Search results

The purpose of this paper is to present detailed algorithms for simulation of individual and group control of production wells in hydrocarbon reservoirs which are implemented in a finite volume-based reservoir simulator.

The algorithm for individual control is described for the multi-lateral multi-connection ones based on the multi-segment model considering cross-flow. Moreover, a general group control algorithm is proposed which can be coupled with any well model that can handle a constraint and returns the flow rates. The performance of oil production process based on the group control criteria is investigated and compared for various cases.

The proposed algorithm for group control of production wells is a non-optimization iterative scheme converging within a few number of iterations. The numerical results of many computer runs indicate that the nominal power of the production wells, in general, is the best group control criterion for the proposed algorithm. The production well group control with a proper criterion can generally improve the oil recovery process at negligible computational costs when compared with individual control of production wells.

Although the group control algorithm is implemented for both production and injection wells in the developed simulator, the numerical algorithm is here described only for production wells to provide more details.

The proposed algorithm can be coupled with any well model providing the fluid flow rates and can be efficiently used for group control of production wells. In addition, the calculated flow rates of the production wells based on the group control algorithm can be used as candidate solutions for the optimizer in the simulation-optimization models. It may reduce the total number of iterations and consequently the computational cost of the simulation-optimization models for the well control problem.

A complete and detailed description of ingredients of an efficient well group control algorithm for the hydrocarbon reservoir is presented. Five group control criteria are extracted from the physical, geometrical and operating conditions of the wells/reservoir. These are the target rate, weighted potential, ultimate rate and introduced nominal power of the production wells. The performance of the group control of production wells with different group control criteria is compared in three different oil production scenarios from a black-oil and highly heterogeneous reservoir.

The purpose of this paper is to present a detailed algorithm for simulating three-dimensional hydrocarbon reservoirs using the blackoil model.

The numerical algorithm uses a cell-centred structured grid finite volume method. The blackoil formulation is written in a way that an Implicit Pressure Explicit Saturation approach can be used. The flow field is obtained by solving a general gas pressure equation derived by manipulating the governing equations. All possible variations of the pressure equation coefficients are given for different reservoir conditions. Key computational details including treatment of non-linear terms, expansion of accumulation terms, transitions from under-saturated to saturated states and vice versa, high gas injection rates, evolution of gas in the oil production wells and adaptive time-stepping procedures are elaborated.

It was shown that using a proper linearization method, less computational difficulties occur especially when free gas is released with high rates. The computational performance of the proposed algorithm is assessed by solving the first SPE comparative study problem with both constant and variable bubble point conditions.

While discretization is performed and implemented for unstructured grids, the numerical results are presented only for structured grids, as expected, the accuracy of numerical results are best for structured grids. Also, the reservoir is assumed to be non-fractured.

The proposed algorithm can be efficiently used for simulating a wide range of practical problems wherever blackoil model is applicable.

A complete and detailed description of ingredients of an efficient finite volume-based algorithm for simulating blackoil flows in hydrocarbon reservoirs is presented.

Simultaneous hydrofracturing of multiple perforation clusters in vertical wells has been applied in the stimulation of hydrocarbon resources reservoirs. This technology is significantly impeded due to the challenges in its application to the multilayered reservoirs that comprise multiple interlayers. One of the challenges is the accurate understanding and characterization of propagation and deflection of the multiple hydraulic fractures between reservoirs and embedded interlayers.

Numerical models of the tight multilayered reservoirs containing multiple interlayers were established to study hydrofracturing of multiple perforation clusters and its influencing factors on unstable propagation and deflection of hydraulic fractures. Brittle and plastic multilayered reservoirs fully considering the influences of different in situ stress ratio and physical attributes for reservoir and interlayer strata on propagations of hydraulic fractures were investigated. The combined finite element–discrete element method and mesh refinement strategy were adopted to guarantee the accuracy of stress solutions and reliability of fracture path in computation.

Results show that the shear stress fields between adjacent multiple hydraulic fractures are superposed to cause fractures deflection. Stress shadows induce the shielding effects of hydraulic fractures and inhibit fractures growth to emerge unstable propagation behaviors, and a main single fracture and several minor fractures develop. As the in situ stress ratio increases, hydraulic fractures more easily deflect toward the direction of maximum in situ stress, and stress shadow and mutual interaction effects between them are intensified. Compared to brittle reservoir, plastic-enhanced reservoir may limit fracture growth and cannot form long fracture length; nevertheless, plastic properties of reservoir are prone to induce more microseismic events with larger magnitude.

The obtained fracturing behaviors and mechanisms based on engineering-scale multilayered reservoir may provide effective schemes for controlling and estimating the unstable propagation of multiple hydraulic fractures.

This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with similar oil reservoirs. The ultimate objective is to optimize oil extraction from this field by leveraging intelligent technology. Incorporating intelligent technology in oil fields can significantly simplify operations, especially in challenging-to-access areas and increase oil production, thereby generating higher income and profits for the field owner.

This study evaluates the level of maturity of present oil field technologies from the perspective of an intelligent oil field by using criteria for measuring the readiness of technologies. A questionnaire was designed and distributed to 18 competent oil industry professionals. Using weighted criteria, a mean estimate of oil field technical maturity was derived from the responses of respondents. Researchers evaluated the level of technological readiness for Brunei, Kuwait and Saudi Arabia’s oil fields using scientific studies.

None of the respondents believe that the intelligent oil field in Iran is highly developed and has a TRL 9 readiness level. The bulk of experts believed that intelligent technologies in the Iran oil industry have only reached TRL 2 and 1, or are merely in the transfer phase of fundamental and applied research. Clearly, Brunei, Kuwait and Saudi Arabia have the most developed oil fields in the world. In Iran, academics and executive and contracting firms in the field of intelligent oil fields are working to intelligently develop young oil fields.

This study explores the level of maturity of intelligent technology in one of Iran’s oil fields. It compares it to the level of maturity of intelligent technology in several other intelligent oil fields throughout the globe. Increasing intelligent oil fields TRL enables better reservoir management and causes more profit and oil recovery.

The paper intends to offer an understanding of the regional energy integration in the South Cone of Latin America as perceived in Brazil.

It assesses the Brazilian need of energy imports to balance its supply to demand and then reviews the strategy followed by successive Brazilian governments in order to move forward the process of energy integration domestically and, more recently, regionally. The reaction of the Brazilian energy establishment to the integration strategy implemented in the 1990s is studied as well.

The main findings of the paper are that the strategy pursued to regional integration (bilateral commercial contracts) is not providing the benefits originally envisaged and that the main reason for this outcome is the focus on the convergence of national energy regulations and policies.

To move the process of integration forward, the paper proposes that the focus should be on a multilateral agreement that can provide reliability to the national energy systems and can reduce domestic energy prices volatility as well. It is suggested that an agreement on the cooperative management of part of the large hydro and natural gas reservoirs available in the region offers the opportunity to institutionalize multilateral regional security reservoirs.

This paper aims to perform a comparative study between capabilities of two numerical schemes from two main branches of numerical methods for solving hyperbolic conservation equations.

The accuracy and performance of a newly developed high‐resolution central scheme vs a higher‐order Godunov‐based method are evaluated in the context of black‐oil reservoir simulations. Both methods are modified enabling study of applications that are not strictly hyperbolic and exhibit local linear degeneracies in their wave structure.

The numerical computations show that while both schemes produce results with virtually the same accuracy, the Godunov method reproduces slightly more accurate results at the expense of calculation of eigen‐structures.

The paper investigates only one dimensional problems, but the idea can be easily extended to multi‐dimensional problems.

The paper shows the strengths and weaknesses of two practical numerical methods.

Such comparative study has not been published elsewhere and in particular, the performance of numerical methods on simulating hysteresis effect in hydrocarbon reservoirs has not been investigated in detail before.

In this paper, the flow of multiphase fluids in a one-dimensional homogeneous porous media involving the gravity effects is numerically studied using the dominant wave method. The paper aims to discuss these issues.

The numerical scheme used for solving the pressure equations, obtained for the black-oil model, is a backward Euler scheme while the hyperbolic mass conservation equations, derived for both black-oil and Buckley-Leverett models, are solved using the dominant wave method. Higher-order schemes are achieved using either variable derivatives along with the minmod limiter or a MUSCL type interface construction scheme using the Fromm's limiter. The mass conservation equations are solved using the first-order forward Euler method in time. Harten's entropy correction procedure is employed to avoid non-physical expansion shocks.

It was found that the dominant wave method can accurately solve multiphase flow equations involving gravity effects. Numerical experiments also show that both minmod and Fromm's limiters can be successfully used to construct higher-order schemes while the minmod limiter gives slightly more diffuse solutions.

The flow models considered here include two- and three-phase Buckley-Leverett and the black-oil models and the capillary effects are neglected.

The proposed scheme can be efficiently used for solving problems involving non-convex flux functions especially those experienced during gravity drainage process in hydrocarbon reservoirs.

To the best of authors knowledge, this is the first time that the dominant wave method has been used to tackle multiphase flow problems involving gravity effect.

The purpose of this paper is to investigate the performance of a specific class of high‐resolution central schemes in conjunction with the black oil models for hydrocarbon reservoir simulation.

A generalized black oil model is adopted, in which the solubility of gas in both oil and water and evaporation of oil are considered, leading to a system of equations prone to degeneracy. A computer code is generated and three test cases are solved to evaluate the performance of various schemes in terms of accuracy and discontinuity handling.

It is shown that, although some of the central schemes are highly sensitive to the choice of Courant‐Friedrich‐Levy (CFL) number and produce overly diffusive results, a certain type of this class is insensitive to the CFL number and can conveniently handle degenerate equations appearing in the reservoir simulation. The obtained results are compared with those available in the literature, showing merits of this class of schemes in complex reservoir simulation models.

This paper gives the one‐dimensional implementation of the above‐mentioned schemes. Extension to higher dimensional black oil model is currently under development by the authors.

The specific class of high‐resolution central schemes investigated here presents the same level of accuracy as more complicated numerical methods, yet keeping it much more simple, by avoiding Riemann solvers.

The high‐resolution central scheme used in this work has been newly developed and applied to simple scalar hyperbolic equations. It has been adopted for the black oil for the first time.

This paper aims to discuss opportunities for pairing the carbon dioxide (CO₂) points of supply from stationary sources such as power plants, steel and cement production, coal to liquid plants and refineries, with potential oil reservoirs in China.

This study builds a linear optimization model to analyze the tradeoffs in developing CO₂-enhance oil recovery (EOR) projects in China for a range of policy options to match points of supply with the points of demand (oil fields). The model works on optimizing CO₂ application costs by meeting four principal components; CO₂ storage, CO₂ capture, transport costs and additional oil recovery.

This study reveals new opportunities and economic sources to feed CO₂-EOR applications and offers reasonable options to supply CO₂ for potential points of demand. Furthermore, power plants and coal to liquid industries had the most significant and economic contributions to potential CO₂-EOR projects in China. Total annual emission reduction is expected to be 10% (based on 10 Gton annual emissions). The emission reductions and potential CO₂ storage from the different industries as follow; 94% from power plants, 4% from biofuel and 2% from coal to liquid plants.

Carbon capture and storage (CCS) is one practice aiming to reduce the amounts of anthropogenic emissions of carbon dioxide emitted into the atmosphere and reduce the related social costs. However, given the relatively high cost associated with this practice, coupling it with EOR could offer a significant financial incentive to facilitate the development of CCS projects and meet climate change objectives.

The model used in this study can be straightforwardly adapted to any geographic location where industry and policymakers are looking to simultaneously reduce CO₂ emissions while increasing hydrocarbon recovery. The model is highly adaptable to local values in the parameters considered and to include additional local considerations such as geographic variation in capture costs, taxes and premiums to be placed on CO₂ capture in so-called “non-attainment zones” where pollution capture make could make a project politically and economically viable. Regardless of how and where this model is applied, it is apparent that CO₂ from industrial sources has substantial potential value as a coproduct that offsets its sequestration costs using existing, commercially available CO₂-EOR technology, once sources and sinks are optimally paired.

This paper is concerned with the estimation of reservoir parameters in the presence of noise and outliers using neural network (NN) and Bayesian algorithm. The paper aims to discuss these issues.

Outlier detection is of great importance to prediction of time series data. A reliable predictive methodology is proposed based on NN and Bayesian algorithm to efficiency estimates of the parameters of a petroleum reservoir. This strategy is applied to estimate the parameters of Marun reservoir located in Ahwaz, Iran utilizing available geophysical well log data.

For an evaluation purpose, the performance and generalization capabilities of Bayes-ANN are compared with the common technique of back propagation (BP).

The experimental results demonstrate that the proposed hybrid Bayes-NN algorithm is able to reveal a better performance than conventional BP NN algorithms.

Helped oil and gas companies to estimation of petroleum reservoir parameters more accurate than other methods in the presence of noise and outliers.