","","","","","","",200,"",2,2,10,10,"","","","",""] Style[100]=["white","black","black","#E8E8FF","","","","","","","","","","",700,"",2,2,-350,10,51,1,0,"",""] applyCssFilter()