Erratum to: Characterizing interwell connectivity in waterflooded reservoirs using data-driven and reduced-physics models: a comparative study

Neural Computing and Applications -     

Application of the prins reaction on oleic acid

The probable structure of the various components of oleic acid-formaldehyde adducts is discussed. The adducts are reduced to alcohols by high pressure hydrogenation with copper chromite as a catalyst. The new alcohols are distilled, analyzed and used for the preparation of various esters with carboxylic acids. The esters were evaluated as low temperature lubricant base stocks and low temperature plasticizers.     

Characterizing interwell connectivity in waterflooded reservoirs using data-driven and reduced-physics models: a comparative study

Waterflooding is a significantly important process in the life of an oil field to sweep previously unrecovered oil between injection and production wells and maintain reservoir pressure at levels above the bubble-point pressure to prevent gas evolution from the oil phase. This is a critical reservoir management practice for optimum recovery from oil reservoirs. Optimizing water injection volumes and optimizing well locations are both critical reservoir engineering problems to address since water injection capacities may be limited depending on the geographic location and facility limits. Characterization of the reservoir connectivity between injection and production wells can greatly contribute to the optimization process. In this study, it is proposed to use computationally efficient methods to have a better understanding of reservoir flow dynamics in a waterflooding operation by characterizing the reservoir connectivity between injection and production wells. First, as an important class of artificial intelligence methods, artificial neural networks are used as a fully data-driven modeling approach. As an additional powerful method that draws analogy between source/sink terms in oil reservoirs and electrical conductors, capacitance–resistance models are also used as a reduced-physics-driven modeling approach. After understanding each method’s applicability to characterize the interwell connectivity, a comparative study is carried out to determine strengths and weaknesses of each approach in terms of accuracy, data requirements, expertise requirements, training algorithm and processing times.

     

Modeling,analysis, and screening of cyclic pressure pulsing with nitrogen in hydraulically fractured wells

Cyclic pressure pulsing with nitrogen is studied for hydraulically fractured wells in depleted reservoirs. A compositional simulation model is constructed to represent the hydraulic fractures through local-grid refinement. The process is analyzed from both operational and reservoir/ hydraulic-fracture perspectives. Key sensitivity parameters for the operational component are chosen as the injection rate, lengths of injection and soaking periods and the economic rate limit to shut-in the well. For the reservoir/ hydraulic fracturing components, reservoir permeability, hydraulic fracture permeability, effective thickness and half-length are used. These parameters are varied at five levels. A full-factorial experimental design is utilized to run 1250 cases. The study shows that within the ranges studied, the gas-injection process is applied successfully for a 20-year project period with net present values based on the incremental recoveries greater than zero. It is observed that the cycle rate limit, injection and soaking periods must be optimized to maximize the efficiency. The simulation results are used to develop a neural network based proxy model that can be used as a screening tool for the process. The proxy model is validated with blind-cases with a correlation coefficient of 0.96.     

Designing cyclic pressure pulsing in naturally fractured reservoirs using an inverse looking recurrent neural network

In this paper, an inverse looking approach is presented to efficiently design cyclic pressure pulsing (huff ‘n’ puff) with N₂ and CO₂, which is an effective improved oil recovery method in naturally fractured reservoirs. A numerical flow simulation model with compositional, dual-porosity formulation is constructed. The model characteristics are from the Big Andy Field, which is a depleted, naturally fractured oil reservoir in Kentucky. A set of cyclic pulsing design scenarios is created and run using this model. These scenarios and corresponding performance indicators are fed into the recurrent neural network for training. In order to capture the cyclic, time-dependent behavior of the process, recurrent neural networks are used to develop proxy models that can mimic the reservoir simulation model in an inverse looking manner. Two separate inverse looking proxy models for N₂ and CO₂ injections are constructed to predict the corresponding design scenarios, given a set of desired performance characteristics. Predictive capabilities of developed proxy models are evaluated by comparing simulation outputs with neural-network outputs. It is observed that networks are able to accurately predict the design parameters, such as the injection rate and the duration of injection, soaking and production periods.     

Design of output feedback sliding mode controller for SEPIC converter for robustness

ABSTRACT

This paper presents an output feedback sliding mode control (SMC) of a SEPIC converter whose utilisation areas include MPPT and PFC in industrial applications. Owing to their discrete nature, DC-DC converters represent challenges in modelling therefore special linearisation techniques are required. In this study, state space averaging method, which is one of those linearisation methods, is employed in the modelling phase of the design process. Since SEPIC has non-minimum phase and non-linear characteristics, conventional linear control algorithms offer unsatisfactory performance in the face of disturbances, thereby requiring more advanced control strategies. Recently, SMC technique has gained popularity due to whose robust nature against parameter variations, modelling uncertainties and disturbances. Output Feedback Discrete Sliding Mode Control (ODSMC) is a SMC control algorithm that requires only output to be measured instead of full state vector, thereby eliminating the observer design process. To validate the superiority of the non-linear controller in the case of supply voltage and load current variations with sensor noise, results of numerical simulations that are carried are also given.     

Performance Evaluation of Cyclic Pressure Pulsing in a Depleted,Naturally Fractured Reservoir with Stripper-Well Production

Abstract

We present a parametric study on the operational parameters of cyclic pressure pulsing with N₂ and CO₂. We aim to develop a better understanding of how operational parameters affect the process performance in a shallow, naturally fractured, and depleted reservoir of the Big Andy Field in eastern Kentucky. The study includes analyses of various design parameters such as the injection rate, lengths of injection and soaking periods, cycle rate limits, and number of cycles. Incremental oil production, peak oil rate, and net present value (NPV) are considered as the performance criteria. Analyses have been performed using a single-well, dual-porosity, compositional reservoir model.     

Investigation of production of medical ~(82)Sr and ~(68)Ge for ~(82)Sr/~(82)Rb and ~(68)Ge/~(68)Ga generators via proton accelerator

How to operate~(82)Sr/~(82)Rb and ~(68)Ge/~(68)Ga generators used in the positron emission tomography scan process is explained, and the importance of ~(82)Sr and ~(68)Ge radionuclides for these generators is revealed. To produce medical ~(82)Sr and ~(68)Ge by means of a proton accelerator in an irradiation time of 24 h, a proton beam current of250 l A, and an energy range E_(proton)= 100 →5 MeV, the cross sections and the neutron emission spectrum curves of(p,xn) reaction processes on Rb-85, Ga-69 and Ga-71 targets were calculated, and the activities and yields of the product were simulated for the reaction processes. Additionally, the integral yields of the reaction processes were determined via the calculated cross-sectional curves and the mass stopping power obtained from the X-PMSP program. Furthermore, based on the obtained results, the appropriate reaction processes for the production of ~(82)Sr and ~(68)Ge isotopes on Rb-85, Ga-69, and Ga-71 targets are discussed.