Oil and Gas Evaluation Report : Oil & Gas Evaluation Professionals : Obsidian Energy Company : · Seismic Interpretation, Petroleum Engineering

This article was contributed by Staffan Van Dyke as part one of a two part series.

INTRODUCTION

Direct Hydrocarbon Indicators, or DHI's (also commonly known as, HCIs [HydroCarbon Indicators]), are used every day in the oil and gas industry by technical professionals to help search for hard to find, or simply overseen, hydrocarbon deposits. There are many factors that must be taken into consideration to apply seismic attributes properly; to name a few:

1) understanding rock physics;

2) the signal to noise ratio of the seismic survey;

3) poor processing;

4) insufficient (or erroneous) acquisition parameters, and so on.

When gas or oil replace the interstitial brine water in existing reservoirs, the seismic reflection coefficient inherently changes (this is manifested by a difference in the acoustic impedance of the hydrocarbon-bearing zone as compared to the brine-saturated zone either above or below the reservoir in question). This work must be done in order to determine if a well should be drilled OR NOT DRILLED - this cannot be stressed enough; therefore DHI's are a cornerstone application for the hunt of oil and gas deposits. It should be noted that not all seismic anomalies are DHI’s, and not all DHI’s are of equal quality; amplitudes can be caused by factors not related to hydrocarbon accumulations - this is a key point that many geophysicist commonly overlook (this will be discussed in greater detail in Part II of this write-up).

Potential Pitfalls in DHI Interpretations

The relative amplitude value can be deteriorated and/or altered dramatically by post-processing of the seismic data. That is, the numbers associated with the seismic amplitude values are unitless, therefore, they fall into no particular unit scheme (there is a large misconception in the oil industry that all seismic amplitudes fit nicely into a -128 to +128 value scheme - THIS IS NOT SO - in fact, they can range anywhere from -0.00234 to +0.00234 to as high as -14656 to +14656 before processing - simply put, amplitude values are unitless numbers - therefore, they are qualitative, not quantitative.

During processing, erroneous artifacts may manifest themselves in the seismic dataset - these need to be studied with great detail to be certain that they are indeed real or not real; an error of this magnitude could cost a company $100's of millions of dollars, so it is very important to understand what one is doing and if they are going about it the proper way. Therefore, analog data, calibrated well logs, etc., must be used to help determine if these artifacts are true representations of hydrocarbon deposits.

Other major issues include the calibration of wells that are not in the same geologic province because they come from a different environment of deposition, or the wells used to calibrate the data are simply too far away from the well being studied. Additionally, if things such as stratigraphic changes (e.g., going from a channel fill sandstones environment to a thin bedded levee environment) the well ties and the prospects will be wildly different. And perhaps the most common error is the lack of sufficient integration of geological data/interpretations for the prospect being examined.
 

Basic Seismic Attributes Definitions

Bright spots: Local increase in amplitude on a seismic section (presumably caused by a hydrocarbon accumulation)
DHI or HCI: Measurement which indicates the presence or absence of a hydrocarbon accumulation (bright spot, dim spot, flat spot, shadow zone, etc.)
Phase (Polarity Change): Seismic peak changes to a trough (or vice versa)
Dim Spot: Local decrease in reflection amplitude, generally occurs in low porosity sands (10% to 15%)

Figure 01: Flat Spot showing fluid contact of a gas field with an underlying water leg (blue-dashed line)

Figure 02: Gas reflections from the Nile Delta in Egypt; the high amplitude red reflection (trough) is from the top of the gas in this antiformal trap; conversely, the high amplitude blue reflection is from the base of the gas, or from the fluid contact.

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This article was contributed by Staffan Van Dyke

The objective of this article is to evaluate tight gas sandstones in relation to conventional reservoirs (sandstones/carbonates) as well as unconventional reservoirs (coalbed methane/shale gas), with reference to its constituent petroleum system parameters: source, trap, seal, reservoir properties (porosity and permeability), and time factors (timing of charge and migration). The article indicates significant differences between tight gas sandstones as compared to coalbed methane and/or gas shales. A thorough evaluation of the geological evidence studied for this article indicates that tight gas sandstones, as a reservoir, are closer to conventional type reservoirs than they are to unconventional type reservoirs, such as coalbed methane and/or gas shales.

Utilizing the framework described in this paper, tight gas sandstone reservoirs should then be considered as a sub-type category within the overall conventional reservoir definition, as the majority of its geological properties fall within this definition, and not that of an unconventional reservoir – note: the suggestions laid out in this article STRICTLY refer to the geological parameters of these reservoirs and NOT their engineering parameters (which are still very clearly considered “unconventional”).

Under this definition just laid out, the characterization of tight gas sandstones as an unconventional reservoir is simply inappropriate, as the geological setting / petroleum system / etc., as compared to coalbed methane and shale gas, are very different in their most basic geological constituents, making the comparison (and, hence, the argument that they are indeed very different from one another when viewed in a geological sense). Tight gas sandstones are simply reservoir rocks, whereas coal and shale are considered to be both the source and the reservoir rock.

Unconventional reservoirs are ones that cannot be produced at economic flow rates or they do not produce at economic volumes without the assistance from massive stimulation treatments, such as hydraulic fracturing (fracking) or other special recovery processes and technologies, such as steam injection (these are known as “secondary” and/or “tertiary” recovery techniques). Typically unconventional reservoirs have been described as: tight gas sands, coalbed methane, and gas shales (Holditch, 2003 and 2006). However it is an economic and reservoir engineering definition and does not take into account the geological processes behind the deposition of said deposits.

It is also important to understand that a conventional (sandstone/carbonate) reservoir with low natural pressure that depletes very quickly (in the order of weeks to months) that requires artificial hydrocarbon recovery techniques to maintain or increase its economic viability, is very nearly the exact definition of an unconventional reservoir, as the one given above. However, such reservoirs are still categorized as conventional in the geological sense.

On the other hand, since tight gas sandstones must be artificially stimulated (fracked) in order to produce its gas, it would only seem natural to place this reservoir criterion in the “unconventional reservoir” category.

Comparison of conventional and unconventional reservoirs

In the United States, the tight gas sandstone definition is applied to reservoirs with less than 0.1 mD of permeability (Meckel and Thomasson, 2008). Our investigation indicates that tight gas sandstones have significantly different characteristics in comparison to coal bed methane and shale gas. They are:

1. Tight gas sandstones act purely as a reservoir, whereas coalbeds and shales act not only as their own source rocks, but as well as their own reservoirs;

2. Shanley et al (2004) found that the low permeability reservoirs in the Greater Green River Basin of southwest Wyoming were not part of a continuous type gas accumulation but were low permeability rocks in conventional structural, stratigraphic, and/or combination traps. Earlier, Berry (1959) and Hill et al (1961), proposed that in the San Juan Basin, the gas within the sandstone reservoir was localized in a potentiometric sink associated with down-dip flow of water. In other words, it is a hydrodynamic type trap, thus, much more like the conventional trap settings found in conventional reservoirs;

3. Gas migrates into tight sandstones from the nearby source rock and the charged gas may be housed within the reservoir due to high capillary pressure conditions by virtue of low porosity and permeability, and up-dip presence of water due to regional or local hydrodynamic conditions, whereas in coal and shale gas, it is adsorbed into the matrix of organic matter (Bustin and others, 2009);

4. Many conventional reservoirs are porous and permeable but do not have enough primary energy to support hydrocarbon production unaided at an economic level, but are still categorized as conventional reservoirs. According to the unconventional reservoir definition given above, this quality should then define these reservoirs as unconventional, primarily because enhanced recovery techniques are required for them to be economically producible. Similarly, tight gas sandstone reservoirs need enhanced recovery techniques like fracturing, flooding, and
acidization to make them economically viable. However, instead of categorizing these low primary-energy conventional reservoirs as unconventional, it is the authors’ opinion that they should remain classified as conventional reservoirs, and that tight gas sandstones should be classified as a sub-type within the overall conventional reservoir petroleum system;

5. The only correlatable property of tight sandstones to coal and shale is their low porosity and permeability similarity, unlike the higher porosities and permeabilities typically seen in conventional sandstone / carbonate reservoirs. The geological aspects discussed above suggest that tight gas sandstone as a reservoir is closer to conventional reservoirs (sandstone / carbonates) than to coalbed methane and shale gas reservoirs. Table 1 summarizes the petroleum system and other parameters with respect to tight gas sandstones, coalbed methane, shale gas, and conventional reservoirs to elucidate the similarities between these reservoir types.

Conclusion

Evaluation of the above geological aspects suggests that tight gas sandstones, as a reservoir, are closer to conventional type reservoirs than to unconventional type reservoirs, like coalbed methane and shale gas. It is clear that tight gas sandstones act simply as a reservoir, whereas coal and shale act as a source rock as well as a reservoir for the gas. Tight sandstones may become a hydrocarbon reservoir only when a potential source rock is available within the basin, or a nearby region, capable of charging the reservoir. Utilizing the framework described in this paper, tight gas sandstone reservoirs should be considered as a sub-type conventional reservoir, as the majority of its geological and petroleum system parameters fall within this definition, and not that of an unconventional reservoir.
 

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We will periodically feature a guest author and this post was contributed by Staffan Van Dyke 

Spectral decomposition is a novel seismic technique that was originally pioneered through research at BP and Amoco in the 1990’s. Spectral decomposition (spec-decomp) is an imaging innovation that provides interpreters with high-resolution reservoir detail for imaging and mapping temporal bed thickness and geological discontinuities within 3D seismic surveys by breaking down the seismic signal into its component frequencies.

A fully processed seismic survey contains all of the frequencies that are capable of being recorded by the geophones/hydrophones used for that particular survey (this is known as its “dynamic range”). After the seismic source has been “shot,” the energy propagates downward into the subsurface and at each geologic boundary (e.g., an unconformity, bed boundaries, etc.), the seismic energy is reflected, refracted, and/or absorbed.

As the wave front continues to propagate into the underlying sediments, it attenuates, causing the frequency content to decrease with depth, i.e., higher frequencies are better preserved at the top of the section. Due to this attenuation, the higher frequencies deeper in the seismic survey are “drowned” by the more dominant, lower frequencies. The purpose of spectral decomposition is to see the seismic response at different, discrete frequency intervals, as higher frequencies image thinner beds, while lower frequencies image thicker beds.

The concept behind spectral decomposition is that the seismic reflection from a thin bed has a characteristic expression in the frequency domain that is indicative of its thickness in time. For example, a simple homogeneous thin bed contains a predictable and periodic sequence of notches into the amplitude spectrum of the composite reflection (Praptono et al., 2003; Figure 1). However, typically a seismic wavelet contains the information from multiple subsurface layers and not just one simple thin bed. The combined seismic response from these multiple subsurface layers usually results in a complex tuned reflection which has a unique frequency domain expression; in order to help resolve these thin beds, spec-decomp can be used. 

 Figure 1: Spectral decomposition is used to identify thin beds through analysis of the frequency spectrum in a short window around the time of the bed (Partyka et al., 1999).

As stated before, spectral decomposition can be used to break down the seismic survey into its component frequencies (Figure 2).  When determining which frequency to extract from the dataset, it's best to use a non-standard or octave scale in order to avoid potential harmonics (seeing the same information at multiples of its base frequency).  Thus, multiple datasets are created at these pre-selected, discrete intervals, e.g. 15.3 Hz, 29.6 Hz, 44.4 Hz and so on.  After determining these frequency intervals, each subsequent dataset produced via spec-decomp manifests only that particular frequency.

After all datasets have been produced, the reservoir interval of interest can then be scrutinized in greater detail.  This is carried out by capturing the seismic response at each frequency subset (15.3 Hz, 29.6 Hz, 44.4 Hz, etc.) - essentially, a "screen-capture" of the seismic image for each of these intervals can be input into an animated sequence from lower frequencies to higher frequencies, thus revealing spatial changes in stratigraphic thickness otherwise impossible to ascertain from the full frequency dataset.  Spectral decomposition reveals details that no single frequency attribute can match.

Figure 2: Note the different seismic response at 40 Hz as compared to 20 Hz; much more detail can be ascertained with the 40 Hz wavelet, however, the 20 Hz wavelet still manifests information about temporal bed thickness and the stratigraphic nature of the deposit.

*Nexen Petroleum U.S.A. Inc., Dallas, TX, U.S.A. (email: staffan_vandyke@nexeninc.com)

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We will periodically feature a guest author and this post was contributed by Staffan Van Dyke*

When used as a standalone tool for Vshale, there are some known issues about gamma-ray (GR) logging to consider.  Petrophysicists frequently use the term ‘Vshale’ or ‘Vclay’ (where V stands for Volume) to help establish gamma-ray cut-off values (baseline) to determine a shale from a clean sandstone in clastic depositional environments. Typically, in most geologic settings, this works reasonably well, but of course, the tool, and the use of a single measurement, isn’t always perfect.

So, what exactly is a gamma-ray tool actually measuring? Radioactivity. Because most shales tend to contain one, or more, of the radioactive elements Potassium (K), Thorium (Th), or Uranium (U), they have higher radioactivity levels.  The higher the radioactivity measured, the ‘hotter’ the interval.  Since sandstones typically have few radioactive minerals, they are termed ‘clean.’  GR response is usually calibrated by a ‘clean’ or radioactive-free zone in the rock column being measured.  This GR response is then contrasted to more radioactive rock in the column, notably the much finer-grained shales – this then creates the ‘baseline’ by which all rock classifications are then based.

As aforementioned, this method can work very well as a lithology indicator, particularly in the Gulf of Mexico (GOM), however, there can be misinterpretations.  Kaolinite is virtually a radioactively clean and common clay.  So, if a gamma ray log was run through a purely kaolinitic clay, you would have a very ‘clean’ or zero-radioactive GR response, which could be misinterpreted as Vclay = 0%; hence, the clay would then be wrongly identified as a ‘clean’ sandstone...well, obviously, this is not the case.

On a similar note, this same phenomenon (i.e., an erroneous reading) can occur to a perfectly good reservoir-quality sandstone, as well.  Sandstones are typically characterized by sand-sized particles (very fine to very coarse), and are usually highly quartzose (i.e., non-radioactive). Theoretically though, they could be almost exclusively feldspathic (as seen in active margin settings [e.g., California]), or calcitic, or basaltic, or even hematitic.  Since the provenance of many reservoir rocks found in California oil fields were sourced from granitic uplifts, the resultant reservoir rocks contain radioactive aggregates (primarily Potassium Feldspar [K-Spar]).  Because of this, these rocks (with permeabilities in the order of Darcies) light up on the GR sonde as ‘hot’ lithologies, i.e., it would lead one to classify them as shales.  Obviously, this is not the case, either.  In order to avoid these potential misinterpretations, a thorough background geologic study of the field at hand should be carried out.

We can see that there are inherent errors associated with using the GR sonde as the sole lithology indicator in certain geologic settings, not only with Kaolinite in shales, but with K-Spar in sandstones, as two end-member examples.  This is why it is always wise to use several tools at one’s disposal for proper lithologic classification.  So, in addition to the familiar GR tool, consider using neutron-density, and possibly a Spectral Gamma Ray tool in conjunction with the Spontaneous Potential (SP) log for additional insight on the true lithologic character of the intervals being examined. 

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