scholarly journals Stratigraphic subdivision of Tertiary sediments Of Well 1 using total organic carbon (TOC) and gamma ray (GR) log: Case study, the Niger Delta

2021 ◽  
Vol 9 (10) ◽  
pp. 46-50
Author(s):  
Benson Akinbode Olisa ◽  
Ayomide Samson Ifanegan
Keyword(s):  
Organic Carbon ◽  
Total Organic Carbon ◽  
Niger Delta ◽  
Gamma Ray ◽  
Stratigraphic Subdivision

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.

Total organic carbon from well logging - statistical approach, Polish shale gas formation case study

2019 ◽  
Vol 22 (2) ◽  
pp. 140
Author(s):  
Marcin Zych ◽  
Edyta Puskarczyk ◽  
Jadwiga A. Jarzyna ◽  
Kamila Wawrzyniak Guz ◽  
Paulina I. Krakowska
Keyword(s):  
Organic Carbon ◽  
Total Organic Carbon ◽  
Shale Gas ◽  
Statistical Approach ◽  
Well Logging ◽  
Gas Formation

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.

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).

Sign in / Sign up

Export Citation Format

Share Document