3D organic matter modeling: a novel tool in forward stratigraphic modeling

Abstract The source rock characteristics (thickness, quantity and quality) can be varied both in the deposition of time and space. Currently, the distribution map of organic matter is estimated by simplified extrapolate methods using observed data on well location. There is a high degree of uncertainty as a result of using this method especially in the area with a lack of well data.  The aim of this study is to intreduce a novel tool in DionisosFlow software for three-dimensional (3D) simulation of the distribution of total organic carbon in a source rock. In this method, a stratigraphic modeling approach is used to mimic the production and preservation process of the organic-rich interval. The main parameters in this module will be bathymetry, sedimentation rate, primary production, carbon flux and oxygen condition of the sedimentary environment. In this study, we constructed an artificial model to investigate the efficiency of this process-based algorithm. Furthermore, the 3D simulation result of a real model is illustrated. This study indicates a close relationship between depositional conditions on the one hand and the production and preservation of organic matter on the other hand. Also, simulation results pinpoint which anoxic condition could be one of the main parameters in maintaining and distribution of organic matter. Keywords: Forward stratigraphic modeling, Organic matter modeling, Sedimentary environment, Organic matter production and preservation.     Introduction In exploration, the prediction of hydrocarbon accumulation and quality variations within a prospect, prior to drilling, is of great economic importance. Recently, developed 3D modeling methods are gaining significance concerning volumetric hydrocarbon predictions. Nevertheless, in basin modeling studies, source rocks often have higher uncertain input parameters, even though the source rock is the first prerequisite for a hydrocarbon accumulation.  Often a conceptual approach or simple models applying average geochemical values describing source rock properties are used. This often is insufficient, particularly in areas with heterogeneous geological conditions and/or variable depositional environments. Recently, a novel method is evolved from the needs of the petroleum industry to obtain a better estimation of the spatial and temporal distribution of source rocks and variability in the basin. This method describes the characterization of source rock as a function of the sedimentation environment and displays a relationship between rich organic layers and accommodation space. The purpose of the approach is a 3D estimation of source rock characterization (Thickness, Total organic carbon (TOC), Hydrogen index (HI)) to utilize in the petroleum system modeling.   Material & Methods The 3D forward stratigraphic modeling is a process-based approach  simulating sedimentary and tectonic processes both in carbonate and clastic environments (Granjeon, 2014; Granjeon and Joseph, 1999). The main sedimentary processes considered include: 1) accommodation space through time; 2) sediment supply and in situ production in clastic and carbonate sediments, respectively; and 3) sediment transport using Macro-Scale diffusion equations (Csato et al. 2012; Granjeon 2014; Al-Salmi et al. 2018; Hawie et al. 2015, 2021). For each cell of the numerical model, environment properties including a fraction of sediments, thickness, palaeobathymetry, sedimentation rate and energy are estimated. Finally, modeling results are compared with observed data at a well location to validate the constructed model. The stratigraphic forward modeling approach provides most of the parameters required for organic matter simulation (e.g., water depth, basin morphology, sedimentation rate). New parameters are added into classic forward modeling to simulate all the processes needed for organic matter modeling (Granjeon and Chauveau 2014; Bruneau et al. 2016) as follows: primary productivity, carbon flux, organic matter transport, dissolved oxygen level and burial efficiency (which corresponds to degradation within the topmost meter of burial). All these processes and their parameters are based on empirical equations or observations. The production of organic matter by photosynthesis is called primary productivity because it is the first stage in the marine food chain. After primary production, the organic particles sink to the seafloor. The amount of exported production, which reaches the sediment/water interface, is determined by the Martin equation (Martin et al. 1987). The oxygen level in sediments is one of the most important factors controlling the preservation of organic matter since it determines the nature of respiration of benthic organisms. After sinking from the sea surface and transport at the sediment/water interface, the organic matter is finally buried. The amount of organic matter preserved after the first few meters of burial is called burial efficiency; this parameter is mainly controlled by the sedimentation rate (Betts & Holland 1991) and local redox conditions (Tyson 1995). The Total Organic Carbon (TOC) is eventually determined by the amount of preserved organic matter diluted depending on the sedimentation rate. In this study, an artificial model is constructed to determine the efficiency of the new method in the simulation of TOC. Defined initial palaeobathymetry varied between 10 to 700 meters. Sediment was assumed to be composed of two main sediment classes: shallow carbonate and deep carbonate sediment. In this study, the primary productivity, the carbon flux and its variation are used by the default of the software.   Discussion of Results & Conclusion The results of the model show the optimal depth for maintaining organic matter in such a way that with the increase of the palaeodepth, first an increase and then a decrease of TOC is observed. One of the reasons is the reduction of carbon flux concerning to depth. The results of this study indicated that the optimal depth of preservation of organic matter is less than 500 meters. Modeling results demonstrated that there is a rather poor spatial correlation between areas of high marine primary productivity and areas of organic-rich sediment deposition. The absence of correlation is due to the combined influence of the other key factors such as oxygen level. The results indicated that the lowest amount of oxygen is observed in the depth range between 200 and 500 meters and will be increased in much more depth. Because increasing depth leads to a decrease the amount of organic particles and oxygen consumption. Therefore, with the increase in depth, the oxygen level of sea water gradually increases. The depth corresponding to the highest value of TOC was observed between 200 and 400 meters. The modeling results showed that the effective parameters in the distribution of TOC are the oxygen level and accommodation space variation through time. This study demonstrated that the use of this new tool is a very suitable method in the 3D estimation of source rock characteristics in order to use petroleum system modeling. One of the strengths of this method is the use of close relationship of the sedimentary environment with the value of TOC. Therefore, this tool can be very suitable and practical in modeling deep source rocks or areas with a lack of data

Identification of over producer strain of endo-ß-1,4-glucanase in Aspergillus Species: Characterization of crude carboxymethyl cellulase

Cellulases are a group of hydrolytic enzymes capable of degrading cellulose to smaller sugar components like glucose units. These enzymes are produced by fungi and bacteria. The aim of this research was to identify a Aspergillus species with over production of endo-β-1,4-glucanase. Properties of endo-β-1,4-glucanase/carboxymethylcellulase (CMCase) from a culture filtrate of the Aspergillus sp. was also studied. Aspergillus sp. (R4) was selected as over producer of endo-β-1,4-glucanase among 13 different species. SDS-PAGE activity staining with 1% Congo Red solution revealed three protein bands showing cellulolytic activity. The molecular weights of these proteins were estimated to be approximately 18.5, 23 and 28 kD. Also, conservative region of endo-β-1,4-glucanase coding gene was studied by polymerase chain reaction (PCR). Amplified fragments with 1204 bp and 399 bp were confirmed by restriction pattern with HindII and PstI enzymes. Key Words: Aspergillus sp., Endo-β-1, 4-glucanase, CMCase, SDS-PAGE, PCR. African Journal of Biotechnology Vol.4(1) 2005: 26-3

Relevance-based Word Embedding

Learning a high-dimensional dense representation for vocabulary terms, also known as a word embedding, has recently attracted much attention in natural language processing and information retrieval tasks. The embedding vectors are typically learned based on term proximity in a large corpus. This means that the objective in well-known word embedding algorithms, e.g., word2vec, is to accurately predict adjacent word(s) for a given word or context. However, this objective is not necessarily equivalent to the goal of many information retrieval (IR) tasks. The primary objective in various IR tasks is to capture relevance instead of term proximity, syntactic, or even semantic similarity. This is the motivation for developing unsupervised relevance-based word embedding models that learn word representations based on query-document relevance information. In this paper, we propose two learning models with different objective functions; one learns a relevance distribution over the vocabulary set for each query, and the other classifies each term as belonging to the relevant or non-relevant class for each query. To train our models, we used over six million unique queries and the top ranked documents retrieved in response to each query, which are assumed to be relevant to the query. We extrinsically evaluate our learned word representation models using two IR tasks: query expansion and query classification. Both query expansion experiments on four TREC collections and query classification experiments on the KDD Cup 2005 dataset suggest that the relevance-based word embedding models significantly outperform state-of-the-art proximity-based embedding models, such as word2vec and GloVe.Comment: to appear in the proceedings of The 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '17

Association between anogenital distance as a noninvasive index in the diagnosis and prognosis of reproductive disorder: A systematic review

Background: There are 2 measures of anogenital distance (AGD) in men and women. AGD has been used as an indicator of fetal androgen dysfunction and an adverse outcome in adulthood. Some studies have shown the association of AGD as a predictor in the diagnosis and prognosis of diseases and disorders. Objective: To systematically summarize the latest evidence for presenting AGD as a new approach for prognosis and early diagnosis of diseases. Materials and Methods: A systematic review of the available literature was performed using Medline via PubMed, Scopus, and ISI Web of Knowledge up to July 2021, using search terms “anogenital distance” OR “anogenital index” OR “ano genital distance” OR “ano genital index”. Language restrictions were not imposed. Results: After reviewing the retrieved articles, 47 unique studies were included in this systematic review. Different outcomes, including endometriosis, prostate cancer, polycystic ovary syndrome, pelvic organ prolapse, hypospadias, cryptorchidism, fertility and semen parameters, maternal and birth development, and ovarian and gynecological-related disorders, have been studied in the included evidence. A negative association was observed between AGD and endometriosis and hypospadias and a positive association between AGD and prostate cancer, polycystic ovary syndrome, male fetal gender, and fertility parameters. Conclusion: Using quantitative indicators such as AGD may be a useful clinical tool for diagnosing diseases. Although many studies have shown an association between AGD and diseases, some factors, including different measurement methods, different measurement tools, age, and different definitions of AGD, can be involved in the variation of AGD. Key words: Genitalia, Prognosis, Early diagnosis, Reproductive health

Conceptual Explanation of the Food Production Cycle Based on Tayyib Food Indices in the Holy Quran

For downloading the full-text of this article please click here.Background and Objective: Developing civilization processes and systems based on the Qur'anic principles is one of the major issues in the field of epistemics and management in the Islamic community. Nutrition is one of the most vital processes in life and, based on Islamic principles, it plays a key role in securing the religion and world for human. From the perspective of Islamic ideology, nutrition affects the body, thought and faith of humans, although foods do not have the same appearance. God has set the highest standard of quality for human food.Methods: This is an qualitative content analysis study based on Quranic verses relying on the interpretations as an ignored aspect of nutrition. To analyze the word Tayyib, first, its meaning was investigated in lexicographers’ studies, and from the sum of their opinions, we came to a comprehensive and obstructive meaning. In order to achieve the standard of Tayyib food, the word Tayyib was analyzed in the Holy Qur'an and semantically examined. Using semantic network design, its semantic core was extracted and, based on it, the indicators of tayyeb food were determined. The authors declared no conflict of interest.Results: Tayyib food is a pure and developmental food that is perfectly in harmony with the body. Also, it is pleasing, clean, tasty and in good condition, and has a beneficial effect. Furthermore, it is non-harmful to the soul and body. Halal food, on the other hand, is anything that is not forbidden and tayyeb is used to mean something which is in harmony with human spirit as against khabith, which human spirit hates. Conceptually, tayyeb food refers to good, useful, healthy, non-harmful, halal, clean food that is in harmony with human spirit and without any contamination within or in appearance. It refers to a food with complete nutritional values.Conclusion: Tayyib food indices are used as the main elements of a comprehensive and process standard for the entire food cycle from production to consumption. It is considered as a quality standard for optimizing food processes. For downloading the full-text of this article please click here.Please cite this article as: Zamani H, Naji-Tabasi S, Afkhami-Rouhani H, Ahmadzadeh SM, Shahidi-Noghabi M. Conceptual Explanation of the Food Produciton Cycle Based on Tayyib Food Indices in the Holy Quran. Journal of Pizhūhish dar dīn va salāmat. 2020;6(2):165-179. https://doi.org/10.22037/jrrh.v6i2.2146