Changes

* Logistical considerations

* Logistical considerations

* Expected natural variation in surface measurements

* Expected natural variation in surface measurements

* Probable [[Signal to noise ratio|signal-to-noise ratio]]<ref name=ch18r26>Matthews, M., D., 1996, [http://archives.datapages.com/data/specpubs/memoir66/18/0243.htm Importance of sampling design and density in target recognition], in Schumacher, D., Abrams, M., A., eds., Hydrocarbon Migration and Its Near-Surface Expression: [http://store.aapg.org/detail.aspx?id=75 AAPG Memoir 66], p. 243–253.</ref>

* Probable [[Signal to noise ratio|signal-to-noise ratio]]<ref name=ch18r26>Matthews, M. D., 1996, [http://archives.datapages.com/data/specpubs/memoir66/18/0243.htm Importance of sampling design and density in target recognition], in D. Schumacher and M. A. Abrams, eds., Hydrocarbon Migration and Its Near-Surface Expression: [http://store.aapg.org/detail.aspx?id=75 AAPG Memoir 66], p. 243–253.</ref>

==Procedure==

==Procedure==

==Seeps==

==Seeps==

Oil and gas seeps, if present, are also valuable analogs because they permit direct correlation of seeping hydrocarbons with soil gas and fluorescence data as well as other microbial or geochemical data. Old producing fields may not provide good analogs since production and pressure decline may have reduced or even eliminated their surface geochemical expression.<ref name=ch18r15>Horvitz, L., 1969, Hydrocarbon prospecting after thirty years, in Heroy, W., B., ed., Unconventional Methods in Exploration for Petroleum and Natural Gas: Dallas, Southern Methodist Univ. Press, p. 205–218.</ref>

Oil and gas seeps, if present, are also valuable analogs because they permit direct correlation of seeping hydrocarbons with soil gas and fluorescence data as well as other microbial or geochemical data. Old producing fields may not provide good analogs since production and pressure decline may have reduced or even eliminated their surface geochemical expression.<ref name=ch18r15>Horvitz, L., 1969, Hydrocarbon prospecting after thirty years, in W. B. Heroy, ed., Unconventional Methods in Exploration for Petroleum and Natural Gas: Dallas, Southern Methodist Univ. Press, p. 205–218.</ref>

==Sample density==

==Sample density==

[[file:surface-geochemical-exploration-for-petroleum_fig18-4.png|300px|thumb|{{figure number|1}}Illustration of the value of geochemical grids over geochemical traverses for anomaly recognition. Copyright: Geo-Microbial Technologies, Inc.]]

[[file:surface-geochemical-exploration-for-petroleum_fig18-4.png|300px|thumb|{{figure number|1}}Illustration of the value of geochemical grids over geochemical traverses for anomaly recognition. Copyright: Geo-Microbial Technologies, Inc.]]

Defining background values adequately is an essential part of anomaly recognition and delineation; Matthews<ref name=ch18r26 /> suggests that as many as 80% of the samples collected be obtained outside the area of interest. This is a good recommendation for reconnaissance and prospect evaluation surveys. However, for very small targets such as pinnacle reefs or channel sandstones, optimum results are obtained when numerous samples are collected in a closely spaced grid pattern, (100–160-m sample interval or less) over the feature of interest.<ref name=ch18r41>Schumacher, D., Hitzman, D., C., Tucker, J., Roundtree, B., 1997, Applying high-resolution surface geochemistry to assess reservoir compartmentalization and monitor hydrocarbon drainage, in Kruizenga, R., J., Downey, M., W., eds., Applications of Emerging Technologies: Unconventional Methods in Exploration for Oil and Gas V: Dallas, Texas, Southern Methodist Univ. Press, p. 309–322.</ref>

Defining background values adequately is an essential part of anomaly recognition and delineation; Matthews<ref name=ch18r26 /> suggests that as many as 80% of the samples collected be obtained outside the area of interest. This is a good recommendation for reconnaissance and prospect evaluation surveys. However, for very small targets such as pinnacle reefs or channel sandstones, optimum results are obtained when numerous samples are collected in a closely spaced grid pattern, (100–160-m sample interval or less) over the feature of interest.<ref name=ch18r41>Schumacher, D., D. C. Hitzman, J. Tucker, and B. Roundtree, 1997, Applying high-resolution surface geochemistry to assess reservoir compartmentalization and monitor hydrocarbon drainage, in R. J. Kruizenga, and M. W. Downey, eds., Applications of Emerging Technologies: Unconventional Methods in Exploration for Oil and Gas V: Dallas, Texas, Southern Methodist Univ. Press, p. 309–322.</ref>

==Example==

==Example==

[[Category:Predicting the occurrence of oil and gas traps]]  

[[Category:Predicting the occurrence of oil and gas traps]]  

[[Category:Surface geochemical exploration for petroleum]]

[[Category:Surface geochemical exploration for petroleum]]