bluuebunny/crossref_metadata_2025_split huggingface dataset:
Developing Surfactant to Increase the Production in Heavy Oil Reservoirs
Authors: Khosravi Vahid 
Published: July 2010

AbstractMicro-organisms are the creatures that in the prepared condition for their growth, they can be beneficial for so many fields. One of these fields is Enhanced Oil Recovery. Microbial enhanced oil recovery method (MEOR) includes the usage of Micro-organisms of their productions.One of the most important productions of micro-organisms is surfactants. Surfactants include cationic surfactants, anionic surfactants, and neutral surfactants. These conditions have two parts which are water-wet and oil-wet, and by putting their selves in the surface between oil and water, they decrease the interfacial tension, and in this way they help oil flow going towards wells. For instance, one of the problems in the movement of oil inside an environment of porosity is a phenomena which is called pinching off, in which the surfactants decrease the trapped oil and make it continuous, and this makes the diameter of oil molecules decrease to the size smaller than gate diameter, so that the oil molecules start bypassing.The advantages of these biological combinations compared with their chemical types are as follows: more surface activity, better performance in various temperature conditions, PH, salinity, and being less poisonous. Nc is related to the residual oil saturation through the capillary desaturation curve. The critical capillary number and the shape of the capillary desaturation curve depend on the rock propertiesSuch as pore size distribution and wettability. The more the Nc, the less the IFT, so the oil recovery gets more.The high potential of EOR is illustrated in the fact that over %65 of the original oil-in-place still remains in many worldwide reservoirs after primary and secondary oil recovery. Micro-organisms are used in this method to reduce permeability and homogenization of reservoir by sealing the areas with high permeability. Their productions are being used in other fields too; for example biopolymers are used to increase the viscosity of oil, biosurfactants are used to decrease the interfacial tension of oil-water, biogases and solvents are used to reduce the viscosity and organic acids of oil to increase the porosity by solving the carbonate rocks.
Best Practices in Testing and Analyzing Multilayer Reservoirs
Authors: Pan Yan , Sullivan Michael , Belanger David 
Published: July 2010

Abstract
Layered formations are the norm rather than exception among oil and gas reservoirs. Knowing the individual layer properties is important for making development strategies. It plays a significant role in secondary recovery. This paper presents best practices in the design, execution, and analysis of multilayer pressure transient tests in Tengiz oil field in western Kazakhstan. Our experience proves that the use of multilayer testing and analysis techniques results in a lower level of uncertainty in layered reservoir characterization than can be obtained by the simpler commingled pressure transient test alone.
The formations in the platform area of Tengiz consist of multiple zones with different reservoir pressures; therefore cross-flow often occurs during shut-in periods. In some cases, the impact from different layer pressure and skin distribution could result in 100% difference in individual layer permeability estimations. To reduce the uncertainty, the Selective Inflow Performance (SIP) production logging technique (Stewart et al. 1981) is used to measure the bottom-hole pressures and flow contributions of individual layers during a commingled pressure transient test. Pulsed Neutron Capture logs are also used to provide information about stimulation effectiveness (skin) in each zone. Then a robust step by step analysis method developed to use all data and information is applied to obtain individual layer properties. The best practices of using this methodology and the associated uncertainty are discussed in this paper.
The challenge in characterization of layered reservoirs lies in the large number of unknown parameters. The approach described in this paper resolves enough of these unknowns in a systematic fashion that a more direct solution is obtained with resultant lower uncertainty.
Optimizing Volumetric Sweep Efficiency in Waterfloods by Integrating Streamlines, Design of Experiments, and Hydrocarbon F-F Curves
Authors: Izgec O. , Sayarpour M. , Shook G. M. 
Published: July 2010

Abstract
Waterflooding is by far the most commonly used method to improve oil recovery. Success of a waterflood depends on its ability to sweep remaining oil efficiently. Incorrect or insufficient design may lead to increases in cost associated with water cycling and poor sweep. Most waterflood management is restricted to classical methods (e.g., surveillance or pattern balancing) or sensitivity studies centered on finite difference simulation. Most of the time, conventional methods fail to account for subsurface heterogeneity, while optimizing sweep via conventional modeling is time consuming in waterfloods with large number of wells or a relatively high-resolution numerical grid.
We propose a practical and efficient approach for rapid and full-field optimization of waterfloods. Our method focuses on optimizing volumetric sweep efficiency using streamlines. We introduce two new concepts: the Hydrocarbon F-Φ Curve and Hydrocarbon Lorenz Coefficient (LC-HC). We show that these concepts can be easily derived from streamline simulation and can be used for optimum waterflood management. The LC-HC serves as a unique measure of the flow – or dynamic – heterogeneity, and we show that minimizing LC-HC results in optimal volumetric sweep efficiency. The method is straightforward: we evaluate the sensitivity of LC-HC to variations in operating conditions in a design of experiment (DoE) study, describe the LC-HC as a function of those operating conditions using response surface methods, then select the operating conditions that minimize LC-HC (maximize sweep efficiency). The main advantages of our method are its speed, flexibility to start optimizing at any arbitrary time regardless of the history, and ability to handle large problems. The new approach requires running a streamline simulator only a few time steps, so multi-million cell models are optimized in minutes.
We verified our approach with several synthetic examples. An example shows that a 100,000 cell, complex reservoir with 13 wells, and 29 completions can be optimized in less than 4 hours, leading to significant increase in recovery efficiency and reduced water cycling. We then apply the method to a model of the Brugge field, the SPE comparative problem on recovery optimization. Improved production response illustrates the power of the new method.
The Roles of Nano-Scale Intermolecular Forces on the Film Stability During Wettability Alteration Process of the Oil Reservoir Rocks
Authors: Rahbar M. , Ayatollahi S. , Ghatee M. H. 
Published: July 2010

Abstract
The interfacial phenomenon of spreading and adhesion of fluid on the rock surfaces, known as wettability, has serious implication because of their impact on multi phase flow in the rock hence the recovery efficiency of petroleum reservoirs. However, the prediction of wetting properties and its alteration during the production or any chemical treatment processes is difficult because of the complex chemical composition of the crude oil and the formation brine as well as the interaction with the minerals very close to the rock surface. Many practical techniques to assess the wettability of mineral surfaces are available, but these measurements cannot capture the micro mechanism of wetting and the mechanisms of wettability changes. To understand these mechanisms one needs to investigate the interactions that take place between crude oil, brine and rock surfaces close to the solid-fluids boundary. The objective of this work is to present the results of developed software based on the rock-fluids interactions for the prediction of the wettability state in a solid-liquid-liquid system. In this model, macroscopic contact angle and surface wettability are related to the film stability through disjoining pressure isotherm of the wetting phase film separating the solid and non-wetting phase. Besides, the mechanism of wetting changes and predominant surface forces is diagnosed through disjoining pressure. The contribution of van der Waals, electrostatic and structural forces is identified as the main forces to affect the status of the wetting film through disjoining pressure calculation. In this model some efficient parameters such as pH, brine composition, zeta potential, crude oil composition especially its polarity and acid-base number and crude oil refractive index are considered. This model is especially designed to predict the wettability and its alteration for the tight rocks, which is seldom to be done through the laboratory measurements.
New Insight into Integrated Reservoir Management using Top-Down, Intelligent Reservoir Modeling Technique; Application to a Giant and Complex Oil Field in the Middle East
Authors: Kalantari-Dahaghi Amirmasoud , Mohaghegh Shahab D. , Khazaeni Yasaman 
Published: July 2010

Abstract
This paper demonstrates the validity of a recently developed reservoir modeling technique called "Top-Down, Intelligent Reservoir Modeling" (will be referred to Top-Down Modeling for short). This new modeling technology integrates reservoir engineering analytical techniques with Artificial Intelligence & Data Mining (AI&DM) in order to arrive at an empirical, cohesive and spatiotemporally calibrated full field model. The model is used to predict reservoir performance in order to recommend field development strategies. One of the distinctive features of this technology is its data requirement for analysis. Although Top-Down Modeling can incorporate almost any type and amount of data that is available in the modeling process, it only requires monthly production rate and some well log data (porosity, initial water saturation and thickness) in order to start the analysis and provide a full field model. Presence and incorporation of other types of data such as core analysis, pressure data, reservoir characteristics and seismic data can and will increase the accuracy and validity of the developed model.
In this work, we apply Top-Down Modeling to a large and complex Oil field in the Middle East that produces from a combination of clastic and carbonate formations. Production rates and well log data from 210 wells have been analyzed and imported into the Top-Down Modeling software to develop a new empirical reservoir model and make predictions on new well performance and potential infill locations. Results from Top-Down Modeling analyses are compared with results concluded from a comprehensive reservoir management study (that included use of large amount and various types of data and a commercial numerical reservoir simulator) performed by an IOC. Analytical reservoir engineering techniques used in the Top-Down Modeling presented in this study include production decline analysis, volumetric reserve and recovery factor estimations and are integrated with Voronoi graph theory, geostatistics, two-dimensional Fuzzy Pattern Recognition (FPR), and discrete, data driven predictive modeling.
The resulting full field Top-Down Modeling is used to identify the distribution of the remaining reserves, sweet spots for infill locations and under-performer wells and also identify the locations in the reservoir where gas cap is formed. Furthermore, the fullfield model is used to predict new well’s performance.
Modeling Gas-Phase Mass Transfer Between Fracture and Matrix in Naturally Fractured Reservoirs
Authors: Jamili A. , Willhite G. P. , Green D. W. 
Published: July 2010

Abstract
Gas injection in naturally fractured reservoirs maintains the reservoir pressure, and increases oil recovery primarily by gravity drainage and to a lesser extent by mass transfer between the flowing gas in the fracture and the porous matrix. Although gravity drainage has been studied extensively, there has been limited research on mass-transfer mechanisms between the gas flowing in the fracture and fluids in the porous matrix.
This paper presents a mathematical model which describes the mass transfer in one dimension between a gas flowing in a fracture and a horizontal matrix block. The model accounts for diffusion and convection mechanisms in both gas and liquid phases in the porous matrix. The injected gas diffuses into the porous matrix through gas and liquid phases causing the vaporization of oil in the porous matrix which is transported by convection and diffusion to the gas flowing in the fracture. Compositions of equilibrium phases are computed using the Peng-Robinson EOS.
The mathematical model was validated by comparing calculations to two sets of experimental data reported in the literature (Morel et. al. (1990) and Le Romancer et. al. (1994)), one involving nitrogen flow in the fracture and the second with carbon dioxide flow. The matrix was a chalk. The resident fluid in the porous matrix was a mixture of methane and pentane. In the nitrogen diffusion experiments, liquid and vapor phases were initially present, while in the carbon dioxide experiment the matrix was saturated with a liquid phase.
Calculated results match the experimental data, including recovery of each component, saturation profile, and pressure gradient between matrix and fracture. The simulation revealed the presence of countercurrent flow inside the block. Diffusion was the main mass-transfer mechanism between matrix and fracture during nitrogen injection. In the carbon dioxide experiment, diffusion and convection were both important.
A Multivariate Autoregressive Model for Characterizing Producer-producer Relationships in Waterfloods from Injection/Production Rate Fluctuations
Authors: Lee Kun-Han , Ortega Antonio , Jafroodi Nelia , Ershaghi Iraj 
Published: July 2010

Abstract
In this paper we introduce injector-producer models to characterize communications among wells in waterfloods, using only injection and production data. In other proposed modeling approaches, the producers are often assumed to be independent of each other and to be only influenced by nearby injectors. We present an improved technique based on a multivariate autoregressive model with exogenous inputs (M-ARX), which models the interaction among all injectors and producers (including producer to producer interactions) in a region, using a set of linear differential/difference equations.
By coupling all injection/production rates in a region under analysis, the M-ARX model outperforms other models in terms of prediction performance, while requiring a relatively small number of parameters to be estimated. Also, when the rates of some producers are artificially constrained, e.g., due to shutting-in of a producer, the retraining period of our M-ARX model is significantly shorter, as compared to other models. Moreover, model parameters can be interpreted as the producer-to-producer interactions.
Validation under various scenarios using numerical simulated data shows that the M-ARX model outperforms the capacitance model (CM) in terms of forecasting ability and is much more robust to noise than the finite-impulse-response (FIR) model. The M-ARX model provides estimates of the interwell connectivities that are highly consistent with the results obtained from both CM and FIR models.
In addition, the M-ARX model can be extended to higher orders easily, making it possible to handle more complex and heterogeneous scenarios.
Ensemble Based Optimization of EOR Processes
Authors: Odi Uchenna O. , Lane Robert H. 
Published: July 2010

AbstractThe advent of smart well technology has allowed the control of a hydrocarbon field in all stages of production. This holds great promise in managing EOR processes, especially in terms of applying optimization techniques. However, some procedures for optimizing EOR processes are not based on the physics of the process, which can lead to erroneous results. Additionally, optimization of EOR processes can be difficult if there is no access to the simulator code for computation of the adjoints used for optimization. This work is a general procedure for designing an initial starting point for a surfactant flood and water flood optimization. The method does not rely on a simulator's adjoint computation. Instead of using adjoints for optimization, the Ensemble Kalman Filter optimization (Enkfopt) was developed and used to optimize the net present value (NPV) of a 5 spot surfactant flood and water flood process. Additionally, constrained optimization was created and added to the Enkfopt method. The controls were based on surfactant flood and water flood process dynamics and included production control for four producers, injector injection rate, and surfactant concentration. Field permeability, field porosity, and economic inputs were parameters held constant for the optimization. Once the optimal solution was obtained, multiple realizations of the permeability and economic inputs were used to generate a cumulative probability distribution of the NPV. Preliminary results show an improvement of the NPV of the water flood process (up to 60% increase) and surfactant flood process (up to 150% increase). Results also show that the optimized controls retain the same relationship as the original controls. This work provides a method to manage risk by performing an optimization and then using the optimal solution to assimilate possible geological and economic scenarios. Cumulative distribution curves of NPV provide tools in accessing the probability of project success.
Intelligent Model Management and Visualization for Smart Oilfields
Authors: Chelmis Charalampos , Bakshi Amol , Seren Burcu , Gomadam Karthik , Prasanna Viktor K. 
Published: July 2010

Abstract
Simulation models are commonly used as an aid to decision making for oilfield development and operations. Such models represent information uncertainty and alternate operational strategies and form a design space, which is used by engineers to explore different "what-if" scenarios. As the composition of the engineering team changes over the lifetime of the oilfield and new modeling requirements emerge, it becomes important for engineers to be able to quickly "mine" from and understand the distribution of the models in the design space, and also to know if a particular scenario was already modeled in the past or if a new model needs to be created.
In this paper, we describe a technique to analyze arbitrarily large set of simulation models, identify similarities and differences between model parameters, and automatically cluster the models based on similarity in an n-dimensional design space. The major contribution of this work is a vector space based approach for automatic model clustering without human intervention. Building on this contribution, our system provides a smart browse, search and visualization capability over a legacy model catalog in a non-proprietary manner. The system also performs automatic analysis of available models in order to discover their underlying basic structure and, if possible, represents the models as variations of this basic structure. We demonstrate the application of our algorithm to a set of Integrated Production Modeling (IPM) models. However, our use of a standard, non-proprietary network model abstraction as an intermediate representation means that our analysis technique can be applied to models created using a variety of modeling and simulation tools.
The broader significance of this work is in the context of knowledge management for smart oilfields, specifically focused on extracting meaningful information from legacy simulation models, and making this information available and useful to the domain experts.
Investigation of Trapped Oil Mechanisms and Opportunities for Improved Oil Recovery in Deepwater Gulf of Mexico
Authors: Li Xin , Lach Joseph , Mcmillen Kenneth , Duan Shengkai 
Published: July 2010

Abstract
Deepwater Gulf of Mexico oil fields (DW GoM) typically get modest ultimate recovery factors in the 10% - 35% range, because reservoirs tend to be small, deep, and complex. The remaining oil target for Improved Oil Recovery (IOR) is tempting large, with about 30 Billion Bbl estimated to be left in discovered fields at abandonment. Procedures on by-passed oil mechanisms analysis are based on analysis of field data compiled by Minerals Management Service, on data extracted from focused literature reviews, and on original work to analyze by-passed oil mechanisms and describe the remaining oil distribution in turbidite reservoirs of DW GoM.
This paper describes a study on oil trapping mechanism, by-passed oil categories and their distributions. It is key part of study directed at recommending a select group of IOR processes for multi-million dollar research and development funding by Research Partnership to Secure Energy for America (RPSEA).
The performance of 450 oil reservoirs in 83 deepwater Gulf of Mexico fields has been evaluated and characterized by geological setting, reservoir properties, and development constraints. The results have been used to estimate statistically the average oil recovery, prominent reservoir drive mechanisms, oil trapping due to structural and depositional complexity, and reservoir volume not connected to wells. The term "Trapped Oil Mechanisms" is used in this work to define the reasons for projected remaining oil in-place under current operating practices. In this paper we review the detailed assessment of several signicant reservoirs in two fields and then present the overall summary of trapped oil mechanisms for Neogene reservoirs in the deepwater Gulf of Mexico.
The results of this work are being used to define IOR processes targeted at reducing the projected ROIP.
Numerical Modeling of the Water Imbibition Process in Water-Wet Laboratory Cores
Authors: Kalaei M. Hosein , Green Don W. , Willhite G. Paul 
Published: July 2010

Abstract
Oil recovery from water-wet, naturally fractured reservoirs subjected to waterflooding is governed by spontaneous imbibition of water from the fractures into the matrix rock due to capillary and gravity forces, which results in the displacement of the non-wetting oil. Several parameters, such as wettability, boundary conditions, rock geometry, fluid properties, and IFT between oil and water affect the oil recovery.
A three-dimensional, two-phase numerical simulator was developed to investigate both mechanisms of oil production and the parameters that influence recovery in water-wet laboratory cores. The model was validated by a comparison of calculations to the numerical simulation of Blair (1964) and experimental data presented by Schechter (1991) and Fischer and Morrow (2005). Agreement between model calculations and data was excellent.
When capillary forces are negligible, gravity force causes displacement of the oil spontaneously due to density difference between the oil and water in cores mounted vertically. The effect of reducing the interfacial tension between water and oil on oil recovery by spontaneous imbibition was numerically investigated for a wide range of IFT's in cores oriented vertically and compared against experimental data. The study showed that reducing the IFT between oil and water may dominate the gravity segregation and decrease the rate of imbibition in low permeable cores. However, the ultimate recovery increases when compared to the same system with higher IFT. Comparison of the imbibition curves obtained for the same value of oil/water viscosity ratio revealed that imbibition had its lowest value when the one-end, open-boundary condition was applied on the core. Ultimate recovery was almost the same for all other different boundary conditions.