Total Organic Carbon

Possible delayed emission of S1 products may adulterate the S1 and S2 signals, requiring that this possibility be considered during ROCK EVAL pyrolysi...
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Energy & Fuels 1996, 10, 905-914

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Disentanglement of Hydrogen Index and S1/Total Organic Carbon Variations with Depth B. Mudford* Unocal Corporation, Sugar Land, Texas 77478

I. Lerche Department of Geological Sciences, University of South Carolina, Columbia, South Carolina 29208 Received November 16, 1995. Revised Manuscript Received May 7, 1996X

Many workers, especially in coal studies, have suggested that changes which occur during pyrolysis studies could lead to mobile components being retained within the macromolecular network, rather than being instantaneously released. This process has the potential to cloud the results from ROCK EVAL pyrolysis. We present a procedure that can be used to disentangle the effects of delayed emission of mobile components during ROCK EVAL pyrolysis. This procedure is illustrated using four wells from East Kalimantan, Indonesia, which have hydrogen index (HI) vs depth curves that increase with depth, contrary to conventional expectations. The disentanglement procedure developed in this paper is used to show that delayed emission may be an explanation for the anomalous HI vs depth behavior in these wells. Possible delayed emission of S1 products may adulterate the S1 and S2 signals, requiring that this possibility be considered during ROCK EVAL pyrolysis data analysis.

I. Introduction In conventional ROCK EVAL pyrolysis studies1 on whole rock samples, the total organic carbon (TOC) per unit mass of rock is measured. Samples are progressively heated and extracts recorded at increasing temperatures. The first extract group, labeled S1 (mg/g of rock), is conventionally taken to represent thermally labile hydrocarbons present in the sample prior to laboratory heating; the second extract group, labeled S2 (mg/g of rock), is taken to represent the hydrocarbons released upon thermal breakdown in the laboratory of the nonvolatile TOC in the sample and so records the remaining potential of the rock (per unit mass of TOC) for producing hydrocarbons. It then follows that, in the absence of migration, a suite of rocks from increasing burial depths should record an S1/TOC variation which increases with depth and also an S2/TOC variation which decreases with depth of burial. These twin requirements imply that all the hydrocarbons produced in the sample prior to laboratory heating are released in the recorded S1 extract group and also implies that all S2 is released and not absorbed into the rock matrix. However, two aspects of kinetic models describing the thermocatalytic breakdown of organic matter suggest that a potential problem can occur in the disentanglement of the observed pyrolysis extract groups. The two kinetic aspects which indicate the likelihood of such a problem are the following: (i) Modern kinetic thermocatalytic breakdown models of degradation consist of multiple reaction pathways (taken in parallel, series, or combinations), each with Abstract published in Advance ACS Abstracts, June 15, 1996. (1) Espitalie, J.; Madec, M.; Tissot, B. Source rock characterization method for petroleum exploration, 9th Annual Offshore Technology Conference, Houston, TX, 1977.

its own frequency factor, activation energy, and fractional contribution factor to the overall breakdown. Thus, under a heating and/or cooling experiment, the implication is that there must be a “spread” in amount and type of products produced with increasing temperature. In turn, this intrinsic product variability with temperature (which is required in the distributed activation energy kinetic models) suggests that not all of the S1 observed is in the sample prior to laboratory heatingsa fraction could be produced while the experiment is ongoing. Equally, a distributed activation energy model suggests that a fraction of the TOC could convert to hydrocarbons at temperatures lower than those for the nominal S2 extract groupsso that the observed S1 could contain a component from hydrocarbon production during the experiment. (ii) The second kinetic aspect which suggests an examination of potential entanglement of observed S1 and S2 measures comes from the coal literature. Derbyshire and Davis2 have noted that “Pyrolysis will cause certain, formerly mobile, components to be incorporated into the residue by condensation and crosslinking reactions. Similarly, components of the macromolecular network will be liberated.” Snape and Bartle3 have also commented that “The question then arises as to whether the range of molecular masses present in coal is a continuum, with no real distinction between molecular and macromolecular components.” And in the same connection, Derbyshire and Davis2 have pointed out that “Logically, it is to be expected that there will be a gradation in the manner in which the smaller

X

S0887-0624(95)00230-1 CCC: $12.00

(2) Derbyshire, F.; Davis, A. Fuel 1989, 68, 1095, 1103. (3) Snape, C.; Bartle, K. Fuel 1989, 68, 1105.

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molecules are associated with the (macromolecular) network. This may involve both physical and chemical forces such as covalent bonds, dispersion forces, and hydrogen bonding, and could also involve physical entrapment. It is doubtful whether any single technique can distinguish between these different modes of entrapment sufficiently clearly to establish a precise boundary.” The point being made is that there can be delayed release of pre-existing S1 types of extracts while there can also be prompt production of S2 types of extracts at lower temperature ranges than the conventional picture would indicate. Evidence for this type of behavior has also been given by Monthioux and Landais,4 who observed free, but trapped, hydrocarbons in coal samples from the Mahakam Delta. From both kinetic aspects, the potential for admixtures of S2 products in the S1 temperature range, and of delayed release of S1 occurring at the S2 temperature range, implies that some practical procedure must be developed to disentangle the intrinsic S1 and S2 groups from observed S1 and S2 extract measurements. There is, to be sure, a likelihood that the majority of entrapped hydrocarbons (the “mobile phase” of Derbyshire and Davis2) are released under pyrolysis at the lower temperature range of the S1 extract, else the ability would have been compromized long ago to use S1 and S2 pyrolysis measurements as fairly rugged indicators of hydrocarbon potential. Although the majority of mobile phase material is likely to be extracted at the S1 temperature range, this does not exclude the likelihood that a minority fraction can appear at a higher temperature range. Hence, one must devise a procedure that enables a quantitative estimate to be made of the minority fraction (including zero fraction as an option) from observed extract information. An increase of hydrogen index (HI) with depth during the diagenetic phase of maturation has been observed by many authors5 and a variety of explanations have been proposed for this phenomena. An initial increase of HI with depth can be due to the preferential loss of kerogen moieties that yield CO2 and H2O and the consequent increase in the preponderance of hydrocarbonyielding moieties. An additional factor to consider is that the flame ionization detector (FID) of the ROCK EVAL instrument detects hydrocarbons but not CO2 and H2O. The products of kerogen cracking can also play a role in the S2 yield during ROCK EVAL pyrolysis. Ashphaltenes, or polar compounds, are intermediate products on the continuum between kerogen and generated hydrocarbons, and they can contain a large fraction of the petroleum potential,6 especially in Type III organic matter. Mansuy et al.6 have also shown that the maturation behavior of coals may be sensitive to the nature of the reacting medium and the presence, or absence, of ashphaltenes and generated hydrocarbons within the residual kerogen matrix. Hence, anomalous variations in HI may also be caused by variations in the composition of the reacting medium. A further important consideration when using HI data is that the HI of the individual macerals making up the organic matter will combine together to give the (4) Monthioux, M.; Landais, P. Fuel 1987, 66, 1703-1708. (5) Horsfield, B.; Yordy, K. L.; Crelling, J. C. Org. Geochem. 1987, 13, 121-129. (6) Mansuy, L.; Landais, P.; Ruau, O. Energy Fuels 1995, 9, 691703.

Mudford and Lerche

HI of the sample as a whole. Landais7 has calculated the HI of individual macerals from infrared data for a Mahakam coal and found a significant spread from vitrinite to bituminite. Hence, variations in maceral composition, or organic facies, could lead to anomalous patterns of HI variability with depth (maturity). The quantitative analysis of anomalous patterns of S1 and S2 maturity due to variations in TOC and of organic facies within a sedimentary section has been presented by Huc et al.8 and Cao and Lerche.9 In the cases where facies or maceral variations give rise to anomalous HI variations with depth, endmember analysis procedures10 can be used to estimate the individual end-member components and their fractional contributions to the total TOC. However, as is often the case in geology, it may not be possible to unequivocally say that one mechanism or the other is causing the observed anomalous pattern. The geology of the area would need to be used as a guide to determining which mechanism was dominant. The important question is whether the actual mechanism matters in terms of the exploration questions we wish to have answered. Clearly, as has been set out above, there are a number of possible reasons for the anomalous behavior of increasing HI with depth. Many of these possible reasons can be refuted or accepted by more detailed geochemical studies. However, in an exploration setting, one is often faced with a suite of geochemical screening data, including ROCK EVAL pyrolysis data, and asked to draw some conclusions about the petroleum system. In many cases, when anomalous data are contained within the available data set for a well, the only response is to ignore the anomalous data. We hope to show in this paper that in some cases these anomalous data can be analyzed to provide useful information about the petroleum system. An important caveat is that these anomalous data must always be analyzed with due attention to the geology of the area in question. The purpose of this paper is to show that one of the possible mechanisms for anomalous HI variations with depth, namely the potential mixing of observed S1 and S2 extracts, can be quantitatively analyzed so that one is more certain either that no entanglement took place or that one can estimate quantitatively the degree of entanglement. In addition, the procedure is applied to a typical suite of exploration data from the Mahakam Delta. II. Basic Framework A. General Arguments. The scenario we wish to analyze is as follows. Produced S1 material will not be released from the sample until a leakage pathway exists, possibly created by matrix fracturing. Hence, the observed S1 may be only some fraction of the preexisting S1, while the measured S2 extract presumably contains not only S2 hydrocarbons produced by labora(7) Landais, P. Org. Geochem. 1995, 23, 711-720. (8) Huc, A. Y.; Lallier-Verges, E.; Bertrand, P.; Carpentier, B.; Hollander, D. J. Organic Matter: Productivity, Accumulation, and Preservation in Recent and Ancient Sediments; Whelan, J., Farrington, J. W.; Columbia University Press: New York, 1992; pp 469-486. (9) Cao, S.; Lerche, I. App. Geochem. 1994, 9, 93-117. (10) Full, W. E.; Williams, D. F.; Lerche, I. Isotope Chronostratigraphy: Theory and Methods; Academic Press: SanDiego, CA, 1986; 345 pp.

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Energy & Fuels, Vol. 10, No. 4, 1996 907

tory pyrolysis of the nonvolatile TOC but also that component of the S1 which could not promptly escape at the temperature range recorded for the observed S1 extract. While the intrinsic S2 material will decrease for a more deeply buried sample, the S1 (if all retained) will increase, so that the determined HI (hydrogen index ) S2 (measured)/TOC × 100) will reflect the increasing S1 which has been delayed in its release by some form of entrapment. Thus the HI will then tend to increase with depth; again noting that it is assumed that the TOC has been constrained to be of only one organic facies. The determination of a hydrocarbon kinetic framework from such measurements is then compromised, unless a procedure can be found for unscrambling the true S2 and true fractional variations with depth from a sequence of S1/TOC and S2/TOC measurements from a suite of samples at increasing depth. Consider a sample from depth z, containing a measured amount of TOC. Under pyrolysis heating, let the fractional amount f(z) S1(z) be produced as the first low temperature range extract, where S1(z) is the amount that would be produced if there were no retention of the S1 material. Then

Such a simplified procedure operates as follows. Write

S1(observed,z)/TOC ) f(z)(S1(z)/TOC)

Note that X2 is quadratic in S* and f*-1 so that for fixed values of a and R, X2 has minima with respect to variations in S* and f*-1 at

(1)

Under continued heating, the remaining S1 material is produced (≡(1 - f(z)) S1(z)) plus all the S2 material (≡S2(z)) and, together, they are recorded as S2(observed,z) i.e.

HP(z) ≡ f(z) s1(z)

(3a)

HI(z) ) s2(z) + (1 - f(z)) s1(z)

(3b)

(5a)

s2(z) ) S* exp(-az)

(5b)

and

with the enforced requirements that a > 0, 0 < S* < 1, and f* exp(RzN) < 1. The job here is to obtain values for f*, S*, R, and a from the data. The idea is to obtain rough trend information which can then be used in the more sophisticated nonlinear iteration procedure given above should data resolution warrant such considerations. The additional problem of including the mixing of material from the S2 peak with that in the S1 peak is solved in the supporting information, part B. To obtain the four parameters f*, S*, R, and a, construct X2 as

X2 )

N

1

∑ [M(zn) - S* exp(-azn) Nn)1 HP(zn)f*-1 exp(-(Rzn))]2 (6)

N

S* ) [

S2(observed,z)/TOC ≡ (1 - f)(S1(z)/TOC) + (S2(z)/ TOC) (2) For brevity, denote S2(observed,z)/TOC by HI(z), S1(observed,z)/TOC ) HP(z); S1(z)/TOC ≡ s1(z), S2(z)/TOC ) s2(z), then eqs 1 and 2 are

f(z) ) f* exp(Rz)

N

M(zn) exp(-azn) - f*-1 ∑ HP(zn) × ∑ n)1 n)1 N

exp(-2azn))-1 ∑ n)1

exp(-zn(R + a))]( with N

f*-1 ) [{

∑HP(z ) exp(-z (R + a))}

N

2

n

n

-(

n)1

exp(-2Rzn))(

(4)

exp(-zn(R + a))}{

2

n

×

∑exp(-2az ))] [{∑HP(z ) × -1

n

n)1 N

Using eq 3a in eq 3b yields

∑HP(z )

n)1 N

N

M(z) ≡ HI(z) + HP(z) ) s2(z) + HP(z)/f(z)

(7a)

n

n)1

N

∑M(z

exp(-azn))} - (

n

n)1

∑exp(-2az ))× n

n)1 N

Two factors are manifest: first, the fraction f(z) must be less than unity, and second, s2(z) must be a decreasing function of increasing depth. Then, if HP(z) increases with depth, it follows from eq 4 that the hydrogen index, HI, must also increase with depth (provided f(z) < 1). The task is to determine s2(z) and f(z) using eq 4 from measurements of HI(z) and HP(z) at the suite of increasing depths (z1, z2, ..., zN), subject to the constraints ds2(z)/dz e 0, 0 e f(z) e 1, and 0 < s2(z) < 1, at all z. B. Approximate Procedures. The nonlinear procedure given in the supporting information, part A, is highly effective in providing a minimum as has been demonstrated many times for a wide variety of problems.11 Yet, it may be that a less sophisticated method is desired in order to obtain a quick overview of likely resolution of behaviors without the attendant need for a massive in-depth analysis of every quirk of the data. (11) Lerche, I. Q. Appl. Math., in press.

(

∑M(z ) HP(z ) exp(-az ))] n

n

n

(7b)

n)1

The values of S* and f*-1 given by eqs 7 minimize X2 for each a,R pair. So, by running a two-dimensional search on a and R, the minimum of all minima of X2 can be found. The requirements that f(z) < 1 and s2(z) < 1 can then be checked for consistency and the bestfitting behavior for s2(z) and f(z) obtained. Two factors dictate that, while this approximate procedure will lead to minimum mismatches of predicted and observed variations of S1/TOC and HI with depth, nevertheless the procedure is not optimal: first, there is the intrinsic assumption that s2(z) is taken to be of exponentially declining variation with increasing depth, z; second is the intrinsic assumption that the fraction f(z) is also exponentially varying in behavior. There is no particularly good reason for these twin assumptions, so a minimum value of X2 represents only a minimum within the class of one-parameter exponential variations with depth.

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However, the fact that minima can be achieved at all does indicate that the presumption of delayed release of the S1 material is appropriate. Further, the value of the mismatch between predictions and observations indicates whether it is worthwhile to pursue the more sophisticated procedure outlined in the supporting information, which is not subject to the constraints of the approximate method. The point is that, if the mean square residual mismatch with the approximate procedure already produces a value close to the mean square fluctuations in the data, then one has exhausted the resolution of the data without the need for a more detailed description of the variation with depth that would be afforded by the sophisticated procedure. In that case there is no point in refining the predicted behavior any further. III. Illustrative Examples In order to provide an idea of the practical aspects of the manner in which the disentanglement procedure can be used, four wells from the Mahakam Delta were made available for this study, each with observed HI(z) and observed S1/TOC variations with depth. These data are typical exploration data, having come from a variety of contractors results, taken over a period of about 10 years. Observations with TOC < 0.5% were excluded from consideration. The wells are labeled A, B, C, and D, in order to protect the proprietary locations. Shown in Figure 1a-p are the observed S1/TOC, HI, oxygen index (OI), and vitrinite reflectance (VR) variations with depth recorded for the four wells. Apart from the large fluctuations (of order ( 20 mg/gm) around a mean value, there is also a trend variation, observable even by eye, which indicates that both S1/TOC and HI increase systematically with increasing depth. This trend of increasing HI with depth is more pronounced in wells C and D, which penetrate a deeper, more mature section than do wells A and B. It should also be noted that HI increases with depth for maturities up to at least 0.6% Ro in wells C and D. This contrasts with the oft-quoted maturity interval of VR e0.5% Ro for which HI increases with depth. One has to be aware of the potential for organic facies variation through the section. The shallow section is more controlled by upper delta sediments as compared to the lower section, where pro-delta and lower delta plain sediments are in the majority. Liptinitic and amorphous organic matter are likely to enrich the lower delta sediments, while the upper delta is likely to contain more vitrinite-type organic material. Then, as remarked earlier, one must obtain the endmember fractions for TOC measurements with depth of the same organic facies in order to ensure that variations of S1 and S2 with organic facies types are not the main, or even sole, cause of observed behaviors. Nevertheless, for illustrative purposes, it is at the least instructive to examine the consequences of considering that the observed variations of S1/TOC and S2/ TOC with depth in the four wells are a result of delayed emission in the sense of Derbyshire and Davis.2 Within that framework, while conventional theory argues that S1/TOC should increase steadily with increasing depth, theory equally argues that HI should decrease steadily with increasing depth, contrary to the observed behavior. This anomaly in behavior of HI in the four wells can be used to infer that not all the generated S1 is being released at the conventional S1 peak.

Mudford and Lerche

For each of the wells in turn, contour plots of constant X2 were generated as functions of R and a. Represented in Figure 2a-d are the departures (in percent) of the variation in (X2)1/2 above the minimum value for each well. Contour lines at 10% and 5% above minimal values are drawn on Figure 2, indicating that a mean square residual minimum mismatch of 13-30 mg/gm is achieved throughout the depth range of the data. If 10% uncertainty is allowed in values of measured HI (a conservative error), then the curves displayed indicate the ranges of a and R values allowed. Table 1 presents three representative points of a and R: the maximum possible R value (and the attendant a value), the minimum possible R value (and the attendant a value), and the maximum possible a value (with the attendant R value), all for the 10% contour. For each R,a pair, in turn, the behavior of predicted versus observed HI is sketched for each well, as shown in Figure 3a-d. To be noted from Figure 3 is that, while each curve is at the minimum value of root mean square X2, all the curves are not equally parallel to the data, although each has the same average mismatch overall. For example, in the case of well B, the curve for maximum R (which corresponds to a ) 0, or constant S2 ) S*) is a noticeably poorer fit to the variations in HI than are the curves for values of minimum R or maximum a, even though all three curves provide the same degree of fit (viz. 22 mg/gm root mean square mismatch). In the case of well D, all three extremes provide effectively the same degree of fit by eye to the data field, indicating that the resolution of the data has already been reached. For each of the three extremes (maximum R, minimum R, maximum a) the correspondence between observed and predicted hydrogen indexes with depth shows interesting patterns of variations for each of the four wells. To be noted from Figure 3 are two major points. First, the fit to the variations of HI with depth is generally significantly poorer for the case of maximum R (corresponding to constant S2(z) ) S*) than for the other two extremes. Second, well B is exceptional in that its observed HI is approximately 100-120 mg/gm TOC while its S1/TOC is only around 20-40 mg/gm TOC (Figure 1g); this behavior is in contrast to the wells A, C, and D in which the S1/TOC and HI values are roughly comparable in magnitude. For wells A, C, and D it is possible to obtain relatively good fits to the observations because a significant fraction of S1/TOC can be in the S2/TOC temperature regime; but, such is not possible in the case of well B for which S1 is, on average, no more than about a maximum of 25% of S2. For well B the variation of the observed HI starts at a low value at shallow depths and has an increasing trend with increasing depthsindicative of mixing. The implications are either that the S2/TOC data for well B are poorly taken (cave-ins, reworked, poorly measured, etc.) or that some cause other than mixing must be contributing to the observed behavior (organic facies variation, rock type, weathering, etc.). In the cases of wells A, C, and D, a satisfactory fit is achieved with the mixing fraction premise and it appears that the observed HI and S1/TOC curves can be modeled if approximately 20% of the S1 material is retained within the rock matrix and emitted in the S2 peak.

Figure 1. (a-p) Observed S1/TOC, HI, OI, and vitrinite reflectance variations with depth for each of the four wells A, B, C, and D.

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Figure 2. (a-d) Contours of constant mismatch of predicted and observed behaviors, as per eq 13, drawn in an (a,R) space. The contour lines are taken at 10% and 5% above the minimum mismatch. The regions marked “forbidden zone” correspond to combinations of R and a that would give fractions greater than unity for the mixing. Table 1. Values of a,r Pairs Corresponding to 10% above Minimum Mismatch Values A+B+C+D C+D A+B C D A B

R

a

-0.17 -0.04 0.55 -0.14 0.19 0.56 -0.46 -0.02 0.46 -0.15 0.30 0.46 -0.43 -0.17 0.11 -0.545 -0.09 0.35 -0.25 0.05 1.00

1.16 1.20 0.00 0.68 1.16 0.00 1.68 1.02 0.24 1.08 1.20 0.00 1.12 0.76 0.00 2.7 1.17 0.00 0.405 0.435 0.105

Figure 4a-d shows the intrinsic S2/TOC variations (under the single-parameter exponential variation with depth assumption) for each well for the three extreme cases, and also exhibited are the fractions of prompt S1 corresponding to each extreme. To be noted from Figure 4 is that the prompt fractions are typically around 80% ( 10%, indicating that about 20 ( 10% of the S1 is delayedsalthough that fraction changes with depth. The 80% rough rule-of-thumb is valid for all four wells. The intrinsic S2/TOC variations show that wells A, C, and D have about 40-60 mg/gm TOC at shallow depths, decreasing at greater depths;

whereas well B shows the largest effect of the observed S2 behavior, with an intrinsic S2/TOC of around 100120 mg/gm TOC at shallow depths. Residual Kerogen Kinetics. First, note that, independent of the precise activation energy distribution, the fact that about one-third to one-half of S2/TOC is generated in the first 8000 ft requires an early seal if any reservoir formations are not to leak significantly; second, note that the inferred S2/TOC surficial values are around 100 mg/gm TOC so that the source rocks from these wells have relatively low hydrocarbon generation potential. The variations of intrinsic S2/TOC for each well are taken as representative of the ability of each gram of TOC to produce hydrocarbons. Thus the variation of S2/TOC is taken to parallel precisely the pyrolysis of kerogen and so to represent the residual kerogen available at each depth. In conjunction with a burial history and a thermal history for each well, the inverse technique of Cao and Lerche9 can then be used to invert the intrinsic S2/TOC variations in order to determine the residual kerogen kinetics (frequency factors, activation energies, and number of channels) necessary to account for the variations. For each of the three extreme cases, and for each of the four wells, such inversions have been performed with the thermal regime held at the present day constant heat flux for each well. In view of the rapid supply of sediment to the basin, and because the oldest sediments are less than about 10-15 My old, such a constant heat flux at each well site is an accurate enough approximation. The

Figure 3. (a-d) Predicted versus observed hydrogen indexes with depth for each of the four wells A, B, C, and D under the three extreme cases of maximum a, minimum R, and maximum R.

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Figure 4. (a-d) Intrinsic S2/TOC variations and fractional contributions of intrinsic S1/TOC with depth for each of the four wells A, B, C, and D and for each of the three extreme cases.

dominant temperature variation of a formation is then caused by rapid burial and/or overpressure development. The intrinsic S2/TOC variations with depth for each of the four wells and for each of the extreme cases, are given in Figure 5a-d, together with the intrinsic curves determined using the kerogen kinetics calculated from inversion. In addition, the activation energy distribution, the overall frequency factor, and the depositional surface value of S2/TOC are also displayed. Perhaps the dominant point to note is that (apart from the constant S2/TOC cases corresponding to maximum R and a values of zero) the activation energy distributions all require extremely low valuessof order 5-30 kcal/

molsto account for the intrinsic S2 behaviors. This pattern is not unexpected because Figure 4 shows that the intrinsic S2/TOC has decreased by about one-third to one-half of its surface value by around 6000-8000 ft of burial, corresponding to a temperature of about 7080 °C (mudline surface temperature is around 27 °C), so that early, low-temperature catagenesis appears to be occurring. Such low temperatures require either a high frequency factor or a low activation energy distribution, or both of course. As can be seen from Figure 5, the inverse method produces fits to the intrinsic S2/ TOC variations with depth which are best served by a low activation energy distribution for all four wells for each of the extreme end-member situations (minimum

Figure 5. (a-d) (i) Predicted versus intrinsic S2/TOC distributions with depth for wells A, B, C, and D and for the two extreme cases of minimum R and maximum a, respectively; (ii) activation energy distributions derived from the inverse procedure.

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Figure 6. Plot of mean square residual versus minimum activation energy showing the need for a low activation energy.

R, maximum R) except for the exceptional case of constant S2/TOC. This result was confirmed by varying the minimum activation energy permitted and obtaining the best fit for that minimum. A plot of mean square residual versus minimum activation energy (Figure 6) shows that a low minimum activation energy is required, consistent with implications from the observed variations of early shallow, hydrocarbon production. The clustering of the activation energies about low values also indicates that the organic matter giving rise to low intrinsic HI’s will have generated most of its available hydrocarbons at relatively low levels of maturity (approximately 0.7% Ro to 0.9% Ro). If such a low-temperature situation for kerogen production is common, then not only must laboratory pre-processing preparation conditions of kerogen be adjusted so as not to remove the low activation energy extract but the onset temperature for pyrolysis must be lowered, and the sample held at low temperatures, until it is sure that no S1 peak is available or until it has been completely extracted. Then, and only then, can one move the sample to higher temperatures to obtain an S2 peaksbut with the proviso that delayed S1 material may be also being recorded in the S2 measurements.2 IV. Discussion and Conclusions Several factors emerge from the analysis of the S1/ TOC and HI measurements with depth. First, the observed increase of HI with depth can be accounted for if a fraction of the prior-generated S1 is delayed in its emission under laboratory pyrolysis studies. In turn this delay in emission requires that the recorded HI variation be “unscrambled” to determine that component of the HI measurements which represents an intrinsic S2/TOC signal from the fractional admixture of delayed S1/TOC, and the fraction must itself be determined. This paper has provided procedures for performing the disentanglement. Second, application of the disentanglement technique to data from four wells shows that the contributions to the observed HI of S1 and of intrinsic S2/TOC are not absolutely uniquesa degree of ambiguity remains.

Mudford and Lerche

Nevertheless, both the original HI data and the intrinsic S2/TOC variations with depth indicate early, shallow generation of hydrocarbons with about 20% ( 10% admixture of delayed S1/TOC to S2/TOC. Third, the shallow, early hydrocarbon generation implies a low activation energy distribution for production, and this implication was confirmed both by using an inverse procedure on the intrinsic S2/TOC for the four wells (which gave activation energies in the 5-30 kcal/mol range) and by running laboratory pyrolysis on samples at low temperatures (∼180 °C) when a significant S1 peak was recorded,12 implying once again low activation energies for the generation of hydrocarbons. The hydrocarbon generation characteristics of the organic matter in the wells studied imply a relatively low potential for generating hydrocarbons. As this is a wellknown hydrocarbon system, it may be that the geochemical analyses of the wells used in this study have not captured the total generative capacity of source rocks in this area but are depicting the source potential of a component that may not volumetrically represent a high proportion of the reservoired hydrocarbons. Further, more detailed geochemical work would be required to place the results obtained in this paper in a regional context. However, the methods outlined in this paper can be applied irrespective of the volumetric importance of the generative component being studied. Apart from the detailed and specific application to the Mahakam Delta region as an illustration of the disentanglement procedure and the inferences that can then be made, two dominant factors of general interest are (i) the inclusion of prior-generated S1 in HI measurements may be of a more prevalent concern than just for the Mahakam Delta data; (ii) the early generation of hydrocarbons and the associated low activation energies may also be of a more general nature, and one should, at the least, be aware that such effects can exist. The determination of hydrocarbon kinetics from S2/ TOC measurements requires that no multiple sources of kerogens subject to different kinetics be present or, if there are multiple sources, then an unmixing procedure must first be applied. The present work would also suggest that, even in the case of a single kerogen type, care should be taken to ensure that all possible adulteration of the HI signature by delayed S1 material should be removed prior to using the HI variations to infer kinetic descriptions of kerogen catalysis to hydrocarbons, else results obtained will be less than unassailable. Acknowledgment. The work reported here was supported by the Industrial Associates of the Basin Modeling Group at USC and especially by Unocal Corp. We thank Unocal for data release and publication permission. We also acknowledge the input of two anonymous reviewers. Supporting Information Available: Details of experimental procedures (8 pages). See any current masthead page for ordering information. EF950230C (12) Jarvey, D. Private communication, 1993.