Abstract Monitoring fluid movement is important for selecting infill locations and completion intervals and optimizing production operations in reservoirs producing under waterflood and gravity drainage mechanisms. Estimation of the fluid contacts in the interwell regions can be difficult due to complex interactions between fluid movement and reservoir heterogeneities. Previously, we developed a systematic geostatistical fluid mapping methodology that integrates multiple sources of data and accounts for the spatial correlation and uncertainty due to the sparcity of the data.1 We found that this methodology is more efficient and accurate than the conventional mapping approach. This paper describes several enhancements incorporated into the geostatistical methodology and evaluates their advantages. The major sources of data used in the geostatistical methodology are the surveillance and shale databases. The surveillance data provide the locations of fluids (oil, gas and water) intervals at the wells based on logs. The shale data provide the locations of shales intervals at the wells based on cores and logs. The first step in the methodology is to transform the surveillance and shale data into indicators. Then, the methodology uses indicator variograms to evaluate the spatial correlation of the data. The last step generates multiple equi-probable three-dimensional fluid and shale descriptions using a conditional simulation technique that honors the well data and variograms. The enhancements introduced into the geostatistical methodology account for more information about the data and quantify the quality of the surveillance data. The stratigraphic coordinates and vertical proportion curves account for variations in the reservoir structure and major trends in the data, respectively. The indicator variables for fluid movement at different times and shales in different zones account for the different correlations. The quality variables account for the degree of confidence engineers assign to the log interpretations. Cross-validation of the enhanced methodology consisted of the.estimation of fluid column thicknesses at infill locations and visualization of three-dimensional distributions of oil and gas in a gravity drainage area of Prudhoe Bay. The results of the methodology are in excellent agreement with actual data.
Resonant tunnelling diodes (RTD's) have found various applications in high-speed digital and analog circuits due to their specific advantages associated with the unique folded-back negative differential resistance (NDR) I-V characteristics. As a result of the nonlinearity of RTD's, cellular neural networks (CNNs) designed with RTD's can achieve higher integration density and higher processing speed in comparison to standard CMOS based implementations. This paper describes two implements of RTD's based CNNs: one with RTD's only where RTD's are represented by current sources describing physics-based models, and the other with RTD's and FET's configured in well-known monostable-bistable logic elements (MOBILEs) circuitry. The paper also proposes a new and simple cell structure of MOBILE based CNN for connected component detection. Several image processing operations have been successfully simulated for these two types of CNNs. Simulation results show that RTD based CNNs have excellent performance in terms of complexity, speed and compactness.
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An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Because water is generally free to move across the plant-soil, soil-atmosphere, and plant-atmosphere interfaces it is necessary and desirable to view the water transfer system in the three domains of soil, plant, and atmosphere as a whole. . . it must be pointed out that, as well as serving as a vehicle for water transfer, the SPAC is also a region of energy transfer.John R. Philip (1966)
This paper shows the action potential (spikes) generated from the Hodgkin–Huxley equations emerges near the edge of chaos consisting of a tiny subset of the locally active regime of the HH equations. The main result proves that the eigenvalues of the 4 × 4 Jacobian matrix associated with the mathematically intractable system of four nonlinear differential equations are identical to the zeros of a scalar complexity function from complexity theory. Moreover, we show the loci of a pair of complex-conjugate zeros migrate continuously as a function of an externally applied DC current excitation emulating the net synaptic excitation current input to the neuron. In particular, the pair of complex-conjugate zeros move from a subcritical Hopf bifurcation point at low excitation current to a super-critical Hopf bifurcation point at high excitation current. The spikes are generated as the excitation current approaches the vicinity of the edge of chaos, which leads to the onset of the subcritical Hopf bifurcation regime. It follows from this in-depth qualitative analysis that local activity is the origin of spikes.
