Reservoir Characterization. Группа авторов
14.2 Market capitalization and proved reserves – integrated oil companies...Figure 14.3 Market capitalization and production – integrated oil companies (201...Figure 14.4 Market capitalization and total assets – integrated oil companies (2...Figure 14.5 Market capitalization and proved reserves — large-cap independents (...Figure 14.6 Market capitalization and proved reserves — small-cap independents (...Figure 14.7 Market capitalization and total assets – independents (2010).Figure 14.8 Market capitalization and proved reserves – independents (2010).Figure 14.9 Multinational vs. domestic independents market capitalization (2010)...Figure 14.10 Conventional vs. unconventional independents market capitalization ...Figure 14.11 Proved reserves and annual production – independents (2010).Figure 14.12 Market capitalization and proved reserves – state-owned majors and ...
15 Chapter 15Figure 15.1 A comparison of temperature profiles given by different analytical m...Figure 15.2 Effect of formation fluid influx on the temperature profiles.Figure 15.3 Effect of Joule-Thomson cooling on the temperature profiles.Figure 15.4 Effect of entrained drill cuttings on the temperature profiles.Figure 15.5 Sketch illustrating heat transfer in a borehole section.
16 Chapter 16Figure 16.1 Sketch illustrating heat transfer in a borehole section.Figure 16.2 Model-predicted temperature profiles in drilling well NGHP-01-17A.Figure 16.3 Model-predicted temperature profiles with injection mud temperature ...Figure 16.4 Model-predicted temperature profiles with mud flow rate 0.05 m3/s.Figure 16.5 Model-predicted temperature profiles with 3 °C-temperature drop at t...
17 Chapter 17Figure 17.1 Gas-filled formations. The standard deviations of calculated Vp, Vs ...Figure 17.2 Standard deviations of the Vp/Vs ratio for gas and brine saturated f...Figure 17.3 Clusters of (Vp,Vs) velocities for gas-filled and brine-filled forma...Figure 17.4 K-nearest neighbor and the probability of true discovery.Figure 17.5 K-nearest neighbor and the probability of false discovery.Figure 17.6 Recursive partitioning and the probability of true discovery.Figure 17.7 Recursive partition.Figure 17.8 Linear discriminant analysis and the probability of true discovery.Figure 17.9 Linear discriminant analysis and the probability of false discovery.Figure 17.10 The probability of true discovery and the three classification tech...Figure 17.11 The probability of false discovery.
18 Chapter 18Figure 18.1 Vp versus effective pressure for sandstone samples [9] (Zhang and Be...Figure 18.2 Typical Mohr rupture diagram for concrete [13] (Wuerker, 1959).Figure 18.3 Poisson’s ratio versus total porosity [19] (Spikes and Dvorkin, 2004...Figure 18.4 The relationship of Young’s modulus and porosity [20] (Kumar et al ....Figure 18.5 (a) The variation of Young’s modulus with RH [29] (Pham et al ., 200...Figure 18.6 The relationship of Vp-fast & Vs-fast and Young’s modulus with TOC [...Figure 18.7 The relationship of Young’s modulus and TOC [21] (Kumar et al. , 201...Figure 18.8 The relationship of Young’s modulus and clay content [21] (Kumar et ...Figure 18.9 The influence of clay content on UCS [41] (Sone and Zoback, 2011).Figure 18.10 Experimental data showing strength anisotropy in shales [42] (Wills...Figure 18.11 Strength of horizontally and vertically cored samples from Upper an...Figure 18.12 The strength of shale core in different direction [45] (Li et al .,...Figure 18.13 Effect of the bedding angle on compressive failure strength [46] (A...Figure 18.14 The bulk and shear moduli with different mineral concentrations of ...Figure 18.15 The dependence of Young’s modulus on quartz and carbonate [20] (Kum...Figure 18.16 The relationship between Sw and Young’s modulus.Figure 18.17 The relationship between Sw and Poisson’s ratio.Figure 18.18 The relationship between Sw and UCS.Figure 18.19 (a) and (b) The fitting line and the “best” line for E and UCS.Figure 18.20 (a) and (b) The data range analysis for E.Figure 18.21 (a) and (b) The data range analysis for UCS.
19 Chapter 19Figure 19.1 Flowchart of solution for mathematical models for one time step.Figure 19.2 Simulation results under two different time steps.Figure 19.3 Oil and water relative permeability curves (repotted from Parvazdava...Figure 19.4 Comparison of oil recovery change with time after water flooding or ...Figure 19.5 Compared results of normalized effluent concentrations of nanopartic...Figure 19.6 Compared results of normalized effluent concentrations of nanopartic...Figure 19.7 Influence of nanofuids injection time on oil recovery.Figure 19.8 Amount of nanoparticles trapped under different injection time.Figure 19.9 Water saturation distribution at 0.5 PV, 1.5 PV, 2.25 PV and 3 PV re...Figure 19.10 Nanoparticle distribution in the reservoir at the end of the nanofu...Figure 19.11 Oil recovery under different nanofuids injection rates.Figure 19.12 The amounts of nanoparticles trapped in the reservoir at the end of...Figure 19.13 Oil recovery with slug injection of nanofuids under different injec...Figure 19.14 Oil recovery and Water cut against injection time (nanofuids inject...Figure 19.15 Oil recovery with slug injection of nanofuids at different slug siz...Figure 19.16 Oil recovery curves under different length of nanofuids injection t...Figure 19.17 Oil recovery under different flow rate ratio between water flooding...Figure 19.18 Dimensionless nanoparticle effluent concentration at production wel...Figure 19.19 Porosity of the SPE 10B model.Figure 19.20 Comparison results of (a) water saturation under water flooding, (b...Figure 19.21 The distribution of Nanoparticles concentration in water phase afte...Figure 19.22 Nanofuids concentration distribution in the reservoir at different ...Figure 19.23 Nanoparticles concentration distribution on the rock surface at dif...
20 Chapter 20Figure 20.1 (a) The Tensleep horizon interpreted from 3D seismic data shown in s...Figure 20.2 (a) West–east seismic section across the Teapot Dome. The reverse fa...Figure 20.3 Apertures are log-normally distributed in the wireline image logs, C...Figure 20.4 Distributions of the fracture intensity attribute for each zone in t...Figure 20.5 (a) Possible deformation bands are shown by red arrows, note that th...Figure 20.6 The permeability barriers are roughly parallel the S1 fault. The gri...Figure 20.7 Locations of 8 Wells with core data used in Chiaramonte (2009) reser...Figure 20.8 Saturation pressure and swelling factor calculated in the swelling e...Figure 20.9 Fluid viscosity is plotted vs. bubble point pressure at each swellin...Figure 20.10 Streamline analysis on 03-28-2004 for water saturation around produ...Figure 20.11 (a) Model 1 has injectors (I4, I5, and I6) parallel to the main fra...Figure 20.12 A high mole fraction of CO2 is observed at the producers beginning ...Figure 20.13 The oil production for Models 1 and 2 are compared to an oil produc...Figure 20.14 Increasing fault multiplier results in higher oil production for bo...
21 Chapter 21Figure 21.1 Different components of Reservoir Characterization [32].Figure 21.2 Different types of clusters [52].Figure 21.3 Fuzzy clustering to monitor fluid movement in a geothermal reservoir...Figure 21.4 Hierarchical clustering with different proximity functions [42].Figure 21.5 Overview of the ensemble learning method [52].Figure 21.6 (a) Perceptron learning process [11]. (b) Multi layer perceptron arc...Figure 21.7 An illustrative example of CNN architecture [11].Figure 21.8 Illustration of the RNN architecture [49].Figure 21.9 Illustration of the Auto encoder architecture [59].Figure 21.10 Illustration of GANs architecture [41].Figure 21.11 Elements of a 3D structural model [43].Figure 21.12 Proxy dataset maps aligned to data types (right) and concept layers...Figure 21.13 Illustrative workflow from Justman et al. [27].Figure 21.14 Example of domain boundary revision and iteration using an example ...Figure 21.15 Subsurface Trend Analysis (STA) results. Data-based prediction vs. ...Figure 21.16 ANN-based workflow from Thanh et al. [60].Figure 21.17 EOR screening process workflow [35].
Tables
1 Chapter 3Table 3.1 Mean values of false and true discovery rates for three classifers in ...Table 3.2 Mean and three quantiles of distribution of AUC values.Table 3.3 Percent of values of anomalyIndicator exceeding significance cutoff α ...
2 Chapter 4Table 4.1 Results of TOC and Rock-Evaol Pyrolysis for the rock samples analyzed.Table 4.2 Typical biomarker characteristics of shale and carbonate-derived hydro...
3 Chapter 6Table 6.1 Prior rates of false discovery of anomalous clusters, and cluster sets...Table 6.2 Parameters of clusters, labeled as anomalous