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					 Total Organic CARBON (TOC) BASICS Organic carbon
			in the form of kerogen is the remnant of ancient life preserved in
			sedimentary rocks, after degradation by bacterial and chemical
			processes, and further modified by temperature, pressure, and time.
			The latter step, called thermal maturation, is a function of burial
			history (depth) and proximity to heat sources. Maturation provides
			the chemical reactions needed to give us gas, oil, bitumen,
			pyrobitumen, and graphite (pure carbon) that we find while drilling
			wells for petroleum.
 
			Organic
					carbon is usually associated with shales or silty shales,
					but may be present in relatively clean siltstone, sandstone, and carbonate rocks.
			
 A source rock is a fine grained sediment
			rich in organic matter that could generate crude oil or natural gas
			after thermal alteration of kerogen in the Earth's crust. The oil or
			gas could then migrate from the source rock to more porous and
			permeable sediments, where ultimately the oil or gas could
			accumulate to make a commercial oil or gas reservoir.
 
 If a source rock has
			not been exposed to temperatures of about 100 °C, it is termed a
			potential source rock. If generation and expulsion of oil or gas
			have occurred, it is termed an actual source rock. The terms
			immature and mature are commonly used to describe source rocks and
			also the current state of the kerogen contained in the rock.
 
 Total organic
			carbon (TOC) as measured by laboratory techniques historically has
			been used to assess the quality of source rocks,
			but now is widely used to help evaluate some unconventional reservoirs
			(reservoirs that are both source and productive).
 
 
   Pathways that
			convert living organisms to organic carbon, from "Bitumens,
			Asphalts, and Tar Sands" by 
			
			George V.
			Chilingar,
			Teh Fu Yen, 1978. 
			In the
			lab, it is relatively easy to distinguish kerogen from hydrocarbons:
			
			
			kerogen is insoluble in organic solvents, oil and bitumen are
			soluble. Pyrobitumen is not soluble but its hardness is used to
			identify it from kerogen. 
			Graphite is evident on resistivity logs because of the very
			low resistivity; all other forms of organic carbon are resistive. 
			Organic
			carbon has a density near that of water, so it looks like fsporosity
			to conventional porosity logs. High resistivity with some apparent porosity on a log
					analysis is a good indicator of organic carbon content OR
			ordinary hydrocarbons OR both. 
 Some more definitions are in order. All hydrocarbons are composed of
			organic matter (OM), posibly with inorganic impurities. Kerogen and
			coal are called primary organic matter as they were deposited during
			sedimentation. Gas, oil, bitumen, and pyrobitumen are called
			seccondary organic matter as they were formed in place in a source
			rock and may have migraated from there to another reserervoir rock.
 
 Kerogen has been associated historically with source rocks but has
			gained more notice recently as the source of hydrocarbons in
			so-called gas shale and oil shale (unconventional) reservoirs.
			Kerogen is the source of oil or gas in the free porosity and can
			also hold producible gas within its structure in the form of
			adsorbed gas. Some reservoirs that have been treated or described as
			gas shale or oil shale have little or no kerogen (tight gas or tight
			oil reservoirs). Some of tight gas plays may have bitumen or
			pyrobitumen, instead of kerogen. Pyrobitumen can hold adsorbed gas
			in nano- or micro-porosity, similar to kerogen.
 
 For example, where the generated hydrocarbons have largely remained
			within the source rock, as in the Barnett Shale, the organic matter
			will be a mixture of kerogen and pyrobitumen. However in other tight
			gas plays (Montney, Marcellus), petrographic analysis indicates that
			pyrobitumen is the dominant, sometimes the only, form of organic
			solid, and therefore the primary reservoir for adsorbed gas.
 
 Despite the genetic difference in origin of kerogen and pyrobitumen,
			there is a tendency to classify all shale organic matter as kerogen
			in geochemical analyses, due to the lack of petrographic or SEM work
			which would clarify the situation.
 
 
			
			
			 TYPES OF KEROGEN 
			Organic
			material can be classified according to the source of
			the material, as shown below. 
			 Origin, type, source, and
			hydrocarbon potential of different kerogens. 
			Organic content in gas shales is usually Type II,
			as opposed to coals, which contain mostly Type III
 
			
			 The
			most commonly utilized scheme for classifying organic matter in
			sediments is based on the relative abundance of elemental carbon,
			oxygen, and hydrogen plotted graphically as the H/C and O/C ratio on
			a so called Van Krevelen diagram.   
			
			The classic Van Krevelen diagram  
			
			Rather than plot the elemental ratios it is common to plot indices
			determined by a pyrolysis technique referred to as Rock Eval. In the
			pyrolysis techniques two indices are determined: the Hydrogen Index
			(HI) which is milligrams of pyrolyzable hydrocarbons divided by TOC
			and the Oxygen Index (OI) which is milligrams of pyrolyzable organic
			carbon dioxide divided by TOC.
   
			
			Cross-plots of both elemental H/C and O/C ratios or of HI and OI are
			utilized to discriminate four ‘fields’ which are referred to as
			Types I, II, III, and IV kerogen.   
			
			Type I kerogen is hydrogen rich (atomic H/C of 1.4 to 1.6: HI of >
			700) and is derived predominantly from zooplankton, phytoplankton,
			micro-organisms (mainly bacteria) and lipid rich components of
			higher plants (H/C ratio 1.7 to 1.9).   
			
			Type II kerogen is intermediate in composition (H/C ≈ 1.2: HI ≈ 600)
			and derived from mixtures of highly degraded and partly oxidized
			remnants of higher plants or marine phytoplankton.   
			
			Type III kerogen is hydrogen poor (H/C ratio 1.3 to 1.5) and oxygen
			rich and is mainly derived from cellulose and lignin derived from
			higher plants.   
			
			Type IV kerogen is hydrogen poor and oxygen rich and essentially
			inert. This organic matter is mainly derived from charcoal and
			fungal bodies. Type IV kerogen is not always distinguished but is
			grouped with Type III.   
			
			The different types of organic matter are of fundamental importance
			since the relative abundance of hydrogen, carbon, and oxygen
			determines what products can be generated from the organic matter
			upon diagenesis. Since coal is comprised predominantly of Type III
			kerogen, there is little liquid hydrogen generating capacity. If the
			coal includes abundant hydrogen rich components (such as spores,
			pollen, resin, waxes - Type I or II), it will generate some liquid
			hydrocarbons. Although not common, some oil deposits are thought to
			be sourced by coals.   
			Note: Portions of the above
			Section, and the next Section, were taken verbatim (with moderate
			editing) from CBM Solutions reports. 
 
					
					
					
					
					
					 Analyzing TOC IN THE LABORATORY The total
					organic carbon content of rocks is obtained by heating the
					rock in a furnace and combusting the organic matter to
					carbon dioxide. The amount of carbon dioxide liberated is
					proportional to the amount of carbon liberated in the
					furnace, which in turn is related to the carbon content of
					the rock. The carbon dioxide liberated can be measured
					several different ways. The most common methods use a
					thermal conductivity detector or infrared spectroscopy.
 
 Many source rocks also include inorganic sources of carbon
					such as carbonates and most notably calcite, dolomite, and
					siderite. These minerals break down at high temperature,
					generating carbon dioxide and thus their presence must be
					corrected in order to determine the organic carbon content.
					Generally, the amount of carbonate is determined by acid
					digestion (normally 50% HCl) and the carbon dioxide
					generated is measured and then subtracted from the total
					carbon dioxide to obtain the organic fraction.
 
			Total organic
			carbon is often taken to mean the same thing as kerogen, but this is
			not the case. Kerogen is made up of oxygen, nitrogen, sulphur, and
			hydrogen, in addition to carbon. The standard pyrolysis lab
			procedure measures only the carbon, so total organic carbon excludes
			the other elements. 
 About 80% of a typical kerogen (by weight) is carbon, so the weight
			fraction of TOC is  80% of the kerogen weight. The factor is
			lower for less mature and higher for more mature kerogen:
 1: Wtoc = Wker * KTOC
 OR 2: Wker = Wtoc / KTOC
 
			Where:Wtoc = weight fraction of organic carbon
 Wker  = weight fraction of kerogen
 KTOC = kerogen correction factor - range = 0.68 to 0.90, default 0.80
 
			If
			pyrobitumen, which cannot be removed by solvents, is known or
			supected, a petrogtaphic or SEM study needs to be done to quantify
			non-kerpgen organic matter. The kerogen content can then be reduced
			by an appropriate amount.
 Another
			lab procedure, called RockEval, burns both hydrogen and carbon, so
			the data needs to be calibrated to the standard method by performing
			a chemical analysis on the kerogen. Typically the organic carbon
			needs to be reduced by about 10% (the weight of the hydrogen burned)
			to match the standard method.
 
			
			Rock Eval is the trade name for a set of equipment used in the lab
			to measure organic content of rocks, as well as other properties of
			the organics that help to identify the kerogen type. Rock-Eval combusts
			a crushed sample of rock at 600ºC.  Refractory organic matter
			such as inertinite does not combust readily at 600ºC so most coal
			samples yield Rock-Eval measured TOC values much lower than actual
			values because of incomplete combustion. Rock-Eval is not
			recommended for use with coals or source rocks with significant
			amounts of Type III and IV kerogen. 
			
			A rock sample is crushed finely enough so that 85% falls through a
			75 mesh screen. Approximately 100 mg of sample is loaded into a
			stainless steel crucible capped with a micro mesh filter. To ensure
			accuracy, standard samples are loaded at the beginning and end of
			the run. Any drift in data can be detected and the samples rerun if
			necessary.  
			
			The analyzer consists of a flame ionization detector and two IR
			detector cells. The free hydrocarbons (S1) are determined from an
			isothermal heating of the sample at 340 degrees Celsius. These
			hydrocarbons are measured by the flame ionization detector. The
			temperature is then increased from 340 to 640 degrees Celsius.
			Hydrocarbons are then released from the kerogen and measured by the
			flame ionization detector creating the S2 peak. The temperature at
			which S2 reaches its maximum rate of hydrocarbon generation is
			referred to as Tmax. The CO2 generated from the oxidation step in
			the 340 to 580 degrees Celsius is measured by the IR cells and is
			referred to the S3 peak. 
			
			 Measured results from a typical Rock Eval study will contain: TOC% - Weight percentage of organic carbon
 S1 = amount of free hydrocarbons in sample (mg/g)
 S2 = amount of hydrocarbons generated through thermal
 cracking (mg/g) –
			provides the quantity of
 hydrocarbons that the
			rock has the potential to
 produce through diagenesis.
 S3 = amount of CO2 (mg of CO2/g of rock) - reflects the amount of oxygen
			in the oxidation step.
 Ro = vitrinite reflectance (%)
 Tmax = the temperature at which maximum rate of
 generation
			of hydrocarbons occurs.
 
 Calculated results include:
 Hydrogen index
 1: HI = 100 * S2 / TOC%
 Oxygen index
 2: OI = 100 * S3 / TOC%
 Production index
 3: PI = S1 / (S1 + S2)
 
				
					| 
					Depth (m) | 
					TOC | 
					SRA | 
					Tmax | 
					Meas. | 
					HI | 
					OI | 
					S2/S3 | 
					S1/TOC*100 | 
					PI |  
					| 
					Top | 
					S1 | 
					S2 | 
					S3 | 
					(°C) | 
					% Ro |  
					| 
					X025 | 
					1.35 | 
					0.05 | 
					1.72 | 
					0.63 | 
					444 | 
					  | 
					128 | 
					47 | 
					3 | 
					4 | 
					0.03 |  
					| 
					X040 | 
					1.18 | 
					0.05 | 
					1.65 | 
					0.57 | 
					443 | 
					  | 
					140 | 
					49 | 
					3 | 
					4 | 
					0.03 |  
					| 
					X050 | 
					0.83 | 
					0.03 | 
					1.31 | 
					0.55 | 
					443 | 
					  | 
					158 | 
					66 | 
					2 | 
					4 | 
					0.02 |  
					| 
					X065 | 
					0.80 | 
					0.04 | 
					1.00 | 
					0.58 | 
					440 | 
					  | 
					126 | 
					73 | 
					2 | 
					5 | 
					0.04 |  
					| 
					X075 | 
					0.75 | 
					0.05 | 
					1.04 | 
					0.72 | 
					438 | 
					  | 
					138 | 
					96 | 
					1 | 
					7 | 
					0.05 |  
					| 
					X090 | 
					1.04 | 
					0.09 | 
					2.52 | 
					0.29 | 
					452 | 
					  | 
					241 | 
					28 | 
					9 | 
					9 | 
					0.03 |  
					| 
					X110 | 
					1.02 | 
					0.05 | 
					1.16 | 
					0.56 | 
					441 | 
					  | 
					114 | 
					55 | 
					2 | 
					5 | 
					0.04 |  
					| 
					X135 | 
					1.05 | 
					0.05 | 
					1.32 | 
					0.57 | 
					443 | 
					  | 
					125 | 
					54 | 
					2 | 
					5 | 
					0.04 |  
			Laboratory measured TOC values (weight %) with measured and
			computed indices 
			 HI versus OI plot example, indicating Type III kerogen
 
			An alternate
			method for measuring TOC by solution rather than pyrolysis is
			described below, from a 1980's TOC report from Australia. "The samples are
			analyzed for total organic carbon (TOC) according to AS 1038 Part 6.
			Moisture determinations are made to permit conversion to a dry
			basis. Carbon occurring as carbonate ion is determined to correct
			the gross carbon data to give the organic carbon content. This is
			done by driving off carbonate minerals with HCl acid.The crushed and sieved (100 mesh) samples are weighed and
			exhaustively extracted in a Soxhlet apparatus using a
			benzene-methanol mixture. After removal of methanol by azeotropic
			distillation with benzene, the residue in benzene is diluted with
			hexane and the hydrocarbon solution separated by filtration from the
			brown precipitate. The latter is then dissolved in methanol. The
			yield of methanol soluble material is determined gravimetrically. 
 The hexane soluble portion of the extractable organic matter
			(E.O.M.) is weighed and chromatographed on silica. Elution with
			hexane gives predominantly alkanes and subsequent elution with
			hexane/benzene yields mainly monocyclic and polycycllc aromatic
			hydrocarbons. The eluted hydrocarbons are weighed, and then analyzed
			by gas chromatography / mass spectrometry."
 
			
			
  Geochemical Logs Measured and calculated indices can be plotted versus depth; the
			resulting log
			is called a Geochemical Log.
 
			 A geochemical log from offshore
			East Coast Canada
 
			
 
			
			
			 KEROGEN
					maturity 
  The
			hydrocarbon potential of organic carbon depends on the thermal
			history of the rocks containing the kerogen. Both temperature and
			the time at that temperature determine the outcome. Medium
			temperatures
			(< 175 C) produce mostly oil and a little gas. Warmer temperatures
			produce mostly gas.   
			Hydrocarbon
			type versus temperature defines "oil window" and "gas window",
 with some obvious overlap
  
			Vitrinite reflectance (Ro) is used as an indicator of the level of
			organic maturity (LOM). Ro values between 0.60 and 0.78 usually
			represent oil prone intervals. Ro > 0.78 usually indicates gas
			prone. High values can suggest "sweet spots" for completing gas
			shale wells.
   
			Measurement of vitrinite reflectance was
			described as follows from the 1980's TOC report.   
			"Sample
			chips or sidewall core samples are cleaned to remove drilling mud or
			mud cake and then crushed using a mortar and pestle to a grain-size
			of less than 3 mm. Samples are mounted in cold-setting resin and
			polished ''as received", so that whole-rock samples rather than
			concentrates of organic matter are examined. This method is
			preferred to the use of demineralized concentrates because of the
			greater ease of identifying first generation vitrinite and, for
			cuttings samples, of recognizing cavings. The core samples are
			mounted and sectioned perpendicular to the bedd1ng.
 Vitrinite reflectance measurements are made using immersion oil of
			refractive index 1.518 at 546 nm and 23°C and spinel and garnet
			standards of 0.42%, 0.917% and 1.726% reflectance for calibration.
			Fluorescence-mode observations are made on all samples and provide
			supplementary evidence concerning organic matter type, and exinite
			 abundance and maturity. For fluorescence-mode a 3 mm BG-3
			excitation filter is used with a TK400 dichroic mirror and a K490
			barrier filter."
   
			Tmax is also a useful indicator of
			maturity, higher values being more mature.   
			Graphs of HI vs Ro and HI vs Tmax are
			used to help refine kerogen type and to assess maturity with respect
			to the oil and gas "windows". Depth plots of Ro and Tmax are helpful
			in spotting the top of the oil or gas window in specific wells, and
			in locating sweet spots for possible production using horizontal
			wells.   
			 Crossplots of HI vs Tmax and HI vs Ro
			determine organic maturity, kerogen type, and whether the rock is in
			the oil or gas window. Immature and post mature rocks are not overly
			interesting as possible source or reservoir rocks.
   
			
			 Depth plot of Ro to determine trend line and location of oil and gas
			windows (Ro > 0.55).
 Ro is plotted on a logarithmic scale, which makes the trend line
			relatively straight.
 
			 
			Thermal maturity as indicated by
			vitrinite reflectance (Ro) versus depth for a Barnett shale, showing
			"sweet spot" and
			oil versus gas “windows”.   
					
			
					
					 VISUAL ANALYSIS OF TOC FROM LOGS 
  Visual
			analysis for organic content is based on the porosity - resistivity
			overlay technique, widely used to locate possible hydrocarbon shows
			in conventional log analysis. By extending the method to radioactive
			zones instead of relatively clean zones, organic rich shales
			(potential source rocks , gas shales, oil shales) can be identified.
			Usually the sonic log is used as the porosity indicator but the
			neutron or density log would work as well. The
			trick here is to align the sonic log on top of the logarithmic scale
			resistivity log so that the sonic curve lies on top of the
			resistivity curve in the low resistivity shales. Low resistivity
			shales are considered to be non-source rocks and are unlikely to be
			gas shales. Shales or silts with source rock potential will show
			considerable crossover between the sonic and resistivity curves.
			The absolute value of the sonic and resistivity in the low
			resistivity shale are called base-lines, and these base-lines will
			vary with depth of burial and geologic age.  
			Schematic log showing sonic resistivity overlay in a variety of
			situations    
			  Sonic resistivity overlay showing crossover in Barnett Shale, Texas,
			labeled "ΔlogR" and shaded red.
 
			Crossplots of porosity and logarithm of resistivity can also be used
			to define and segregate source rocks from non-source rocks. See
			"Identification of Source Rocks on Wireline Logs by
			Density-Resistivity and Sonic-Resistivity Crossplots" by B. L. Meyer
			and M. H. Nederlof,  AAPG Bulletin, V. 68, P 121-129, 1984..The
			best description of the method is posted on the online magazine 
			Search and
			Discovery,
			
			
			in
			"Direct Method for Determining Organic Shale Potential from Porosity
			and Resistivity Logs to Identify Possible Resource Plays* by Thomas
			Bowman,
			Article #110128, posted June 14, 2010. These
			crossplots usually show a non-source rock trend line  on the
			southwest edge of the data (similar to the water line on a Pickett
			plot) and a cluster of source rock data to the right of the
			non-source line, as shown in the image below. The
			slope and intercept of the non-source line is used to calculate a
			pseudo-sonic log, DtR, from the resistivity log, which can then be
			plotted on the same scale as the original sonic log.   
  Sonic versus logarithm of resistivity (DlogR) Crossplot showing
			non-source rock trendline and source rock cluster of data. The
			equation of the non-source rock line is DtR = 105 - 25 log(RESD) for
			this Barnett Shale example.
 
			 As
			for the manual overlay technique described above, crossover
			indicates source rock potential, shale gas, or an oil shale, or if
			the zone is clean, a potential hydrocarbon pay zone. An example of a
			DtR log is shown below. 
			Original sonic
			log (left edge of red shading) and calculated DtR curve (black curve)
			showing potential source rock or, as  in this case, gas shale (Barnett)  Because porosity indicating logs
			suffer from mineralogy, porosity, and shale effects (not to mention
			rough and large borehole effects on the density log), as well as the
			effect of kerogen, Heslop (AAPG 2010) proposed a method of using
			gamma ray (GR) and deep Resistivity (RESD) overlays instead of
			porosity - resistivity overlays to find intervals with poential for
			organic carbon.
 In non-source shale (no TOC,), the GR increases while the RESD
			decreases, compared to typical reservoir rocks. These two log curves
			tend to “hour-glass” when plotted using conventional scales.
 Reversing one of the scales causes the GR and RESD curves to track
			each other. The exception occurs where TOC is present. When tracking
			, the separation gap between GR and RESD should be relatively
			constant. When TOC is present, both GR and RESD will increase in
			proportion to the TOC, and because of the standard log scales used,
			the separation gap increases.
 
 When expressed as the difference between non-source and source roc
			log values, the Heslop equation becomes:
 1: ΔGR + ΔRESD = TOC * (GRtoc + log(RESDtoc))
 
 Where:
 ΔGR and ΔRESD = differences between non-source and possible source rock
			values
 measured in log grid units
 TOC = total organic carbon (mass fraction)
 GRtoc and RRESDtoc were determined using TOC lab data correlated to
			the GR vs RESD separation gap.
 
			 Example from Ken Heslop's AAPG
			2010 presentation showung GR and RESD in normal scales in Tracks 1
			and 2, with reversed ILD on normal GR in track 3. Moderate separation
			gap between these two curves near bottom marked "TOC".
 
			
  BASIC ANALYSIS OF TOC FROM LOGS A
			wide variety of log analysis methods are used to calculate total
			organic carbon from well logs, ranging from over-simplified to
			complex multi-mineral probabilistic models. The Passey and Issler
			models, described later, are in the middle of the pack for
			complexity. We also need to convert lab data into volumetric terms
			for comparison to log analyis results. This Section coversd some of
			these steps.
 
					
			IMPORTANT: Remember that all log analysis models for TOC are
			calibrated to standard geochemistry lab data that often do not
			discriminate between kerogen and pyrobitumen. Either or both may be
			present. Both have variable but fortunately similar physical
			propertiees so converting log derived TOC to "kerogen" may actually
			be a conversion to pyrobitumen or a mixture of the two components.
 Correlation of core TOC values to log data leads to useful
			relationships for specific reservoirs. A strong correlation exists in some shales with
			Uranium content from the spectral gamma ray log. In other cases, the
			relationship is made with density, resistivity, sonic,  gamma
			ray, or combinations of these curves. Variations in matrix
			mineralogy strongly affect this type of correlation and it is
			possible that mineralogy will mask any trend with TOC. The crossplot
			shown below is for a particular well in the  Barnett shale.
 
			  Correlation of TOC with density in Barnett Shale: Wtoc = -0.259 *
			DENS  + 0.707.  Similar crossplots
			of sonic or neutron data can be used for specific reservoirs where
			TOC data is available from core.
 
			      
			Plot in Avalon Shale: Wtoc = -0.1324 * DENS + 0.754  
			  
			In their 1983 paper, Schmoker and Hester proposed the
			following equation based on data from the very organic rich Upper
			and Lower Bakken Shales in North Dakota and Montana: 
			
			 Wtoc = 0.01 * ((154.49 7 / DENS) – 57.261) 
				
					
						
							The constants were
							specific to these shales and may not apply
							elsewhere.Assumptions are  based on an organic
							matter density of 1.01 g/cc, a matrix density of
							2.68 g/cc, and a ratio between weight percent of
							organic matter and organic carbon of 1.3. The study
							reported an average organic-carbon content 
							12.1 wt% (upper shale) and 11.5 wt%(lower shale),
							using data from more than 250 wells. 
					It may be
			possible to use crossplots other than TOC versus density (DENS).in
			local areas. Density may be a poor indicator of TOC due to rough
			hole conditions or lithology variations (both clay volume and
			mineral mixture variations can add noise to the crossplot).
 TOC versus DlogR (or DtR), which was derived in a previous section on this
			page, is really a plot of TOC versus deep resistivity (RESD). Both
			plots are shown below. Resistivity is not much affected by rough or
			large borehole or mineralogy variations, but is affected by water
			fraction in porosity and clay volume.
 
 TOC versus uranium (URAN) from a gamma ray spectral log may be
			useful. Large variations in boreehole size and variations in the
			uranium content of the kerogen may cause noise. If clay volume is
			low or nearly constant, the total gamma ray log (GR) may be used. Do
			not use the "corrected" gamma ray (CGR) as the uranium has been
			removed from that curve. If both GR and CGR are available without
			the URAN curve, the difference between GR and CGR is equivalent to
			the shape of a URAN curve, so a TOC versus (GR -  CGR) may be
			useful.
 
					
			     TOC versus DtR                           
			TOC versus log(RESD)                           
			TOC versus URAN
 
			More sophisticated TOC log analysis
			models, such as Passey and Issler's methods, are developed later in
			ths weboage.
 
  Kerogen Density Kerogen density is difficult to measure directly but can be inferred
			from a plot of (inverse) core grain density versus TOC weight
			percent or mass fraction. 
			This value is needed to find kerogen volume fraction
			from kerogen weight fraction. The method also relies on the density
			versus TOC crossplot.
 
			  Plot to find TOC specific gravity (DENStoc) and rock grain density (DENSma)
			using inverse grain density on Y-Axis.
 On
			this graph, 1:
			DENSma = 1 / INTCPT
 = 1 / 0.37 = 2.703 g/cc
 2: SLOPE = (0.409 - 0.37) /
			(9 - 0) = 0.004166
 (from Excel spreadsheet)
 3: DENStoc = 1 / (100 * SLOPE + INTCPT)
 = 1 / (100 * 0.004166 + 0.37) = 1.28 g/cc
 4: DENSker = DENStoc / KTOC
 = 1.28 / 0.80 = 1.42 g/cc
 
 Where KTOC = kerogen correction factor
 - Range = 0.68 to 0.90, default 0.80
 
 
 Typical values for DENSker are in the range 0.95 for immature to
			1.45 for very mature, with a default of 1.26 g/cc.
 
			Because of the extrapolation from small TOC values up to 100% TOC,
			the possible error in DENStoc is quite large, so many people will
			choose a default based on the maturity of the kerogen. 
			
  Kerogen Volume Log
			analysis models need the volume fraction of kerogen, not the weight
			fraction. This is found from:
 
  1: Wtoc = TOC% / 100 2: Wker = Wtoc / KTOC
 3: VOLker = Wker / DENSker
 4: VOLmatrix = (1 - Wker) / DENSma
 5: VOLrock = VOLker + VOLmatrix
 6: Vker = VOLker / VOLrock
 
					There is
			a spreadsheet on the Downloads page
			that does weight to volume and volume to weight conversions -- see
			example at right.
			Typically, Vker is a little less than 2 * Wtoc.  
						
			
			
			SPR-15 META/LOG WEIGHT <== ==> VOLUME CALCULATORConvert weight fraction to / from volume fraction.
 
 
  GAS CONTENT versus TOC TOC values calculated from log analysis models 
			are widely used as a guide to the quality of gas shales. Using
			correlations of lab measured TOC and gas content (Gc). We can use log
			analysis derived TOC values to predict Gc, which can then be summed
			over the interval and converted to adsorbed gas in place. Sample
			correlations are shown below.
   
			  Crossplots of TOC versus Gc for
			Tight Gas / Shale Gas examples. Note the large variation in Gc versus
			TOC for different rocks, and that the correlations are not always
			very strong. These data sets are from core samples, cuttings give
			much worse correlations. The fact that some best fit lines do not
			pass through the origin suggests systematic errors in measurement or
			recovery and preservation techniques.
 
					
					
					
					 PASSEY'S "DlogR"
			METHOD Various multi-curve methods for quantifying organic content from well logs have
			been published, including multiple regression, probabilistic, and
			neural network solutions. The most common method is based on sonic versus resistivity,
			as described in "A Practical
			Model for Organic Richness from Porosity and Resistivity Logs" by Q. R. Passey,
			S. Creaney, J. B. Kulla, F. J. Moretti
			and J. D. Stroud,  AAPG Bulletin, V. 74, P 1777-1794, 1990.
 
					
			It is also known as the "D log R" method
			(with or without spaces and hyphens between the characters). The "D"
			was originally the Greek letter Delta (ΔlogR).  
			Although the sonic resistivity model is the best known version of
			the Passey method, density and neutron data can also be used, as
			shown below:1: SlogR = log (RESD / RESDbase) + 0.02 * (DTC –
			DTCbase)
 2: DlogR = log (RESD / RESDbase) -- 2.5 * (DENS –
			DENSbase)
 3: NlogR = log (RESD / RESDbase) + 4.0 * (PHIN –
			PHINbase)
 
 4: TOCs = SF1s * (SlogR * 10^(0.297 – 0.1688 * LOM))
			+ SO1s
 5: TOCd = SF1d * (DlogR * 10^(0.297 – 0.1688 * LOM))
			+ SO1d
 6: TOCn = SF1n * (NlogR * 10^(0.297 – 0.1688 * LOM))
			+ SO1n
 
 Where:
 RESD = deep resistivity in any zone (ohm-m)
 RESDbase =  deep resistivity baseline in non-source rock (ohm-m)
 DTC = compressional; sonic log reading in any zone (usec/ft)
 DTCbase = sonic baseline in non-source rock (usec/ft)
 DENS = density log reading in any zone (gm/cc)
 DENSbase = density in non-source rock (gm/cc)
 PHIN = neutron log reading in any zone (fraction)
 PHINbase = neutron baseline in non-source rock (fraction)
 SlogR, DlogR, NlogR =
			Passey’s
			number from sonic, density, neutron log (fractional)
 LOM = level of organic maturity (unitless)
 TOCs,d,n = total organic carbon from Passey method (weight fraction)
 SF1s,d,n and SO1s,d,n = scale factor and scale offset to calibrate to lab values of TOC
 
 Divide metric
			DTC values by 3.281 to get usec/ft, metric density by 1000 to get
			gm/cc.
 
 In practice, it is rare to have
			both TOC laboratory measurements and reliable organic maturity data
			to assist in calibration. Chose a value for LOM that will result in
			a match with available TOC data.
			Vitrinite reflectance (Ro) values may be available and are converted
			to LOM with the graph below.  LOM is typically in the range of
			6 to 14. Default LOM for a gas shale is 8.5 and fir an oil shale
			is10.5.
 
			 Graph for finding Level of Organic
			Maturity from Vitrinite Reflectance. Higher LOM reduces calculated
			TOC. Some petrophysicists do not
			believe this chart,  and use regression techniques on measured TOC to
			estimate LOM - see bottom illustration on this page for an example.
 
					
					
					 Numerical Example: RESD   RESDbase   DTC   DTCbase   LOM   DENS   DENSbase   PHIN   PHINbase
 25         4               100         62          8.5      2.35        2.65          0.34    0.15
 
 DTC    	DENS    PHIN
 DlogR =  1.556   	1.546    	1.556
 TOC    =  0.113    0.113    	0.113	weight fraction
 
 
					
					
					
					 ISSLER'S METHOD Dale Issler published a model specifically tuned to Western Canada
			in "Organic
					Carbon Content Determined from
					Well Logs: Examples from Cretaceous Sediments of Western
					Canada" by Dale Issler, Kezhen Hu,
					John Bloch, and John Katsube, GSC Open File 4362. It is based on density vs resistivity and sonic
					vs resistivity crossplots (other methods are also described
					in the above paper).
 
					The crossplots were redrafted in
					Excel , as shown below, and a drop-through code developed to
					generate TOC, based on the lines on the graphs. No doubt
					there is a simpler way to code this, but I didn't have time
					to sort it out.  ◄
						DTC vs RESD
 
					DENS vs RESD
						 ►
						   
					
					Note that sonic and density data are in Metric
					units. 
					
					TOC calculated from DENS vs RESD crossplot gives similar
					results to the sonic approach, but the density model should
					not be used in large or rough borehole intervals. Intervals
					where the sonic log is skipping should be edited before use. 
					The
					"drop-through" code shown below gives integer values of
					TOC%, then coverts it to a decimal fraction. Multiple
					regression equations, developed by Tristan Euzen from the
					Issler graphs, give
					smooth (non-integer) values and are of course easier to code
					into petrophysical software or spreadsheet packages. Thanks
					for your work Tristan.  
					
					
					 TOC FROM REGRESSION ANALYSIS OF ISSLER'S GRAPHS Tristan Euzen's multiple regression gives:
 7: TOCs = 
					
					0.0714 * (DTC + 195 * log(RESD)) - 31.86
 8: Wtocs = SF2 * TOCs / 100 + SO2
 
 Equations for the density-resistivity model are not quite as
					neat. By linear regression, Tristan found:
 97: 
					
					Intercept = 4.122 * Slope + 1014
 98: TOCd = -0.1429 * Slope + 45.14
 Recognizing that:
 99: DENS = Slope * Log(RESD) + Intercept
 And by substitution:
 9: TOCd = -0.1429 * (DENS – 1014) / (log(RESD) + 4.122) + 45.14
 10: Wtocd = SF3 * TOCd / 100 + SO3
 
					Log analysis TOC results
					should be calibrated to lab measured TOC from real
					rocks. Scale factors SF 2 and SF3 and scale offset SO2 and
					SO3 are determined by regression of lab versus log derived
					TOC values. If you want TOC%, remove the "/ 100" from
					equations 8 and 10. 
					
					
					
					 TOC FROM MULTIPLE LINEAR REGRESSION Sometimes it is difficult to get a good match to measured
					TOC values using Passey or Issler methods. Some software
					packages have multiple linera equation solvers. that can
					help. Here is a typical solution for one particular well
					where such a regression was run:
 11: TOCmr = - 3.73089 + 0.0259051 * DTC + 1.13726
					* PHIN_SS + 0.877866 * log(RESD)
 - 0.000722865 * DENS
 
 No scale factor or scale offset is needed as the equation is
					derived from the measured data.
 
					
					
					
					 TOC from Sonic Resistivity Crossplot TOC from Sonic Resistivity Crossplot
 IF DELT <= (-195 * LOG(RESD) + 460) THEN TOCs = 0
 IF DELT > (-195 * LOG(RESD) + 460) THEN TOCs = 1
 IF DELT > (-195 * LOG(RESD) + 474) THEN TOCs = 2
 IF DELT > (-195 * LOG(RESD) + 488) THEN TOCs = 3
 IF DELT > (-195 * LOG(RESD) + 502) THEN TOCs = 4
 IF DELT > (-195 * LOG(RESD) + 516) THEN TOCs = 5
 IF DELT > (-195 * LOG(RESD) + 530) THEN TOCs = 6
 IF DELT > (-195 * LOG(RESD) + 544) THEN TOCs = 7
 IF DELT > (-195 * LOG(RESD) + 558) THEN TOCs = 8
 IF DELT > (-195 * LOG(RESD) + 572) THEN TOCs = 9
 IF DELT > (-195 * LOG(RESD) + 586) THEN TOCs = 10
 IF DELT > (-195 * LOG(RESD) + 600) THEN TOCs = 11
 IF DELT > (-195 * LOG(RESD) + 614) THEN TOCs = 12
 IF DELT > (-195 * LOG(RESD) + 628) THEN TOCs = 13
 IF DELT > (-195 * LOG(RESD) + 642) THEN TOCs = 14
 IF DELT > (-195 * LOG(RESD) + 656) THEN TOCs = 15
 IF DELT > (-195 * LOG(RESD) + 670) THEN TOCs = 16
 IF DELT > (-195 * LOG(RESD) + 684) THEN TOCs = 17
 IF DELT > (-195 * LOG(RESD) + 698) THEN TOCs = 18
 IF DELT > (-195 * LOG(RESD) + 712) THEN TOCs = 19
 IF DELT > (-195 * LOG(RESD) + 726) THEN TOCs = 20
 IF DELT > (-195 * LOG(RESD) + 740) THEN TOCs = 21
 IF DELT > (-195 * LOG(RESD) + 754) THEN TOCs = 22
 IF DELT > (-195 * LOG(RESD) + 768) THEN TOCs = 23
 IF DELT > (-195 * LOG(RESD) + 782) THEN TOCs = 24
 Wtocs = SF2 * TOCs / 100 + SO2
 
					
					
					
					 TOC from Density Resistivity Crossplot IF DENS < (150 * LOG(RESD) + 1670) THEN TOCd = 24
 IF DENS < (155 * LOG(RESD) + 1695) THEN TOCd = 23
 IF DENS < (160 * LOG(RESD) + 1720) THEN TOCd = 22
 IF DENS < (166 * LOG(RESD) + 1745) THEN TOCd = 21
 IF DENS < (170 * LOG(RESD) + 1770) THEN TOCd = 20
 IF DENS < (176 * LOG(RESD) + 1795) THEN TOCd = 19
 IF DENS < (183 * LOG(RESD) + 1820) THEN TOCd = 18
 IF DENS < (190 * LOG(RESD) + 1845) THEN TOCd = 17
 IF DENS < (197 * LOG(RESD) + 1870) THEN TOCd = 16
 IF DENS < (211 * LOG(RESD) + 1895) THEN TOCd = 15
 IF DENS < (218 * LOG(RESD) + 1920) THEN TOCd = 14
 IF DENS < (225 * LOG(RESD) + 1945) THEN TOCd = 13
 IF DENS < (232 * LOG(RESD) + 1970) THEN TOCd = 12
 IF DENS < (239 * LOG(RESD) + 1995) THEN TOCd = 11
 IF DENS < (246 * LOG(RESD) + 2020) THEN TOCd = 10
 IF DENS < (253 * LOG(RESD) + 2050) THEN TOCd = 9
 IF DENS < (260 * LOG(RESD) + 2080) THEN TOCd = 8
 IF DENS < (267 * LOG(RESD) + 2110) THEN TOCd = 7
 IF DENS < (274 * LOG(RESD) + 2140) THEN TOCd = 6
 IF DENS < (281 * LOG(RESD) + 2170) THEN TOCd = 5
 IF DENS < (288 * LOG(RESD) + 2200) THEN TOCd = 4
 IF DENS < (295 * LOG(RESD) + 2232) THEN TOCd = 3
 IF DENS < (302 * LOG(RESD) + 2264) THEN TOCd = 2
 IF DENS < (309 * LOG(RESD) + 2300) THEN TOCd = 1
 IF DENS >= (309 * LOG(RESD) + 2300) THEN TOCd = 0
 Wtocd = SF3 * TOCd / 100 + SO3
 
					Log analysis TOC results
					should be calibrated to lab measured TOC from real
					rocks. Scale factors SF 2 and SF3 and scale offset SO2 and
					SO3 are determined by regression of lab versus log derived
					TOC values. If you want TOC%, remove the "/ 100" from the
					final equations. 
					
					
					 Numerical Example RESD      DTC      DENS  
			Using spreadsheet from Downloads page
 English       25           100         2.35
 Metric         25          
			328         2350
 
 TOCs (RESD-DTC crossplot)    = 0.11   weight fraction
 TOCd (RESD-DENS crossplot)  = 0.10   weight fraction
 
 
 
  META/LOG "TOC" SPREADSHEET
			-- TOC ASSAY FROM LOG ANALYSIS This
			spreadsheet calculates Total Organic Carbon (TOC) from the two
			different models described above.
 
						
						
			
			SPR-13 META/LOG ORGANIC CARBON (TOD) CALCULATORCalculate total organic carbon (TOC), Passey, Issler,
						5 Methods
 
  Sample output from META/LOG "TOC" spreadsheet for analysis of Total
			Organic Carbon from well logs.
 
 
			
					
					
					
					
					 TOC From SpectrAL GAMMA RAY Log 
			
			The uranium content of many kerogen bearing source and reservoir
			rocks is often a function of the kerogen content. Bob Everett
			suggests the following relationship:1: TOCuran = SFuran * log(URAN / 4)
   
			Where:TOC uran = total organic carbon from uranium curve on spectral GR loh
			(fractional)
 URAN = uranium content (ppm)
 SFuran = scale factor = 0.05 default (range 0.02 to 0.08)
 
 Calibrate SFuran using lab derived TOC data. Note that the spectral
			GR could be a core GR log.
 
					
					
					
 
  TOC From Elemental Capture Spectroscopy (ECS) Logs 
			
			The ECS log measures the weight contribution of various elements in
			the formation, for example calcium, oxygen, iron, silicon, and so
			forth. By using a least squares statistical approach, the elements
			can be composed into the minerals that might be present in the
			rocks. One of the minerals can be kerogen. Results are in weight
			fraction so kerogen can be compared directly to geochemical assays
			from the lab. The TOC and XRD or XRF lab data can be used to
			constrain the inversions, giving results that will naturally match
			kerogen and mineralogy data quite well. An example is shown at the
			end pf this web page. 
					
					
					
					 TOC LOG ANALYSIS EXAMPLES 
					
			 TOC calculated from Passey DlogR Method. There are numerous
			published examples with much worse correlations between calculated
			and measured TOC, usually attributed to varying proportions of Type
			I, II, and III kerogen or mineral variations (calcite, dolomite,
			pyrite, and quartz) in the shale.
 
			
			 The figure above shows a comparison of the DlogR method with the
			Issler model. Both methods use sonic and resistivity logs to
			calculate the depth variation in TOC. Red dots represent measured
			TOC analyzed on core
 samples using a Rock-Eval 2 instrument; blue dots represent
			re-analyses of the same samples using a Rock-Eval 6 instrument. For
			the Issler model, results are presented for both empirical (blue)
			and Archie (green) resistivity porosity methods. The DlogR method
			gives poor results for this well when observed thermal maturity is
			used (LOM = 5.0) An LOM value of 6.9 provides a good fit to the data but
			it is not representative of the true maturity.
 
				 
  
  A nuclear magnetic effective porosity curves
				(light grey on porosity track) shows a close match to shale and
				kerogen corrected density-neutron effective porosity (left edge of red shading).
				Dark shading on porosity track is kerogen volume. NMR porosity, and corrected effective porosity
				match very well. The NMR effective porosity is unaffected by
				kerogen and clay bound water. The far right
				hand track is the mineralogy from an Elemental Capture
				Spectroscopy (ECS) log in weight fraction (excludes porosity but
				includes TOC). TOC from cores, Issler method, and ECS are in the
				track to the left of the porosity. They also match quite well.
				The ECS inversion was also calibrated to TOC and XRD data to get a match
				as good as this. Clay volume in second track from the right is
				from thorium curve calibrated to XRD total clay, with clay
				volume from ECS superimposed to show the close agreement.
				Everything makes sense when you CALIBRATE to lab data but may be
				NONSENSE if you don't gather the right data.
 
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