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==

Use the table below as a guide for designing a surface geochemical survey.

Use the procedure below as a guide for designing a surface geochemical survey.

# Research the method(s); investigate contractor, past clients.

# Use more than one [[Selecting a surficial geochemistry survey method|geochemical survey method]] when possible.

# Be guided by past experience in the basin or exploration trend.

# Base the geochemical sample program on the target's size, geology.

# Conduct a calibration survey(s) over an analog field or recent discovery.

# Integrate available geological and geophysical data to achieve the most meaningful results.

| Research the method(s); investigate contractor, past clients.

| Use more than one [[Selecting a surficial geochemistry survey method|geochemical survey method]] when possible.

| Be guided by past experience in the basin or exploration trend.

| Base the geochemical sample program on the target's size, geology.

| Conduct a calibration survey(s) over an analog field or recent discovery.

| Integrate available geological and geophysical data to achieve the most meaningful results.

==Sample locations==

==Sample locations==

==Analogs==

==Analogs==

Whenever possible, it is advisable to acquire surface geochemical data over a nearby geologic analog or recent discovery. A dry hole can be as valuable an analog as a recent discovery if the well penetrated the target horizon and found it water wet (or lacking the reservoir facies).

Whenever possible, it is advisable to acquire surface geochemical data over a nearby geologic analog or recent discovery. A [[dry hole]] can be as valuable an analog as a recent discovery if the well penetrated the target horizon and found it water wet (or lacking the reservoir facies).

==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==

Hydrocarbon microseepage data, whether soil gas or microbial or other geochemical measurements, are inherently noisy and require adequate sample density to distinguish between anomalous and background areas. Matthews<ref name=ch18r26 />) reviews the importance of sampling design and sampling density in target recognition. He states that undersampling is probably the major cause of ambiguity and interpretation failures involving surface geochemical studies.

Hydrocarbon microseepage data, whether soil gas or microbial or other geochemical measurements, are inherently noisy and require adequate sample density to distinguish between anomalous and background areas. Matthews<ref name=ch18r26 /> reviews the importance of sampling design and sampling density in target recognition. He states that undersampling is probably the major cause of ambiguity and interpretation failures involving surface geochemical studies.

==Recognizing anomalies==

==Recognizing anomalies==

[[file:surface-geochemical-exploration-for-petroleum_fig18-4.png|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]]