How can I find out about the validity and effectiveness of a proposed SGE method?

How can I evaluate survey results in a given work area?

I read about the claim of reservoir gases migrating through several thousand feet of solid salt/anhydride cap rock to leave a seep signal at the surface. Is this statement correct?

I am confused about statistical statements – often reported in magazines and journals – on "70+% exploration success".

Would you recommend drilling any SGE anomaly on its own merits?

Some service companies report "success probabilities". Is this of any value?

Is a SGE anomaly related to field size or economics?

Some of the service companies put an enormous emphasis on their ultra-high analytical sensitivity. Is this ultra-high sensitivity a definite advantage for SGE?

On CTI's website, the knowledge of the origin of surface gases is stressed; why should I be interested in this, in particular since other methods are offered to record seepage manifestations?

What is your opinion on airborne detection systems?

I read about the poor reproducibility of soil gas data in repeat surveys. So, why should anyone use instant soil gas surveys?

What is the advantage of time-integrative versus instantaneous sampling?

Is contamination a problem in gas surveys?

What is your opinion on "pattern learning data sets" involving hundreds of compounds?

One approach we heard about emphasizes the huge soil gas volume (1 liter) taken from the soil. Is there an advantage to this?

Why did you select soil gas surveys as your preferred SGE method?

What are microbial surveys?

Why are you not offering a microbial survey technique?

Can microbial surveys be used for dry reservoir gas evaluations?

Is there room for improvements on microbial techniques?

What is the GEL technology?

How does the GEL technique report the effectiveness in the search for oil and gas?

Can you predict the depth target from GEL data?

Sometimes, several production horizons are stacked. Is this a problem for GEL?

There are a number of ways to retrieve some information on the validity of a method or to get information on a service company:

• Inform yourself on the conceptual idea of the method from independent expert sources. Some of the proposed methods are fundamentally flawed from physico-chemical principles; others may be flawed from a sampling or analytical point of view.



• Check the reputable literature on published information; a publication in a peer-reviewed journal probably reflects a higher level of scientific merits of the method compared to a publication in, e.g., the Oil & Gas Journal.


Search the scientific literature for critical reviews and comments. We recommend articles by Price, Hunt, Schoell, Philp (SGE Literature)


• Find out whether this method is or has been used with exploration companies. Contact these companies and ask for opinions. (CTI assembles industry records on various methods).



• Was the method developed and tested in an oil company with subsequent published or available results?



• Are data of the method available from surveys over areas proven to be barren?



• Check anomaly maps of this method in case histories, examples, and on the web: if 40-60% or more of the area is "anomalous", chances are the SGE data are, at least in part, invalid. Many methods display large proportions of a survey area as "anomalous".



• Ask a reputable service company or an expert for a short or full seminar on SGE (Education). Make sure the seminar also provides a critical assessment on SGE with limitations, pitfalls and exploration "value" of these methods. Some seminars offered to the industry simply summarize case histories of various SGE methods.



• Ask a geochemist with scientific credentials in your business community -or from public institutions such as Geological Surveys for advice. Make sure there is no conflict of interest.



• When considering a survey, include, as part of the survey, an area familiar to you.



• Check out the service company for repeat customers. Be aware, if 20 customers are listed, but none ordered a repeat service.

If possible make your own field observations during the field survey. Certain tests can be conducted during field sampling to verify claims made by the contractor. For more information, contact CTI.

If subsurface geologic data are available and reliable, compare with surface survey results. Is there a relation of subsurface mapping with surface geochemical features?

Check for topography and soil-type from surfical geological/ agricultural maps: Many SGE data is surface-type related. This does not necessarily imply complete uselessness of the survey; however, surface factors may strongly influence the SGE pattern in question, meaning that many "anomalies" could be false positive anomalies.

Make sure you own or have access to the raw data. Raw data and machine data outputs can be re-evaluated later or independently. If you receive and accept processed data only, there is little or no chance to ground-truth field data. It is an open secret in this business that some methods built up smoke screen in order to confuse the issue and to prevent detailed raw data reconstruction.

Any SGE signal is either false or from above the salt section. Studies show that the content of migrated compounds in salt sections is extremely low (Alimi, 1978). This is also consistent with our observations in Saskatchewan/Canada over the Winnipegoises Reefs in those cases where these reefs are deeply underneath a thick salt package with no seep sign at the surface.

If true, any person or service company with a SGE record of correct "success rate 70%+" had be considered foolish not to run a (highly successful!) oil company if taken at face value. There are different ways to derive to such numbers – and thus, fooling yourself and the public. In many cases these statistical counts are done on a well-by-well count basis including development drilling which is often – by the merits of reservoir geology alone – 70-80% successful. In other cases 40-60% of the SGE surveyed area is "anomalous": no wonder this "method" is "successful" because it simply tracks conventional E&D success – independent from any "surface signal". Keep in mind that a random data set inevitably tracks conventional E&D records, which is in many mature areas 80% producers and 20% dry wells. Also keep in mind, that successful case histories find their way into the public domain, the bad cases end up in the drawer. Finally, none of these surface features are drilled on their own merits: The conventional exploration success record had to be subtracted from claimed "SGE success" in order to provide valid information on the true effectiveness of a SGE method. This type of record breakdown is seldom available. Finally, a statistical evaluation should be restricted to prospects instead expanded on a well-by-well count. More information: Education and GEL Track Record

Only in seldom circumstances! There are several reasons not to do this, the two prominent are: first, SGE does not necessarily correlate with economics. Second, no SGE method, including CTI's unique GEL technology, is 100% foolproof (GEL Track Record). False positive anomalies still do occur. SGE methods are no stand-alone tools, but should be used in conjunction with conventional exploration. SGE anomalies should only be drilled on their own merits if two conditions are met:

1. A proven contribution to discoveries from this method,
2. No subsurface data available.

Then, this SGE method is your only exploration tool.

Limited! These companies are calculating these probabilities because the explorationist likes to hear a number she/he can relate to, equivalent to the prospect risk assessment. These numbers are in fact, pretty meaningless, because they are based on the "quality" or "intensity" of the anomaly. The quality/intensity of an anomaly is, however, co-controlled by a number of variables in particular the fracture system.

E.g.: if you would run a SGE survey in Northern Iraq over a poor oil field, you would see a booming anomaly. Run the same survey over the giant Abqaip or Ghawar field in Saudi Arabia, the surface responds would be small or zero, because of a lack of regional fracture network and excellent seals.

The lateral dimensions can sometimes be indicated from good SGE technology. Quotes of a relation of an anomaly with pay zone thickness may be correct in rare cases, but not as a general rule. As for the question on "success probabilities", the anomaly is influenced from the type and extent of fractures.

The answer is a clear no! Although high sensitivity is important for analytical quality, precision and meaningful low concentrations, statements of such nature aim at a different target: the suggestion here is, that these ultra-low concentrations are of any meaning. Usually they are not.

For example, modern analytical instrumentation can identify few dioxin molecules in every domestic environment; however, such information is insignificant because the presence or absence of two dioxin molecules has no bearing. Likewise, it is feasible to identify native gold atoms in many creeks or rivers without a gold mine present in a 1000 miles radius.

The question is, how important or significant are certain concentrations; the question of the lowest possible detection is irrelevant. Also, keep in mind the lower the concentration the lower the S/N ratio. In deed, some service companies are deep into data noise and many SGE "signals" are simply statistical or surface-related noise.

At CTI, we recognized early on that the major shortcomings, flaws, and misconceptions in SGE originate from the lack of noise definition. A surface explorationist who does not understand the noise in his data, the variation of this noise, and the sources and character of the noise can never claim to report a seep signal.

Surface gas is the most direct way to track seep gases. If, in fact, some surface HC gases have nothing in common with seepage, some of these "seepage manifestations" may be in error. HC-microbes do not differentiate between seep ethane and soil in-situ ethane, for example; surface "compound patterns" cannot differentiate the several sources of surface HC; mineral alterations believed to be associated with seep gases may in fact result from pervasive biological soil HC gases. It should be remembered that micro-seep detection is about low level seep rates comparable to in-situ biological C₁-C₃₀ production in the soil. Smith and Ellis demonstrated this problem as early as 1963!

Thus, some knowledge on soil processes and soil environments is essential to evaluate a range of surface exploration data and their day-to-day applicability.

It depends on the nature of the measurement. At CTI, we have evaluated air-systems that claim to monitor active seep gases escaping into the atmosphere. These claims are entirely unfounded for several reasons:

1. Micro-seep gases are, a priori, low in concentration in the soil. The transition into the atmosphere is a diffusion process resulting in an almost infinite dilution with no chance of recording.
2. If HC gases are, in fact, recorded, they originate from different sources: swamp gases; low level, but pervasive HC gas contamination from industry, traffic, combustion processes etc.
3. Some of these recording devices do in fact not respond to HC gases as claimed. Simple field experiments can demonstrate this fact (Education)

Most airborne systems in use measure magnetic properties in the shallower sediments, which is a different, indirect approach. These surveys may have some merits (Education). In summary, airborne systems can be useful to detect intense seep trends.

The question is related to several factors:

1. Seepage is a dynamic process with some variability of the seep rate due to changing and alternating subsurface conditions. Thus, some variation is expected and, in fact, observed.



2. In some cases the gas sampling is carried out at very shallow depth; no wonder the variability of highly fugitive gases is large.



3. Much of the soil HC content has nothing to do with seepage but with biological soil in-situ HC generation and destruction. Most of the variability of soil gases originates from these processes. Once the true seep HC are identified, the seep signal is present and stable as presented in many repeat GEL surveys.

Time-integrative sampling is, per se, better – and more expensive – than instantaneous sampling. The question is, whether the additional expense fully translates into better data. In most cases instantaneous sampling is sufficient as the deep soil has long gas retention / gas residence times: Seep gases from seep pulses do not disappear over night but remain in the soil for weeks. CTI's Brassey oil field stationary field experiment data demonstrate this fact (Education). The advantage of time-integrative data collection is mostly exaggerated. Seep gases accumulating in the deep soil form a dynamic equilibrium: the snap shot sampling is representative for this sample site. Furthermore, most common time-integrative methods sample from very shallow depth - because of access problems at typical free gas sampling depth. Any sampling at very shallow depth just a few inches in the soil is problematic. There is an exponential increase of noise and erratic nature of data with decreasing sample depth. At the same time the concentration of seep gases is clearly minimized as you move up towards the surface as demonstrated again by Klusman (2003). E.g., Klusmans's (2003) methane seep concentrations of around 2000 ppm at around 1.2m soil depth (normal free gas sampling depth) are reduced to less than 10 ppm (!) at the shallow depth used in "time-integrative" adsorption techniques. The so-called "time-integrative advantage" turns into a definite disadvantage!

Finally, all adsorption materials are problematic, as quite often, they are highly selective. Moreover, they quickly become saturated with abundant moisture vapors and non-seep gases before any seep gases are adsorbed. For further information on this subject, we refer to the USGS paper in 1996 by Leigh Price (SGE Literature) or Contact us for a free copy of this paper. The Price (1996) paper evaluates a number of SGE techniques.

Definitely! Contamination can be classified into several categories:

1. Casing leakage along drill pipe.
   Casing leakage is frequent, but can easily be recognized and by-passed.



2. Surface HC and other types of surface contamination, in particular near and over oil fields.
   Surface contamination is often pervasive over fields as demonstrated by a number of environmental reports and "anomaly" re-evaluation from some classic SGE anomalies cited in the previous literature as textbook examples. Our GEL sampling procedure is rarely ever effected from this type of surface contamination because of deep sampling, and, furthermore, no need for a test or learning case. In addition, GEL concentrates on light gases; surface gas contamination never reaches the GEL sampling depth horizon. However, all instantaneous and time-integrating sampling collection procedures in the 0-30cm depth zone are prone to pick up surface contamination in any area where pollution is present!



3. Sampling contamination.
   Sampling contamination can be avoided by conscientious fieldwork. This is why CTI does not outsource fieldwork unless requested by the client.



4. Lab contamination.
   Lab contamination originates from site (air) pollution, sample cross-contamination running different sample types etc. If a lab processes reservoir oil / reservoir gas / environmental samples / soil gas samples for exploration, contamination of the sensitive soil gas samples is predicted!

Our advice: stay away from surveys depending on field calibration, in particular when very shallow sampling is involved; stay away from labs and service companies processing different sample types. At CTI, the in-house lab is only and exclusively used for soil gas analyses on our own samples. All other sample material is farmed out to first class lab operations in Canada, USA or Europe that we cooperate for years.

Finally, keep in mind that oil field contamination is not limited to the dispersion of liquid HC. Oil field activity can "create" surface anomalies, and some of these previously cited textbook examples on SGE anomalies do not belong into textbooks anymore.

Some SGE methods utilize "pattern learning data sets" over proven, producing fields to obtain a surface "seep pattern" from adsorbed gas profiles and to apply this "seep pattern" as a learning set for comparison to samples collected over virgin exploration terrain. Usually in these methods, the analysis compounds per se are of no interest, it's the pattern that counts.

All geochemists with some reputation consider this method as highly questionable (as a mild expression) for a number of reasons:

• It is assumed that the pattern contains a seep signal from seepage; what if no seepage is present from the calibration field? There is no proof or tests to conduct that verify the learning pattern is associated with a true seep signal. In fact, chances are that the learning pattern has nothing in common with a seep signal, as explained below.



• It is also assumed that seep HC find their way into the collection device, usually some adsorbent. This material is selective with the least chance for seep HC being adsorbed, because of their lowest affinity for adsorption. Instead, vapor moisture and a selection of 300+ soil volatiles saturate the collection device. Thus, these "learning data sets have little chance to record any seep signal expected to be in the C₁-C₅ molecular range.



• Soil-type variation is commonly believed to cause the "patterns" of this simplistic, statistical approach.



• Measuring dozens of compounds of absolutely no significance for seep phenomena is just clouding the issue.



• Investigating the "seep pattern" closer reveals inconsistencies in regard to seepage. The paper of Price (1996) (Contact us) of the USGS is just one of several comments on the inconsistencies of this approach.



• Finally, keep in mind that the sample collection is usually in the very shallow soil with virtually hundreds of noise and volatile gases available and eager to get adsorbed first! Now, keep in mind that the minute amounts of seep HC – with least affinities for absorption – must compete with these other gases for space on the adsorption material. See the recent data of Klusman (2003) for a depth profile of gas concentrations in soils, read the Price (1996) paper, and form your own intelligent opinion.

In summary, we – and the educated geochemical community as a whole – question or disregard this methodology as it is conceptually flawed. Field experiments validate this opinion, too. What are recorded are, as we firmly believe and some explorationists and geochemists know from soil map studies in comparison to these results, variations in soil-type and / or oil field contamination.
Finally, some of these "integrative learning data sets" are cost intensive.

Our experiments show that the opposite is true. The drainage radius around a sampling site in the soil is limited. After 150-200 cc of soil gas sample taken, the soil's free HC gas capacity in this drainage radius is usually exhausted in most soils. More "pumping" dilutes the HC concentration because of infiltrating atmospheric air! Even selective gas collection on, e.g. an adsorbent, does not constitute significantly more HC gas: after about 250cc of sampling there are no additional HC gases left, so further sampling (which would be of atmospheric air) is a wasted effort.

In the late 1980's and early 1990's CTI had the luxury to investigate and explore an entire range of these SGE methods, involving an $8 million R&D budget. It just turned out what Victor Jones, now with ETI, had started at former Gulf Oil made sense and we actually could quantify survey results. None of the other techniques we investigated could demonstrate this; in fact, we even went so far to develop a new microbial technique because of the downfall of microbial techniques being offered. So, CTI took off where Gulf Oil left. We perfected a method that initially emerged from industry R&D and application.

The concept of microbial surveying for oil deposits is based on the observation of HC leakage towards the surface and specific microbial species in association with this seepage. These microbes have enzymes specific to HC metabolism, i.e. they thrive in seep environments with seep HC as their food source.

Thus, the presence or frequent occurrence of these specific microbial communities is considered to be a prime indicator for subsurface HC occurrences, similar to high gas yields in soils observed over fields.

In the past the occurrence of these HC-microbes was considered to be very diagnostic until later research found out the ubiquitous occurrence of these specific microbes (Schlegel, 1992). The reason for this is the ubiquitous occurrence of HC gases and HC liquids in the soil, and the fact that many of these organisms have the ability to switch the food source in lack of HC constituents. Thus, anomalous microbial surface readings operate on a relative scale; point-blank "presence" or "absence" is not a diagnostic criterium. The concept is that HC-microbes thrive better in seep - than in non-seep environments. One advantage of microbial surveying is the natural time-integrated signal in the microbial readings.

There are a number of direct and indirect procedures and methods to quantify HC-microbe populations, from direct plate counts to "food consumption" rates in incubation tests, or the specific products/reactions of the specific HC metabolism.

For a simple reason: There is no microbial technique around that is not plagued with severe problems. We had the luxury to explore many SGE techniques, including microbial methods. The concept of microbial surveying is sound; the available methods are not, because they have inherent problems:

• Sample preservation: samples have to get to the lab or field processed within 24-48 hours. This is difficult or impossible in remote areas. Microbial surveyors dry (sterilize) the sample, in the hope to "resurrect" microbes in the lab at a later date. Detailed research at the Biology Institute IV at the RWTH in Aachen, Germany during the early 2000's shows repeat results on identical dried samples to be vastly erratic. Biotal/Canadian Hunter Exploration made the same experience in the late 1980's.



• The sampling is carried out near the surface which is in the worst depth interval possible, where maximum and extreme biological activity takes place and least amounts of seep HC are present. Furthermore, HC specific microbes are universally occurring and not specifically bound to seep sites. The reason for this is the universal occurrence of HC gases in the soil as pointed out in GEL in-depth.



• Microbes are not discriminating between soil in-situ HC and seep HC!



• Despite some insurance of microbial surveyors, microbial survey results are highly soil/environment type related. There is a solid body of information available to demonstrate this fact. Thus, unless soil type compensation is achieved, the data are of low diagnostic value.



• Finally, microbial methods report only a single number. Unlike detailed compositional gas data, crosschecks to validate, control, or inspect raw data results are not possible.

Microbial surveyors say yes, we say no! Common microbial methods focus on C₂-C₅ HC components, the bulk constituents of seep gases besides the universal methane. Thus, there are conceptual constraints on how, e.g., ethane-metabolizers could respond to micro-seepage from a reservoir of 98% methane. The associated seep-ethane is calculated to be extremely low in comparison with common soil in-situ bio-ethane!

We believe there is considerable room for improvement in microbial survey methods. The approach is conceptually correct for surface oil exploration. That is why CTE is cooperating with a university for some time and recently with partners to develop a new technique that eliminates the shortcomings we report here and earlier (Sleat and von der Dick, 1989). The goal is to overcome the deficiencies of current microbial methods.

CTI developed and introduced the GEL (Geochemical Exploration Lead) system, a high profile gas sampling / compound analysis / numerical analysis system of extreme, quantifiable sensitivity that uses a seep fingerprint approach as a defined seep signal in fuzzy and noisy soil gas data.

GEL gas surveys utilize detailed gas analysis profiles of deep soil samples and can be operated in both instantaneous and time-integrated modes.

We compare the exploration effort seismic/geology vs. the exploration effort seismic/geology + GEL, and we restrict this comparison to a prospect-by-prospect basis (a well-by-well count basis is misleading statistics!). Furthermore, the GEL system is the only SGE method systematically and objectively tested by an oil company (Wyman, 2002). More information is found under GEL Track Record or Education and SGE Literature.

Not in general; as with most SGE methods, GEL is a surface signal relating to deeper sections, but the depth target cannot be predicted.

An exception is very shallow gas where GEL records phenomenal seep rates; also, if Cretaceous dry gas is above and Devonian oil below, we know the seep signal is from the Devonian if the GEL seep gas composition is wet.

This is, in fact, problematic for all SGE technologies, because several horizons can contribute to a combined surface seep signal. It is also a question of the degree of depletion of established production. However, the lack of a seep signal in such situations is a warning.

• Where and when did you first hear about SGE methods?
• Have you subscribed or participated in a SGE survey?
• When was that?
• What type of survey?
• Why did you select this SGE Method?
• What service company was engaged providing this SGE survey?
• Were you actively involved in fieldwork, data analysis etc., or was the service just rendered to you?
• What were the results?
• Could you effectively use this information; was it possible for you to judge/evaluate results; did you consider these data useful or useless?
• Do you have further suggestions or comments?

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