Direct TOC Quantification in unconventional Kerogen-rich Shale Resource Play from Elemental Spectroscopy Measurements: A Case Study from North Kuwait

2015 ◽  
Author(s):  
Girija K. Joshi ◽  
Mihira N. Acharya ◽  
Marie Van Steene ◽  
Sandeep Chakravorty ◽  
Christophe Darous ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Total Organic Carbon ◽  
Gamma Ray ◽  
Horizontal Wells ◽  
Final Analysis ◽  
Total Carbon ◽  
Empirical Estimation ◽  
New Type ◽  
Borehole Image ◽  
Borehole Image Logs

Abstract The deep organic-rich calcareous Kerogen of North Kuwait, a continuous 50ft thinly alternating carbonate – organic-rich argillaceous sequence, is not only a source rock but has gained importance as potential reservoirs themselves of typical unconventional category. Resource play or Kerogen characterization relies on quantifying total organic carbon (TOC) and estimating accurate mineralogy. This paper describes the first attempt to directly measure total organic carbon of the Limestone-Kerogen sequence. For the present study, empirical estimations of TOC have been carried out based on conventional log measurements and nuclear magnetic resonance (NMR). The introduction of a new neutron-induced capture and inelastic gamma ray spectroscopy tool using a very high-resolution scintillator and a new type of pulsed neutron generator for the deep unconventional kerogen resources have provided a unique opportunity to measure a stand-alone quantitative TOC value using a combination of capture and inelastic gamma ray spectra. In this process, Inorganic Carbon Content (ICC) is estimated by using elemental concentrations measured by this logging tool in addition to measuring Total Carbon, and this value is subtracted from the measured total carbon to give TOC. The advanced elemental spectroscopy tool measurements were first used to determine accurately the complex mineralogy of the layered carbonate and organic-rich shale sequence. Extensive laboratory measurements of core / cuttings data were used to calibrate the petrophysical evaluation and capture the heterogeneity seen on borehole image logs. The final analysis shows considerable improvements compared to conventional empirical estimation. Once the mineralogy is properly determined, the log-derived TOC matches very well with core measured TOC. This technique has provided a new direct and accurate log-derived TOC for Kerogen characterization. The application has a potential to be used for CAPEX optimization of the coring in future wells. This technique can also be applied in HPHT and High-angle horizontal wells, which can overcome challenging coring difficulties in horizontal wells.

scholarly journals CARBON CONTENTS AND MODELLING OF TOTAL ORGANIC CARBON FOR Pinus taeda L. FROM NATURAL REGENERATION

2016 ◽  
Vol 40 (4) ◽  
pp. 661-668 ◽  
Author(s):  
Rafael Cubas ◽  
Emanuel Arnoni Costa ◽  
Viviane Zaniz
Keyword(s):  
Organic Carbon ◽  
Total Organic Carbon ◽  
Pinus Taeda ◽  
Natural Regeneration ◽  
Ground Level ◽  
Total Carbon ◽  
Forest Understory ◽  
Planted Forest ◽  
Pinus Taeda L ◽  
Selection Of

ABSTRACT This study aimed to quantify total carbon and its compartments: roots, stems, branches, and aciculas, in order to select an estimated equation of the total organic carbon for Pinus taeda L. settled from natural regeneration in the forest understory of a planted forest in the municipality of Três Barras, SC. Data have been collected from a random selection of 96 individuals with diameter at 0.3 meters above ground level, varying from 2.5 to 19cm. The selected individuals had their dimensional variables (dendrometric and morphometric variables) measured being subsequently felled and their compartments separated, weighed and samples were collected and taken to analysis of carbon contents. Eight traditional models were tested, six arithmetic and two logarithmic, as well as a model developed by the Stepwise process, being total organic carbon the dependent variable, and dimensional variables the independent variables. The total organic carbon found was 46.7% on average, and Tukey-Kramer test indicated significant differences of carbon contents amongst compartments. In comparison with traditional equations tested, the equation adjusted by Stepwise seemed more accurate, with good fit (R2aj. = 0.931) and precision (Syx% = 18.5).

Determination of total carbon and total organic carbon from volatile air pollutants

1979 ◽  
Vol 71 (5-6) ◽  
pp. 317-329 ◽  
Author(s):  
Edmund Kozlowski ◽  
Jacek Namieśnik
Keyword(s):  
Organic Carbon ◽  
Total Organic Carbon ◽  
Air Pollutants ◽  
Total Carbon

scholarly journals Effects of Invasive Spartina alterniflora Loisel. and Subsequent Ecological Replacement by Sonneratia apetala Buch.-Ham. on Soil Organic Carbon Fractions and Stock

Forests ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 171 ◽  
Author(s):  
Jianxiang Feng ◽  
Shugong Wang ◽  
Shujuan Wang ◽  
Rui Ying ◽  
Fangmin Yin ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Total Organic Carbon ◽  
Spartina Alterniflora ◽  
Total Carbon ◽  
Carbon Fractions ◽  
Sonneratia Apetala ◽  
Organic Carbon Fractions ◽  
Soil Organic Carbon Fractions ◽  
Qi’Ao Island

Background and Objectives: The rapid spread of invasive Spartina alterniflora Loisel. in the mangrove ecosystems of China was reduced using Sonneratia apetala Buch.-Ham. as an ecological replacement. Here, we studied the effects of invasion and ecological replacement using S. apetala on soil organic carbon fractions and stock on Qi’ao Island. Materials and Methods: Seven sites, including unvegetated mudflat and S. alterniflora, rehabilitated mangroves with different ages (one, six, and 10 years) and mature native Kandelia obovata Sheue, Liu, and Yong areas were selected in this study. Samples in the top 50 cm of soil were collected and then different fractions of organic carbon, including the total organic carbon (TOC), particulate organic carbon (POC), soil water dissolved carbon (DOC) and microbial biomass carbon (MBC), and the total carbon stock were measured and calculated. Results: The growth of S. alterniflora and mangroves significantly increased the soil TOC, POC, and MBC levels when compared to the mudflat. S. alterniflora had the highest soil DOC contents at 0–10 cm and 20–30 cm and the one-year restored mangroves had the highest MBC content. S. alterniflora and mangroves both had higher soil total carbon pools than the mudflat. Conclusions: The invasive S. alterniflora and young S. apetala forests had significantly lower soil TOC and POC contents and total organic carbon than the mature K. obovata on Qi’ao Island. These results indicate that ecological replacement methods can enhance long term carbon storage in Spartina-invaded ecosystems and native mangrove species are recommended.

scholarly journals Extended evaluation of quality of swimming pool water - importance of selected pollutant fractions

2018 ◽  
Vol 44 ◽  
pp. 00098
Author(s):  
Edyta Łaskawiec ◽  
Mariusz Dudziak ◽  
Joanna Wyczarska-Kokot
Keyword(s):  
Organic Carbon ◽  
Total Organic Carbon ◽  
Main Parameter ◽  
Inorganic Carbon ◽  
Separation Process ◽  
Total Carbon ◽  
Distribution Characteristics ◽  
Fraction Distribution ◽  
Swimming Pool Water

The authors of the study attempted to determine the fraction of selected impurities in the filter backwash water from the pool circuit (hot tub). Ultrafiltration membranes were used for the separation process. The main parameter informing about the content of impurities in a given fraction was total carbon (including the total organic carbon). In the studies, fractions with the following sizes of > 200 kDa, 50–200 kDa, < 50 kDa were separated. The fraction distribution in > 5 kDa and < 5kDa was also analyzed. The percentage content of inorganic carbon and total organic carbon changed depending on the ultrafiltration membrane with different distribution characteristics. The concentration of total organic carbon decreased gradually with a decrease in the MWCO value of the membrane. On the basis of the total carbon value, it was found that the tested washings contained: 30.40 wt.% of > 200 kDa fraction, 55.62 wt.% of fraction in the range of 50–200 kDa and 13.98 wt.% of fraction < 50kDa.

Estimating the Total Organic Carbon for Unconventional Shale Resources During the Drilling Process: A Machine Learning Approach

2021 ◽  
pp. 1-26
Author(s):  
Ahmed Mahmoud ◽  
Hany Gamal ◽  
Salaheldin Elkatatny ◽  
Ahmed Alsaihati
Keyword(s):  
Machine Learning ◽  
Organic Carbon ◽  
Total Organic Carbon ◽  
Gamma Ray ◽  
Fuzzy Inference ◽  
Support Vector ◽  
Drilling Process ◽  
Validation Data ◽  
Inference System ◽  
Data Points

Abstract Total organic carbon (TOC) is an essential parameter that indicates the quality of unconventional reservoirs. In this study, four machine learning (ML) algorithms of the adaptive neuro-fuzzy inference system (ANFIS), support vector regression (SVR), functional neural networks (FNN), and random forests (RF) were optimized to evaluate the TOC. The novelty of this work is that the optimized models predict the TOC from the bulk gamma-ray (GR) and spectral GR logs of uranium, thorium, and potassium only. The ML algorithms were trained on 749 datasets from Well-1, tested on 226 datasets from Well-2, and validated on 73 data points from Well-3. The predictability of the optimized algorithms was also compared with the available equations. The results of this study indicated that the optimized ANFIS, SVR, and RF models overperformed the available empirical equations in predicting the TOC. For validation data of Well-3, the optimized ANFIS, SVR, and RF algorithms predicted the TOC with AAPE's of 10.6%, 12.0%, and 8.9%, respectively, compared with the AAPE of 21.1% when the FNN model was used. While for the same data, the TOC was assessed with AAPE's of 48.6%, 24.6%, 20.2%, and 17.8% when Schmoker model, ΔlogR method, Zhao et al. correlation, and Mahmoud et al. correlation was used, respectively. The optimized models could be applied to estimate the TOC during the drilling process if the drillstring is provided with GR and spectral GR logging tools.

Automated Verification of Sidewall Core Recovery Depth using Borehole Image Logs

2021 ◽  
Author(s):  
Mustafa A Al Ibrahim ◽  
Vladislav Torlov ◽  
Mokhles M Mezghani
Keyword(s):  
Statistical Analysis ◽  
Bayesian Statistics ◽  
Hough Transform ◽  
Gamma Ray ◽  
Cost Effective ◽  
Well Logs ◽  
Automated Identification ◽  
Core Recovery ◽  
Borehole Image ◽  
Borehole Image Logs

Abstract Sidewall coring is a cost-effective process to complement conventional fullbore coring. Because sidewall cores target exact depth points, verification of the sidewall core recovery depth is required. We present an automated, fast workflow to perform the depth verification using borehole images, thereby providing consistent results. An application example using a typical dataset is used to showcase the workflow. A novel automated approach based on image analysis techniques and Bayesian statistical analysis is developed to verify sidewall core recovery depth using borehole image logs. A complete workflow is presented covering: 1) utilization of reference logs, e.g., gamma ray, to correct image log depth using cross correlation and/or dynamic time warping, 2) automated identification of sidewall core cavity in borehole image log using the circle Hough transform, and 3) estimation of confidence in the identification using Bayesian statistics and specialized metrics. The workflow is applied on a typical dataset containing tens of sidewall core cavities with varying quality. Results are comparable to the manual interpretation from an experienced engineer. A number of observations are made. First, the use of reference logs to correct the image log allows for determining the exact well logs values where the sidewall core was sampled, which is then compared to the initial target well logs values. This increases the confidence that the target lithofacies was sampled as planned. Second, the circle Hough Transform is suitable for this problem because it provides stable solutions for partially imaged sidewall core cavities typical in pad-based borehole images. Third, the use of Bayesian statistics and specialized metrics for the problem, such as average and standard deviation borehole image intensity in the cavity, provides customizability to work with multiple types of borehole images and with varying initial depth guess uncertainties. Overall, the use of fast and automated methodology for depth verification opens up avenues for near real-time combined sidewall coring, imaging, and verification workflows. The novelty in this study lies in using a combination of image processing techniques and statistical analysis to automate an established manual workflow. The automated workflow provides consistent results in minutes rather than hours. Results also incorporate a confidence index estimation.

scholarly journals Aktivitas NORM pada Sedimen Dasar di Perairan PLTU Tanjung Jati Jepara dan Kaitannya dengan Ukuran Butir Sedimen serta TOC

EKSPLORIUM ◽  
2019 ◽  
Vol 40 (2) ◽  
pp. 115
Author(s):  
Navila Bidasari Alviandini ◽  
Muslim Muslim ◽  
Wahyu Retno Prihatiningsih ◽  
Sri Yulina Wulandari
Keyword(s):  
Fly Ash ◽  
Organic Carbon ◽  
Total Organic Carbon ◽  
Bottom Sediments ◽  
Activity Concentration ◽  
Gamma Ray ◽  
Bottom Ash ◽  
Radioactive Material ◽  
Gamma Ray Spectrometry ◽  
Purposive Sampling

ABSTRAKNORM (Naturally Occuring Radioactive Material) merupakan unsur radionuklida yang secara alami sudah ada dalam bumi dan kandungannya dapat meningkat dengan adanya kegiatan industri, seperti PLTU. Kegiatan PLTU menghasilkan bottom ash dan fly ash yang akan terbawa oleh angin kemudian masuk ke perairan dan mengendap pada sedimen dasar perairan. Penelitian ini bertujuan untuk mengetahui aktivitas NORM pada sedimen dasar terkait kegiatan PLTU Tanjung Jati, Jepara dan hubungannya dengan ukuran butir serta TOC (Total Organic Carbon). Pengambilan sampel dilakukan dengan metode purposive sampling. Pengukuran konsentrasi aktivitas NORM dilakukan menggunakan spektrometri sinar gama detektor HPGe, di Laboratorium Radioekologi Kelautan PTKMR-BATAN. Konsentrasi aktivitas NORM yang terdeteksi yaitu 40K berkisar 442,75–818,40 Bq.Kg-1, 232Th berkisar 99,19–212,34 Bq.Kg-1 dan 226Ra berkisar 42,42–77,77 Bq.Kg-1. Aktivitas NORM menunjukkan adanya hubungan dengan tekstur sedimen, tetapi tidak menunjukkan hubungan dengan kandungan Total Organic Carbon (TOC).ABSTRACTNORM (Naturally Occurring Radioactive Material) is a radionuclide element which naturally exists in the earth and its content can increased with the presence of industrial activities, such as the PLTU. The PLTU activities produce fly ash and bottom ash which will be carried away by the wind and then fall in the waters and settle on the bottom sediments of the waters. This study was aimed to determine the activity of NORM in bottom sediments related activities PLTU Tanjung Jati Jepara and its relationship with grain size and TOC (Total Organic Carbon). Sampling was conducted by purposive sampling method. NORM activity concentration measurements performed using gamma ray spectrometry HPGe detector, in Marine Radioecology Laboratory PTKMR-BATAN. NORM activity concentration detected is 40K ranged 442.75 to 818.40 Bq.Kg-1, 232Th ranged 99.19 to 212.34 Bq.Kg-1 and 226Ra ranged 42.42 to 77.77 Bq.Kg-1. NORM activity shows the relationship with sediment texture, but does not show a relationship with the composition of Total Organic Carbon (TOC).

Novel Empirical Correlation for Estimation of the Total Organic Carbon in Devonian Shale from the Spectral Gamma-Ray and Based on the Artificial Neural Networks

2021 ◽  
pp. 1-28
Author(s):  
Ahmed Abdulhamid Mahmoud ◽  
Salaheldin Elkatatny
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Organic Carbon ◽  
Total Organic Carbon ◽  
Gamma Ray ◽  
Linear Regression Analysis ◽  
Empirical Correlation ◽  
Training Data ◽  
Validation Data ◽  
Artificial Neural

Abstract Evaluation of the quality of unconventional hydrocarbon resources becomes a critical stage toward characterizing these resources, this evaluation requires evaluation of the total organic carbon (TOC). Generally, TOC is determined from laboratory experiments, however, it is hard to obtain a continuous profile for the TOC along the drilled formations using these experiments. Another way to evaluate the TOC is through the use of empirical correlation, the currently available correlations lack the accuracy especially when used in formations other than the ones used to develop these correlations. This study introduces an empirical equation for evaluation of the TOC in Devonian Duvernay shale from only gamma-ray and spectral gamma-ray logs of uranium, thorium, and potassium as well as a newly developed term that accounts for the TOC from the linear regression analysis. This new correlation was developed based on the artificial neural networks (ANN) algorithm which was learned on 750 datasets from Well-A. The developed correlation was tested and validated on 226 and 73 datasets from Well-B and Well-C, respectively. The results of this study indicated that for the training data, the TOC was predicted by the ANN with an AAPE of only 8.5%. Using the developed equation, the TOC was predicted with an AAPE of only 11.5% for the testing data. For the validation data, the developed equation overperformed the previous models in estimating the TOC with an AAPE of only 11.9%.

Sign in / Sign up

Export Citation Format

Share Document