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Estimation on organic carbon content of source rocks by logging evaluation method as exemplified by those of the 4th and 3rd members of the Shahejie Formation in western sag of the Liaohe Oilfield
Abstract
One of the most important tasks of evaluating natural resources of petroliferous basins is to determine the organic matter abundance of source rocks in the basin. The usual method for assessing the organic carbon content of source rocks is based on laboratory analyses. There is a deviation in calculating organic carbon content due to the heterogeneous distribution of organic matter and the artificial factors when sampling. According to the continuous characteristics of information logging, the conventional logging curves (mainly acoustics and resistivity, etc.) were calibrated with the organic carbon experimental data of cores, cuttings or sidewall cores. The organic carbon content of source rocks of the 4th (Es4) and 3rd (Es3) members of the Shahejie Formation in western sag in the Liaohe depression was estimated directly by a great amount of continuous data including resistivity and acoustic logging, etc. Comparison between the results from computer processing and lab analysis of logging data shows that the organic carbon contents derived from the computer processing of logging data have the same reliability and accuracy as the lab analysis results. The present data show that this method is suitable to evaluate the source rocks of western sag in the Liaohe depression and has great potential in evaluating natural resources of sedimentary basins in the future. On the basis of logging data of source rocks, experimental data and existing geochemical analyses of the Liaohe Oilfield, the corresponding total organic carbon (TOC) isograms of source rocks were plotted. The source rocks of Es4 and Es3 of the Shahejie Formation are thought to be beneficial to hydrocarbon accumulation due to the high TOC.
... Conventionally, shale is a source rock for petroleum systems, showing low permeability (Gluyas and Swarbrick 2009;Liu et al. 2012;Rezaee 2015). Contemporary geophysical and geological techniques have been focused on extracting hydrocarbons from clastics and carbonates due to their favorable permeability. ...
... In the ΔLogR method, resistivity logs are superimposed to one of three porosity logs (neutron, DT and RHOB) (Passey et al. 1990;Liu et al. 2012). Resistivity logs are plotted on logarithmic scale and other logs (neutron, RHOB and DT logs) are displayed on linear scales (Rider 2002). ...
... Any combination of two logs can be taken i.e. resistivity/DT, resistivity/neutron or resistivity/RHOB. In this method, the neutron and RHOB logs are mostly affected by borehole wall rugosity, and it is better to use a combination of resistivity/DT for more precise results (Liu et al. 2012). ...
The exploration and production of unconventional resources has increased significantly over the past few years around the
globe to fulfill growing energy demands. Hydrocarbon potential of these unconventional petroleum systems depends on the
presence of significant organic matter; their thermal maturity and the quality of present hydrocarbons i.e. gas or oil shale. In
this work, we present a workflow for estimating Total Organic Content (TOC) from seismic reflection data. To achieve the
objective of this study, we have chosen a classic potential candidate for exploration of unconventional reserves, the shale of
the Sembar Formation, Lower Indus Basin, Pakistan. Our method includes the estimation of TOC from the well data using the
Passey’s ΔlogR and Schwarzkofp’s methods. From seismic data, maps of Relative Acoustic Impedance (RAI) are extracted
at maximum and minimum TOC zones within the Sembar Formation. A geostatistical trend with good correlation coefficient
(
R2) for cross-plots between TOC and RAI at well locations is used for estimation of seismic based TOC at the reservoir
scale. Our results suggest a good calibration of TOC values from seismic at well locations. The estimated TOC values range
from 1 to 4% showing that the shale of the Sembar Formation lies in the range of good to excellent unconventional oil/gas
play within the context of TOC. This methodology of source rock evaluation provides a spatial distribution of TOC at the
reservoir scale as compared to the conventional distribution generated from samples collected over sparse wells. The approach
presented in this work has wider applications for source rock evaluation in other similar petroliferous basins worldwide.
... Conventionally, shale is a source rock for petroleum systems, showing low permeability (Gluyas and Swarbrick 2009;Liu et al. 2012;Rezaee 2015). Contemporary geophysical and geological techniques have been focused on extracting hydrocarbons from clastics and carbonates due to their favorable permeability. ...
... In the ΔLogR method, resistivity logs are superimposed to one of three porosity logs (neutron, DT and RHOB) (Passey et al. 1990;Liu et al. 2012). Resistivity logs are plotted on logarithmic scale and other logs (neutron, RHOB and DT logs) are displayed on linear scales (Rider 2002). ...
... Any combination of two logs can be taken i.e. resistivity/DT, resistivity/neutron or resistivity/RHOB. In this method, the neutron and RHOB logs are mostly affected by borehole wall rugosity, and it is better to use a combination of resistivity/DT for more precise results (Liu et al. 2012). ...
The exploration and production of unconventional resources has increased significantly over the past few years around the globe to fulfill growing energy demands. Hydrocarbon potential of these unconventional petroleum systems depends on the presence of significant organic matter; their thermal maturity and the quality of present hydrocarbons i.e. gas or oil shale. In this work, we present a workflow for estimating Total Organic Content (TOC) from seismic reflection data. To achieve the objective of this study, we have chosen a classic potential candidate for exploration of unconventional reserves, the shale of the Sembar Formation, Lower Indus Basin, Pakistan. Our method includes the estimation of TOC from the well data using the Passey’s ΔlogR and Schwarzkofp’s methods. From seismic data, maps of Relative Acoustic Impedance (RAI) are extracted at maximum and minimum TOC zones within the Sembar Formation. A geostatistical trend with good correlation coefficient (R²) for cross-plots between TOC and RAI at well locations is used for estimation of seismic based TOC at the reservoir scale. Our results suggest a good calibration of TOC values from seismic at well locations. The estimated TOC values range from 1 to 4% showing that the shale of the Sembar Formation lies in the range of good to excellent unconventional oil/gas play within the context of TOC. This methodology of source rock evaluation provides a spatial distribution of TOC at the reservoir scale as compared to the conventional distribution generated from samples collected over sparse wells. The approach presented in this work has wider applications for source rock evaluation in other similar petroliferous basins worldwide.
... The application of well logging techniques for the evaluation of total organic carbon (TOC) content in source rocks have produced various different models developed by various scholars [4][5][6][7][8][9][10][11][12][13][14] . Many studies have covered TOC evaluation using conventional well logging method based on the applications of these models, such as El Shawary & Gaafar [15] and Liu et al. [16] . In this study, the source rock characterization of Rakopi, North Cape and Mangahewa formations in Taranaki Basin is discussed by the integration of conventional well log data and the available geochemical data measured in the lab. ...
... The detailed workflow is shown in fig. 3. Similar workflow has been used in studies such as El Shawary & Gaafar [15] and Liu et al. [16] , but a newer method has been adapted in this work flow to include the most recent method by Zhao et al. [14] . Several models were applied to determine the amount of TOC and to determine if well log data can be used to measure and evaluate TOC in the absence of geochemical data based on data suitability: Schmocker & Hester [8] , Passey et al. [11] and Zhao et al. [14] models. ...
... This method using ΔlogR separation between sonic DTC or density and deep resistivity Rt curves yielded TOC well log values that are in very good agreement with the TOC values obtained from lab measurements for all wells applied: Tane-1, North Tasman-1, Maui-4 and Inglewood-1 wells (figs. [14][15][16][17]. Good TOC values are observed in zones with positive ΔlogR separation. ...
Abstract
This paper attempts to evaluate the source rock potential of the major source rocks of the Taranaki
Basin, which are the Rakopi and North Cape formations of the Upper Cretaceous Pakawau Group and
the Mangahewa Formation of the Paleocene Kapuni Group, using conventional borehole well log data.
This has been conducted based on the application of three renowned mathematical models for total
organic carbon (TOC) content evaluation on eight selected wells distributed across the basin. Source
zones have been first identified based on responses of well logging tools to the presence of source
rocks. The models are applied on the source rock intervals and the results were calibrated with
geochemical analyses. Good correlation can be observed between well log and core geochemical TOC
values for the studied wells based on all three models, suggesting that they are all applicable in the
study area. This indicates that well log data can be used with confidence to evaluate organic source
quantity of Taranaki Basin in the absence of geochemical data.
... As setas em vermelho indicam as sequências de trato de sistemas transgressivo (TST), culminando numa superfície de inundação máxima (SIM), e trato de sistemas de mar alto (TSMA (DOVETON, 1991;MCGOWAN, 2015), refletindo a variação do aporte de matéria orgânica terrestre ou das concentrações de oxigenação na coluna d'água (TYSON, 1996). LOSETH et al., 2011;LIU et al., 2012), sendo detectadas pelos perfis apenas caso estejam acima de sua resolução (PASSEY et al., 1990). A Tabela 13 resume as isólitas total de litologias pelíticas (folhelho, folhelho síltico e siltito) e dos intervalos relacionados a essas litologias que possuam carbono orgânico total (COT) superiores a 0,5% e a 1% calculados pelos métodos CARBOLOG e ∆logR. ...
... ∆LOGRO método ∆logR(PASSEY et al., 1990) utiliza a sobreposição de um perfil de porosidade escalado em uma curva de resistividade. O perfil de porosidade utilizado foi o perfil sônico em função da melhor resolução para superar os problemas mecânicos da perfuração (e.g.LIU et al., 2012) e para comparação da qualidade do ajuste com o CARBOLOG. As curvas de carbono orgânico total foram calculadas utilizando-se o software SIGEO (Apêndice 2). ...
The integration of geochemical data of rock samples with geophysical log data allowed to identify and characterize the organic richness, quality and thermal evolution of the
Cenomanian-Turonian (Urucutuca Formation) source rock of an offshore area of the Espírito Santo Basin (Brazil). In the study area, it is composed predominantly of organic matter type II/III and, although low organic content and potential prevail (average of 1.39% of total organic carbon - TOC and S2 of 6.99 mg HC/g rock, respectively), locally greater organic richness with TOC up to 9.40% and S2 up to 59.27 mg HC/g rock were identified. Using data from TOC and Rock-Eval Pyrolysis analyses, the Cenomanian-Turonian anoxic event (Ocean Anoxic Event 2) was interpreted as not being expressive in the study area. The study of natural series allowed the definition of the top of the oil window (2900 m burial), corresponding to a Tmax of 440ºC, and top of the expulsion of petroleum (3100 m burial) of the analyzed interval. The analysis of the influence of the organic content, estimated continuously in depth through the methods DlogR and CARBOLOG calibrated with the data measured, on the different in rock geophysical logs, showed trends proportional to the increase of the TOC, except for the resistivity log, which is correlated with thermal maturation. In order to evaluate the potential of source rock identification and characterization in seismic reflection data, it was sought to understand the influence of organic richness on the elastic properties of the source rock through analyses of compressional and shear wave impedance and the amplitude variation with increasing angle of incidence by AVO (or AVA) analysis. The results point to a good potential for identification of organic rocks rich in organic content (TOC above 2%) and thickness through pre- and post-stack seismic data. It is recommended that different seismic methods and attributes must be integrated to diminish the occurrence of ambiguities in the interpretation of source rocks.
... The technique 178 requires the superimposition of LLD curves against one of the three 'basic' porosity logs, Neutron 179 (NPHI), Density (RHOB) and Sonic (DT) log, after a scale adjustment is applied to the data 180 (Passey et al., 1990). A logarithmic LLD log is therefore plotted against one of the linearly scaled 181 porosity logs (Rider, 2002), but since borehole conditions can affect the NPHI and DT logs, it is 182 better to plot the LLD curve against the DT log for more accurate results (Liu et al., 2012). After 183 the curves are superimposed, a baseline is documented within a fine-grained, non-source interval 184 15 (Passey et al., 1990). ...
The ever-increasing demand for new energy sources witnessed at present is leading to a shortage of oil and gas resources throughout the world. At the same time, polluting energy sources such as coal are being gradually replaced by gas, new fuel types and electricity produced by renewable methods. Unconventional shale gas reserves, relying on the presence of substantial volumes of good quality, thermally mature organic matter, are therefore crucial in shaping the economic future of multiple regions in the world. Using seismic reflection data to estimate Total Organic Carbon (TOC) in the underexplored Sembar Formation of the Qadirpur Area, Central Indus Basin, this study investigates the potential of a new unconventional resource in Pakistan. We estimate TOC based on well-log data using Passey’s Δ Log R, Schmoker’s, and Schwarzkopf’s methods. In a second stage, thermal maturity modelling was carried out for the formations encountered in Well Qadirpur Deep-01, while focusing primarily on the Sembar Formation. Petrophysical and petroelastic properties were determined and cross-plotted to identify potential zones favourable to hydraulic fracturing. The results show calculated TOC values ranging from 2–4 wt% based on the multiple methods indicated above, proving that the Sembar Formation is a good to excellent unconventional oil gas play. Thermal maturity modelling further confirms that the organic matter in the Sembar Formation is mature. Our seismic based spatial distribution indicates that TOC values are particularly favourable in the lower part of the formation, which is also prone to hydraulic fracturing based on its petroelastic evaluation. This study presents a valid approach to characterise source-rock potential in sedimentary basins throughout South Asia and around the world.
... Their application can be done in two ways: via 1) mathematical models and/or 2) data mining framework or machine learning intelligent systems. Both techniques have proven to provide accuracy and hence can become a reliable alternative solution in total organic carbon (TOC) content quantification (Liu et al. 2012;Jumat et al. 2017;Bolandi et al. 2015Bolandi et al. , 2017Shi et al. 2016;Shalaby et al. 2019a). Mathematical models developed by Passey et al. (1990), Zhao et al. (2016) and many others have been used to not only evaluate the quantity of carbon, but also identify and discriminate producible source zones within a well-cored interval or formation. ...
Thermal maturity, organic richness and kerogen typing are very important parameters to be evaluated for source rock characterization. Due to the difficulties of high cost geochemical analyses and the unavailability of rock samples, it was necessary to examine and test many different method and techniques to help in the prediction of TOC values as well as other maturity indicators in case of missing or absence of geochemical data. Integrated study of machine learning techniques and well-log data has been applied on Cretaceous–Paleocene formations in the Taranaki Basin, New Zealand. A novel approach of maturity prediction using Tmax and vitrinite reflectance (VR%) is the first and preliminary objective of this research. Moreover, the organic richness or the total organic carbon (TOC) content has been predicted as well. Geochemical and well-log data collected from the Cretaceous Rakopi and North Cape formations and Paleocene Mangahewa Formation have been processed and prepared to apply the machine learning techniques. Five machine learning techniques, namely Bayesian regularization for feed-forward neural networks (BRNNs), random forest (RF), support vector machine (SVM) for regression, linear regression (LR) and Gaussian process regression (GPR), were employed for prediction of TOC, Tmax and VR, and their results have been compared. For TOC prediction, the best model achieved the coefficient of determination (R2) value of 0.964 using RF model. For Tmax prediction, BRNN with one hidden layer achieved the R2 value of 0.828. BRNN with two hidden layers produced the best model for VR prediction achieving R2 = 0.636. A comparison of five ML techniques showed that all of these techniques performed exceedingly well for TOC prediction with a value of R2 > 0.96. In contrast, BRNN with one hidden layer was the only ML technique able to achieve R2 > 0.8 for Tmax and BRNN with two hidden layers was the only ML technique able to achieve R2 > 0.6 for VR prediction. Therefore, this research provides a strong empirical evidence that ML techniques can capture the nonlinear relationship between the well-log data and TOC as well as the maturity indicators which may not be fully understood by existing linear models.
... Various mathematical models have been developed for TOC quantification using well logging techniques (Schmocker and Hester, 1983;Passey et al., 1990;Zhao et al., 2016). Similar studies have been done by El Shawary and Gaafar (2012), Liu et al. (2012) and Jumat et al. (2017). Additionally, the well logging data has been utilized by intelligent systems to predict TOC values, such as the machine learning methods. ...
The machine learning methods and well log mathematical models have been used for predicting total organic carbon (TOC) in Jurassic source rock formations in Northwestern Desert, Egypt. Conventional well log data from two wells have been utilized for source rock study of Jurassic source rocks from Khatatba and Ras Qattara formations in the study area. The source rock is first studied based on geochemical parameters, which include assessments on the type and amount of kerogen present within the source rock samples. The Jurassic source rock samples have great generative potential and consist of mixed kerogen type III and kerogen type II-III. TOC content reaches up to 46.90% for Khatatba and 16.80% Ras Qattara. In the second part of this research, we attempt to characterize the Jurassic source rocks by using mathematical well log models and machine learning methods. GR, RHOB and NPHI well log data were used for TOC prediction using both methods. The quantified TOC results show that the R² values of well log models are above 0.9 for both formations, whereas the machine learning method using Artificial Neural Network showed R² value of 0.4. The results from the well log models suggest that they are applicable in the study area. This study has proven that well log data can be used with confidence to evaluate organic source quantity of Jurassic rocks in Northwestern Desert in the absence of geochemical data.
Total organic carbon (TOC) content of source rocks is usually determined by geochemical analysis of samples, but this process takes a long time and costs a lot. Using high-resolution and continuous logging information to evaluate the TOC content can solve the above problems. Previous studies have shown that there are certain differences in the response of logging curves such as spontaneous potential (SP), acoustic interval transit time (AC), natural gamma ray (GR), resistivity (Rt) and density (DEN) to TOC. Based on the response characteristics, this article uses the logging data of nine wells in Wenchang A and Wenchang B depressions to predict TOC by multiple regression method, and proves its accuracy by comparing with the density logging method and ΔlogR method. In addition, the influencing factors of logging evaluation are discussed: ① Type difference of parent rock affects the structural evolution and reservoir conditions of upper strata; ② Different clay mineral compositions lead to the difference in the distribution of argillaceous types and content, thus affecting the logging data. Therefore, clarifying the factors affecting logging evaluation and establishing effective prediction models in different blocks have important guiding significance for oil and gas exploration and development in the Zhu III sub-basin.
The Western Depression of the Liaohe Basin to the north of Bohai Bay is petroliferous and of Eocene and Oligocene age. Understanding the geological features of hydrocarbon source rocks by analyzing Rock-Eval tests and well-logging data is important in unconventional resource exploration. It indicates that thermal evolution controls unconventional resource accumulation in the Qingshui sag. Relatively favorable sections are from Es1 to the upper Es31. No clear mathematical or functional relationship exists between well-logging data and the organic carbon content acquired from Rock-Eval. However, well-logging data has a statistical relationship with other geochemical scales at different levels, which can be used in assessing shale and mudstone as hydrocarbon source rock in this sag, and excludes the influence of tightly packed and heavy minerals in further drilling.
SUMMARY In the process of formation evaluation for tight reservoirs, extracting quantitative information of kerogen is a potentially important factor. Moreover, Total Organic Carbon (TOC) is not strongly correlated with geophysical well logging data. In this paper, a combinatory algorithm for nonlinear regression based on Empirical Mode Decomposition (EMD) and Support Vector Regression (SVR) is proposed. On the basis of depth matching, sensitive well logging parameters are preferred by core calibration. That, which means should be used to denoise, is a key issue for acquiring precise and high quality data. Then, intrinsic mode functions (IMF) decomposed by EMD algorithm is established and applied for denosing. Further, denoised data is classified into two categories, one for training and the other for validating. Aiming for TOC predicting model, SVR is implemented both for training and predicting, and simultaneously some conventional methods such as logR, back propagation artificial neural networks(BP-ANN), and multiple linear regressions are also exerted for comparisons. The result shows that EMD-SVR is the best solution for TOC predicting, with the highest correlation coefficient and the smallest mean squared errors. Likewise, this algorithm is applicable for other reservoirs like shale gas.
It is thought that some parameters, such as elastic coefficient, U/Th ratio, ΔGR/HCGR, etc., might have relations to organic carbon content in formation according to the properties of hydrocarbon source rock. Two methods are used to calculate the organic carbon content: (1) Overlay technique for acoustic slowness curves and resistivity curves; (2) The regression formula of organic carbon content and log responses obtained from experiments. The calculated results from the above two methods consist well with the experimental results.
One of the most important tasks for evaluating natural resource of hydrocarbon-bearing basins is to quantify the organic matter abundance of source rocks in basins. The source rocks model used in this paper is developed by France Petroleum Research Institute. The total organic carbon content is estimated primarily and directly by using continuous conventional logging curves (such as sonic and resistivity curve, etc.) which have been calibrated through the lab analysis data of the organic carbon of cores, cuttings or sidewall cores. The method have been tested and verified in the hydrocarbon source rocks of the ES3 group Formation of Palogene in Jiyang depression. The comparison between the results from the computer analysis of logging data and the lab analysis shows that the organic carbon content derived from the computer analysis of logging data has the same reliability and accuracy as the lab analysis results of rock samples. The present data show that the method is suit able to evaluate source rocks which are from immature to medium mature in hydrocarbon sags of Shengli Oilfield and has great potential in evaluating natural resource of sedimentary basins in the future.
Recent advances in geochemical logging technology and interpretation have greatly enhanced their ability to quantitatively evaluate potential source rocks from wireline logs. use of the carbon-oxygen ratio in conjunction with inorganic elemental data obtained from gamma-ray spectroscopy tools makes it possible to first determine the total carbon content (TOC) of the formation and then correct for inorganic carbon to ultimately obtain a log of total organic carbon (TOC). The TOC results can then be combined with other logs such as uranium and sulfur to make some inferences regarding the depositional environment. These techniques have been applied to a 20-m interval from a well in France. The depth interval was cored and logged with a Gamma-Ray Spectrometry tool as well as conventional wireline tools. The core was analyzed for both organic and inorganic geochemistry, and the logs were examined for source rock information. Preliminary results of the log interpretation indicate TOC contents as high as 5-6% with as much as additional 4-5% inorganic carbon. These results are compared with a more conventional approach of using a combination of gamma-ray, sonic, resistivity, neutron, and density logs to identify organic matter.
A practical method, the Î log R technique, for identifying and calculating total organic carbon in organic-rich rocks has been developed using well logs. The method employs the overlaying of a properly scaled porosity log (generally the sonic transit time curve) on a resistivity curve (preferably from a deep-reading tool). In water-saturated, organic-lean rocks, the two curves parallel each other and can be overlain, since both curves respond to variations in formation porosity; however, in either hydrocarbon reservoir rocks or organic-rich non-reservoir rocks, a separation between the curves occurs. Using the gamma-ray curve, reservoir intervals can be identified and eliminated from the analysis. The separation in organic-rich intervals results from two effects: the porosity curve responds to the presence of low-density, low-velocity kerogen, and the resistivity curve responds to the formation fluid. In an immature organic-rich rock, where no hydrocarbons have been generated, the observed curve separation is due solely to the porosity curve response. In mature source rocks, in addition to the porosity curve response, the resistivity increases because of the presence of generated hydrocarbons. The magnitude of the curve separation in non-reservoirs is calibrated to total organic carbon and maturity, and allows for depth profiling of organic richness in the absence of sample data. This method allows organic richness to be accurately assessed in a wide variety of lithologies and maturities using common well logs.
The organic-matter content of the Devonian shale of the Appalachian basin is important for assessing the natural-gas resources of these rocks, and patterns of organic-matter distribution convey information on sedimentary processes and depositional environment. In most of the western part of the Appalachian basin the organic-matter content of the Devonian shale can be estimated from gamma-ray wire-line logs using the equation: phiâ = (..gamma../sub B/ - ..gamma..)/1.378A, where phiâ is the organic-matter content of the shale (fractional volume), ..gamma.. the gamma-ray intensity (API units), ..gamma../sub B/ the gamma-ray intensity if no organic matter is present (API units), and A the slope of the crossplot of gamma-ray intensity and formation density (API units/(g/cm³)). Organic-matter contents estimated using this equation are compared with organic-matter contents determined from direct laboratory analyses of organic carbon for 74 intervals of varying thickness from 12 widely separated wells. The organic-matter content of these intervals ranges from near zero to about 20% by volume. The gamma-ray intensity of the Cleveland Member of the Ohio Shale and the lower part of the Olentangy Shale is anomalously low compared to other Devonian shales of similar richness, so that organic-matter content computed for each of these units from gamma-ray logs is likely to be too low. Wire-line methods for estimating organic-matter content have the advantages of economy, readily available sources of data, and continuous sampling of the vertically heterogenous shale section. The gamma-ray log, in particular, is commonly run in the Devonian shale, its response characteristics are well known, and the cumulative pool of gamma-ray logs forms a large and geographically broad data base. The quantitative computation of organic-matter content from gamma-ray logs should be of practical value in studies of the Appalachian Devonian shale. 16 figures.
The upper and lower members of the Mississippian and Devonian Bakken Formation in the United States portion of the Williston basin are black shales that are extremely rich in organic matter and are the source of much of the oil found in the basin. Organic-carbon values are calculated from formationdensity logs using the equation: TOC = (154.497//rho/) -57.261, where TOC is organic-carbon content (wt. %) and /rho/ is formation density (g/cm³). Test calculations comparing this equation to laboratory organic-carbon analyses from 39 wells in North Dakota show an average absolute difference of 1.1% in organic-carbon content. Organic-carbon content, calculated at 159 locations in North Dakota and 107 in Montana, averages 12.1% for the upper member of the Bakken Formation and 11.5% for the lower member. There is a regional depletion of organic carbon, paralleling present-day isotherms, that reflects the conversion of organic matter to oil and subsequent expulsion of the oil from the formation. The mass of organic carbon in the Bakken Formation is approximately evenly divided between the upper and lower members, and it totals about 126 X 10¹² kg in the study area, of which 102 X 10¹² kg are in the thermally mature region. The assumption that 167 mg HC/g TOC have migrated out of the mature Bakken shales leads to a tentative estimate that hydrocarbons equivalent to 132 billion bbl of 43° (API gravity) oil have been expelled from the United States portion of the upper and lower members of the Bakken Formation.
Source rock formations generally show a lower density, a lower sonic transit time, and a higher resistivity than other sediments of equal compaction and comparable mineralogy. This phenomenon can be used to identify source rocks on wireline logs provided the source rocks have a minimum thickness within the resolution of the sondes used and are sufficiently rich in organic matter. Classification rules have been established to assist in the recognition of source rocks on a combination of logs. Because of the low density contrast between water and organic matter, the method becomes inaccurate at high water saturations. Within limits, the amount of organic matter contained in a sediment can be estimated from log anomalies.
Total organic-carbon (TOC) content present in potential source rocks significantly affects the response of various well logs. This paper discusses and illustrates well-log anomalies caused by TOC as observed on various wireline measurements, including resistivity (or conductivity), acoustic, nuclear (density and neutron), gamma ray, natural gamma ray spectra, and pulsed neutron [sigma and carbon/oxygen (C/O) ratio].
Field examples of these well-log responses in open and/or closed wellbores are presented from several countries. Several correlations between TOC and individual and/or combinations of various logging responses are also reviewed.
Recent advances in geochemical logging technology and interpretation have greatly enhanced their ability to quantitatively evaluate potential source rocks from wireline logs. use of the carbon-oxygen ratio in conjunction with inorganic elemental data obtained from gamma-ray spectroscopy tools makes it possible to first determine the total carbon content (TOC) of the formation and then correct for inorganic carbon to ultimately obtain a log of total organic carbon (TOC). The TOC results can then be combined with other logs such as uranium and sulfur to make some inferences regarding the depositional environment. These techniques have been applied to a 20-m interval from a well in France. The depth interval was cored and logged with a Gamma-Ray Spectrometry tool as well as conventional wireline tools. The core was analyzed for both organic and inorganic geochemistry, and the logs were examined for source rock information. Preliminary results of the log interpretation indicate TOC contents as high as 5-6% with as much as additional 4-5% inorganic carbon. These results are compared with a more conventional approach of using a combination of gamma-ray, sonic, resistivity, neutron, and density logs to identify organic matter.
The Woodford Shale, an organic-rich black shale of Late Devonian and Early Mississippian age, is regarded as a major hydrocarbon source rock in the Anadarko Basin. It is divided on the basis of log character into three informal stratigraphic units: the lower, middle, and upper members. A positive structural feature, parallel with and about 75 miles north of the Wichita Mountains front, divides the Woodford into northeast and southwest depocenters. Total organic carbon calculated from log-derived formation density of the lower, middle, and upper members of the Woodford Shale averages 3.2, 5.5, and 2.7 weight percent; it does not correlate with formation thickness, but rather decreases with increasing thermal maturity. The total amount of organic carbon in the Woodland Shale of the study area is evenly divided between the three members. Some 54 of the 73 trillion kilograms of organic carbon mapped in this report are in thermally mature areas characterized by vitrinite reflectance greater than 0.6 percent. Most of the hydrocarbons sourced by the Woodford Shale of the study area were generated from the lower and middle members, in that these two members contain 74 percent of the thermally mature organic carbon.
The feasibility of conducting petroleum source rock evaluations from well-log data was examined using three continuously cored sections (immature, mature and postmature stages) of the Lower Toarcian Posidonia Shale, northern Germany. Logs depicting natural gamma emission (K, U, Th), bulk density, sonic travel time and resistivity were utilised, as was the borehole televiewer for fracture control.Selected data from these logs were correlated with parameters of source richness, hydrocarbon content and maturity. The resulting three-dimensional cross plot shows at a glance well-by-well comparison of facies, maturity and hydrocarbon content. A simple correlation between organic-geochemical and petrophysical parameters is, of course, not perfect since log response is complex and affected by mineralogical and pore fluid properties of the rock as well as by organics. However, source rock characterization by wireline logging is still a fast and therefore economical method. Relative “quick-look” comparisons from well to well are possible without calibration to core data and can easily be performed at once at the drill site. The present application is limited to clastic source rocks in basins with simple geologic histories.
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- R K Mallick
- S V Raju
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