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SUMMARY:Dallas Geophysical Society Luncheon - November 2017
DTSTART;TZID=US/Central;VALUE=DATE-TIME:20171116T113000
DTEND;TZID=US/Central;VALUE=DATE-TIME:20171116T130000
DTSTAMP;VALUE=DATE-TIME:20170908T131153
UID:59b29719893aaa3344acd3fe
DESCRIPTION:Date: Thursday\, November 16\, 2017 Time: 11:30 am - 1:00 pm 
 Location: Denbury Resources\, 5320 Legacy Dr\, Plano\, TX Topic: Multi-
 Seismic Attributes Analysis and Production Integration in Unconventional 
 Plays - Workflow and A Case Study Speaker: Renjun Wen Bio: Renjun Wen is 
 the founder of Geomodeling Technology Corp\, an international geosciences 
 software company in Calgary\, Canada. He holds a PhD in Petroleum Geology 
 from Norwegian University of Science and Technology (NTNU)\, Norway 
 (1995)\, and a Bsc in Petroleum Geology from Jianhan Petroleum Institute\,
  China (1983). From 1983 to 1987\, he worked as an exploration geologist 
 in CNPC. He worked for Statoil Research Center as a research consultant 
 and this work\, together with his post-Dr. research\, formed the basis to 
 found Geomodeling in later 1996 when he moved to Calgary\, Canada. He has 
 published papers in the fields of reservoir modeling\, sub-seismic fault 
 modeling\, geostatistical application in image processing\, and seismic 
 attribute analysis. Since 2000\, Dr. Wen has collaborated with major 
 international oil companies to develop innovative reservoir modeling 
 software in the SBED consortium. He is a registered Professional Geologist
  in Alberta (APEGGA)\, and members of SEG\, CSEG\, CSPG\, AAPG\, SPE\, 
 EAGE\, and IAMG. Abstract: A key question to be addressed in applying 
 seismic attribute analysis to the exploration and exploitation of shale 
 and tight sand plays is whether the analysis can help explain the large 
 variability of production among horizontal wells in the same play. The 80 
 to 20 &ldquo\;rule&rdquo\; is often observed in these plays\, whereas 
 about 80% of the production is contributed by 20% of the wells. Even 
 though the advancement in well completion and horizontal drilling 
 technologies are major factors for the success of shale and tight-sand 
 plays\, variability of rock properties in the plays are believed to key 
 contributors to the production variability. The questions are: what are 
 these rock properties that are controlling the variation of the production
  and is it feasible to map the spatial variation of the key properties 
 before drilling. This talk will present two lines of thought in developing
  seismic attribute analysis workflows to map high productivity areas 
 (sweet-spots) in shale and tight-sand reservoirs. The first line of 
 thought is a prospecting workflow that is based on model-based attributes.
  The second line of thought is a forensic workflow that is based on data 
 integration. A case study of applying these two workflows in a shale gas 
 play will illustrate the strength and weakness in each workflow. In the 
 prospecting attribute analysis workflow\, we rely on seismic attributes 
 that have clear physical meanings\, which can be linked to rock properties
  through physical models. There are a variety of rock properties that are 
 regarded as influential to the productivity of shale and tight-sand 
 plays\, such as total carbon content\, in-situ porosity and permeability\,
  content of brittle minerals\, in-situ fracture density and orientation\, 
 local stress field\, etc. To map these rock properties\, a variety of 
 seismic inversion algorithms have been used to link these rock properties 
 and geomechanical properties\, notably\, Poisson ratio\, Young&rsquo\;s 
 modulus\, fracture density and orientation\, and 
 &ldquo\;brittleness&rdquo\; or &ldquo\;fracability&rdquo\; attributes. In 
 principle\, analyzing these seismic inversion attributes should lead to 
 mapping of &ldquo\;sweet-spot&rdquo\; before drilling\, such as in areas 
 of high fracability. The challenges in the prospective attribute workflow 
 is that how to calibrate these physical attributes. I&rsquo\;ll use the 
 data in a case study to illustrate pitfalls of using these inversion 
 attributes. In the forensic attribute analysis workflow\, we integrate all
  available seismic attributes with production\, drilling and completion 
 data. We do not assume any direct link between any seismic attribute and 
 rock properties or production potential. Instead\, we rely on historic 
 production data in the reservoir to reveal if there is any relationship 
 between production data and seismic attributes. The analysis of such a 
 type of relationship must also consider the influence of drilling and 
 completion parameters. We found that a neural-network derived non-linear 
 relationship often perform better than multi-variate linear regression. No
  single attribute is found to be able explain the spatial variability of 
 the production. But an integrated attribute through non-linear neural 
 networks clearly show patterns of sweet-spots that are consistent with the
  drilling results. Combining both types of seismic attribute analysis 
 workflows discussed above is a more pragmatic approach in practice. Using 
 these workflows together can help in reducing the uncertainty of mapping 
 &ldquo\;sweet-spot&rdquo\; and increase well productivity. 
LOCATION:Denbury Resources\, 5320 Legacy Dr\, Plano\, TX 75024\, USA
PRIORITY:5
URL:https://www.dallasgeophysical.org:443/events/dallas-geophysical-
 society-luncheon-november-2017
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