CO2 sequestration into a coal seam project was studied and a numerical model was developed in this paper to simulate the primary and secondary coal bed methane production (CBM/ECBM) and carbon dioxide (CO2) injection. The key geological and reservoir parameters, which are germane to driving enhanced coal bed methane (ECBM) and CO2 sequestration processes, including cleat permeability, cleat porosity, CH4 adsorption time, CO2 adsorption time, CH4 Langmuir isotherm, CO2 Langmuir isotherm, and Palmer and Mansoori parameters, have been analyzed within a reasonable range. The model simulation results showed good matches for both CBM/ECBM production and CO2 injection compared with the field data. The history-matched model was used to estimate the total CO2 sequestration capacity in the field. The model forecast showed that the total CO2 injection capacity in the coal seam could be 22,817 tons, which is in agreement with the initial estimations based on the Langmuir isotherm experiment. Total CO2 injected in the first three years was 2,600 tons, which according to the model has increased methane recovery (due to ECBM) by 6,700 scf/d.

Hydraulic fracturing is a typical and vital technique applied in shale gas reservoir development. Numerical simulation used to be a common tool to optimize the parameters in hydraulic fracturing design determining the stage numbers, injection pressure, proppant amount, etc. However, the current understanding of shale gas storage and transport mechanism (e.g. adsorption/desorption, diffusion) is basically adopted from the lessons learned from coal seams through past experience, which might not help an efficient numerical simulation development. In this study, how artificial intelligence assisted data driven models assist the hydraulic fracturing design in shale gas reservoir is discussed. It starts by collecting field data and generate a spatial-temporal database including reservoir characteristics, operational/production information, completion/stimulation data and other variables, Neural Network models are then developed to study the impacts of all parameters on gas production as well as perform history matching of the field history. The AI assisted model with acceptable matching of field data can be used to model different hydraulic fracturing design scenarios and provide predictions on well production.

The development of shale gas reservoir has made rapid progress due to the technology advancement in the past decades, which triggered the energy revolution in the United States. Estimating ultimate recovery, the amount of shale gas that can be economically recovered from a reservoir, is an essential task for E&P companies. Based on the estimated ultimate recovery information, a reservoir engineer could determine the economic investment of whether a single well or series of wells would be worthy. Thus, it must be done fast and right. For the past years, the typical methodology of evaluating remaining reserves or estimated ultimate recovery (EUR) of a well or a field is decline curve analysis. This traditional methodology only requires production data for analysis, which is very easy to access and very convenient to use. There are several empirical formulation specifically designed for shale or tight gas reservoir, such as powerlaw exponential decline, stretched exponential decline, doung’s method, etc due to the complexibities of the reservoir nature, flow behavior. However, this curve fitting technique is still problemtic because the reservoir nature itself and the operation performance are not considered into the analysis, which we believe must be a big deal for determination of ultimate recovery. In this work, the data driven analytics, which is deemed as a smart technique, has been implemented in one asset of Marcellus shale. Different from traditional decline curve analysis, data-driven analytics is a data mining and artificial intelligence based technique, which not only considers measured production data, but also takes reservoir characterisitics and completion data into account. Through this research, we are trying to investigate the impact weight of different groups of parameters such as reservoir characteristics, operational activities on the ultimate recovery determination in shale gas reservoir.

Seeds of Ocimum basilicum L. are used in traditional medicine for stomach ulcers, dyspepsia, diarrhea, pharyngitis, and kidney inflammation [1]. Basil seeds are often included in drinks (sherbet) and frozen desserts (faloodeh) for esthetics and as a source of dietary fiber in Iran and many regions of Asia [2,3]. The external pericarp swells upon wetting with water and forms a gel-like coating [4] because of the presence of a polysaccharide layer.We communicated previously that polysaccharides isolated from O. basilicum seeds consisted of fructose, glucuronic acid, galacturonic acid, rhamnose, xylose, arabinose, and galactose. The principal constituents were xylose, glucuronic acid, and arabinose [5]. In continuation of research in this area, we present results on the isolation and purification of acidic watersoluble polysaccharides from O. basilicum fruit by column chromatography over DEAE-Sepharose CL-6B and Sephadex G-100 and on their structures according to IR and NMR spectroscopy.Pure acidic polysaccharides were obtained using the previously obtained acidic water-soluble polysaccharide (WSPS-H-A) [5]. WSPS-H-A (200 mg) was dissolved in distilled H 2 O (6 mL) and centrifuged for 5 min at 10,000 rpm and 4°C. The supernatant liquid was transferred to a Servacel DEAE-23SN ion-exchange column (25 mm u 25 cm) and eluted with H 2 O and NaCl solutions (concentrations 0.2, 0.5, and 1.0 M). The polysaccharide yield was monitored using the phenol-H 2 SO 4 method.The polysaccharide content in the fraction eluted by H 2 O was 12.6 mg (fraction 1, 6.3%); by NaCl (0.2 M), 170 mg (fraction 2, 80%); by NaCl (0.5 M), 19.5 mg (fraction 3, 9.7%); and by NaCl (1.0 M), 5.1 mg (fraction 4, 2.5%). A total of 98.5% of the polysaccharide fraction was recovered.Fraction 2 (50 mg) was separated by column chromatography over Sephadex G-100 on an HP Polysaccharide Purifier 10 instrument equipped with conductivity, UV, and differential detectors to afford homogeneous fraction 2-1 (13.1 mg yield).The IR spectrum of fraction 2-1 had absorption bands at 3411 cm 1 (OH), 1642 (carboxyl), 1200-1000 (C-Ñ and C-O stretching), 800 (pyranose ring), and 873 (E-glycoside bond) [6].The structure of fraction 2-1 was studied using PMR and 13 C NMR spectroscopy and 2D COSY, HSQC, and HMBC methods.PMR spectra in the region of anomeric protons exhibited four resonances at G 5.30 ppm (strongest), 4.86 (minor), 4.64, and 4.48. Other proton resonances were located in the range 3.2-4.4 ppm. A strong singlet at 3.48 ppm was characteristic of an OCH 3 group. The strong-field spectral region contained a doublet at 1.26 ppm (J = 4.2 Hz) that was characteristic of a rhamnopyranose (Rhap) methyl.The 13 C NMR spectrum showed in the range 100-105 ppm four anomeric resonances at 100.44, 102.79, 104.23, and 104.69 ppm. The first strong resonance belonged to C-1 of D-glucuronic acid (D-GlcpA). The other anomeric resonances were assigned to E-rhamnopyranose (E-Rhap, weak), E-xylopyranose (E-Xylp), and E-arabinopyranose (D-Arap). A resonance at 179.97 ppm that gave a cross-...