bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analytical Model for Shale Gas Transportation from Matrix to Fracture Network
Authors: Zeng Yan , Ning Zhengfu , Lei Yu , Huang Liang , Lv Chaohui , Hou Yimeng 
Published: March 2017

Abstract
The matrix of shale gas reservoirs has an extremely low permeability; therefore, fractured vertical wells and multi-stage fractured horizontal wells (MFHWs) are adopted in most cases for exploration purpose. In this context, studying the dynamic pressure in MFHWs in shale gas reservoirs not only provides an important means of obtaining the parameters of shale reservoirs, but also constitutes the basis of evaluating the productivity of shale gas wells. However, existing models for fractured horizontal wells have neglected the heterogeneity of shale gas reservoirs and the seepage mechanism in the nanopores of shale organic matter, and failed to take into account the differences among different occurrence spaces in gas flow characteristics. On that account, in this study, we combined dust gas model (DGM) and generalized Maxwell-Stefan model (GMS) to calculate the apparent permeability considering viscous flow, Knudsen diffusion, surface diffusion and desorption, and introduced these into the macro seepage model to establish a dynamic pressure analysis model considering reservoir heterogeneity and stress sensitivity effect of MFHWs in shale gas reservoirs. Based on the five-linear flow model, this study divides one reservoir into two top reservoir regions, two inner reservoir regions, two outer reservoir regions, and one artificial fracture region. Through analyzing the flow characteristics of different regions, it uses Laplace transformation and regular perturbation methods to solve the model; based on the analytical solution to this model, it plots the dynamic pressure curve and the dynamic productivity curve and carries out flow region division and sensitivity analysis. As indicated by the study results, the model established in this study fits relatively well with actual production data, has a reliable theoretical foundation, and can preferably describe the dynamic changes of pressure in the exploration process of shale gas wells.
Fluid Contact Monitoring Using API Tracking. A Novel Methodology for Reservoir Surveillance
Authors: Paredes J. E. , Carbajal A. , Izquierdo R. , Loyo I. , Pérez R. , Perera L. M. , Larez C. J. 
Published: March 2017

Abstract
There are different methods to estimate the current water-oil contact (WOC) or gas-oil (GOC) contact depth in a reservoir. Reservoir engineers has commonly use PLT, RST logs, material balance and simulation models with this purposed but they implied cost, man-hours and to have a great understating of the reservoir. Previous published work1 proposed two diagnostic plots to estimate WOC or GOC depth at well level and to estimate water or gas breakthrough using only measurement of °API, proving to be practical and accurate. This work was based on the effect in the reservoir of a compositional gradient.
In this paper, a conceptual simulation model was built to prove the effect of the produced °API of the presence of a compositional gradient in the reservoir. Results will show that distribution of °API value in the reservoir will cause change, at surface level, in the measurement of this property during the exploitation cycle, decreasing or increasing depending on weather the reservoir is undergoing a WOC or GOC displacement. The results obtained with the conceptual simulation models present the same behavior describe by other authors and could be translated to real models, and more important prove that changes in the °APi values at surface level are a direct consequence of fluid displacement when the reservoir have a compositional gradient.
Finally the methodology used in the conceptual simulation model for °API monitoring was applied to two reservoirs, one with known aquifer influence and other with a secondary gas cap. Both reservoir had enough historical °API measurement to establish a comparison between simulated and real data. The results show that the numerical models are able to reproduce the historical °API behavior and reinforcing the practicality of predict the breakthrough of fluids using only °API measurements on surface.
Numerical Assessment of Biogenic Souring and Its Inhibition in a MEOR Field Pilot
Authors: Alkan H. , Kögler F. , Dopffel N. 
Published: March 2017

Abstract
Under certain conditions, injection of water or other solutions may result in H2S production, which creates additional challenges for EOR applications. Besides serious health and safety concerns, this can cause significant production problems such as reduced quality of hydrocarbons, reduced productivity of wells and increased corrosion. The numerical assessment of the souring and its successful inhibition for an MEOR (Microbial Enhanced Oil Recovery) application in a Wintershall mature oil field is the subject of this paper. The numerical assessment of the biogenic souring for the field studied was performed in three successive steps. In the first step the potential H2S generation as well as its partitioning between various phases was calculated by analytical methods. The spatial distribution of the potential H2S generation was predicted by using the CMG Stars reservoir simulator on a sector model representing the reservoir portion relevant for the application. In a third step a reactive transport model was used to evaluate the implications of an H2S inhibitor injection due to reactions with formation water and rock.
A significant H2S formation potential was determined considering the formation water sulfate content and the MEOR metabolism. Its portitioning in various phases was calculated for various thermodynamic conditions of the production sequences. The spatial modeling of the H2S generation was done in a previously performed CMG Stars implementation of the MEOR simulation for the case studied. The stoichiometry of the reactions applied was calibrated by using laboratory growth and metabolism data. Various strategies were studied to inhibit the souring at laboratory scale with nitrate being one of the inhibitors tested. Potential microbial induced calcite precipitation (MICP) when using nitrate and its effect on the storage and conductivity properties of a reservoir was modelled using the reactive transport computer code TOUGHREACT. The results obtained led to the key decision for testing other souring inhibitors for the field application. The results of the numerical assessment are discussed in terms of its contribution to the decision quality of the risk management concept developed and applied in the field pilot.
Use of a Probabilistic and Multi-Objective History Matching for Uncertainty Reduction for the Norne Benchmark Case
Authors: Ferreira Carla J. , Davolio Alessandra , Schiozer Denis J. 
Published: March 2017

Abstract
History matching integrated with uncertainty reduction is a key process in the closed loop reservoir development and management methodology which is used for decision analysis related to the development & management of petroleum fields. Despite developments over the last decades in history matching & uncertainty analysis, the challenge of capturing complex interaction among several attributes and several reservoir responses acting simultaneously for complex models still remains. This paper describes the use of a probabilistic and multi-objective history matching integrated with uncertainty reduction as a systematic and iterative process for obtaining a set of reservoir models that honors dynamic data in a complex field case. The methodology is an iterative process that simultaneously matches different objective functions, one for each well production profile. The procedure uses a re-characterization step, where the uncertainties of the attributes (represented by their probability density functions) are updated using indicators that show global and local problems and a correlation matrix to capture the interaction between several reservoir uncertainties and the different objective functions. The methodology was applied to the Norne Field benchmark case considering production data up to 2001 and the remaining part of the provided history is used to estimate the quality of production forecast. The major benefit derived from the application of the methodology was the identification of global and local problems. The initial reservoir models presented high discrepancies between simulated and observed data. The use of independent objective functions in conjunction with the concise plot that is based on the normalized quadratic error of each production data highlighted when new parametrization of the reservoir was necessary. New reservoir attributes were added, such as separated permeability curves for each reservoir formation and new gas permeability curves that better describe the fluid behavior. The initial number of uncertain attributes was twenty seven; the correlation matrix clearly showed which one of those had major influence on the results. Some attributes with significant impact in the study were water-oil and gas-oil contact and faults transmissibility. We updated the probability of the most influencing attributes in order to identify the uncertain levels that improved the history match results. The methodology integrated the process of history matching with uncertainty analysis, addressing both processes simultaneously for a complex case. The methodology was effective and simple to use, even in the complex case study where the reservoir characterization is important.
Accurate Reactive Transport Modeling in Heterogeneous Reservoirs with the Dual Mesh Method
Authors: Bruyelle Jérémie , Audigane Pascal , Guérillot Dominique 
Published: March 2017

Abstract
This paper recall the Compositional Dual Mesh Method, an extension to the concept of dual mesh for reactive transport modeling. This approach involves two meshes, a low-resolution mesh to resolve the pressure equation and a high-resolution mesh to transport the species and to calculate the geochemical equilibrium. Geochemical equilibrium being very sensitive to the concentration, preserving the fine heterogeneities leads to a more accurate field behavior simulation than conventional approach which consist in performing simulations on a coarser mesh. The method is applied to a simulation of CO2 storage in a geological model representing a fluvial deposit with a complex realistic architecture that keep a high resolution of the heterogeneities.
Compaction and Dilation Effects on Polymer Flood Performance
Authors: Wang D. , Seright R. S. , Moe Soe Let K. P. , Bhoendie K. , Paidin W. R. 
Published: March 2017

Abstract
During recent field applications of polymer flooding in unconsolidated reservoirs, questions have arisen concerning the role of compaction and/or dilation on flood performance. The primary goal for this paper was to assess the extent to which the compressible nature of a formation affects polymer flooding. The Tambaredjo field in Suriname (with in-situ oil viscosity ~600 cp) was used as a model for this study. Comparisons were made during simulations where formation compressibility was 5.6 × 10-4 psi-1 versus 1 × 10-6 psi-1. During a simulated 17-year compaction drive with compressibility of 5.6 × 10-4 psi-1, water cut gradually increased to average 20% (consistent with the actual field performance)—compared to 2% if compressibility was 1 × 10-6 psi-1. Oil recovery during this period was 18% OOIP for the highcompressibility case versus 3% OOIP for the low-compressibility case. Subsequent to the above compaction drive, incremental oil recoveries from waterflooding and polymer flooding were significantly less (about half in our case) when compressibility was 5.6 × 10-4 psi-1 than when compressibility was 1 × 10-6 psi-1—simply because the oil recovery target was less. For the many waterflooding and polymer flooding cases, most incremental oil was recovered within five years of starting injection—regardless of formation compressibility. Water cuts rose to high values within five years of injection, regardless of the viscosity of the injected fluid and the compressibility value. Consistent with the actual field application, the response to polymer injection varied greatly from well to well. However, our analysis indicated that these variations were due to existing heterogeneities within the pattern—not to the high compressibility of the formation. During simulation, polymer injection increased porosity by factors up to 1.5 and permeability by factors up to 2.3. Nevertheless, compaction or dilation had a fairly even (proportionate) effect on porosity and permeability throughout the pattern. If polymer injection was stopped after the simulated peak in porosity was reached (after 4-6 years of injection) and compaction was allowed to resume, a modest level of oil recovery resulted from this second compaction period (25%-38% of the incremental oil during polymer injection). However, substantially longer was required for the recovery (15-17 years versus 4-6 years for polymer flooding). Consequently, relying on re-compaction during this period of low oil prices may not be as profitable as one might hope. Our work suggests that there is an optimum rate, viscosity, and pressure for polymer flooding compressible formations. Flooding too rapidly results in pressures that waste much of the injection energy on dilating the formation—thereby detracting from efficient displacement of the oil. These constraints restrict injection rate, viscosity, and pressure to a greater degree for very compressible formations than for incompressible formations.
Representative Sector Modeling and Key Factors Impact on Waterflooding Performance of a Large Multi-Layered Sandstone Reservoir
Authors: Yong Li , Benbiao Song , Baozhu Li , Changbing Tian , Yixiang Zhu , Qihao Qian 
Published: March 2017

Abstract
M1 reservoir is a large multi-layered sandstone reservoir of deltaic environment with oil bearing area more than 500Km2. And M1 is influenced by fluvial, tide and wave, which results in great variations of sand bodies’ distribution, reservoir quality and connectivity. So it is essential to use high resolution models capturing reservoir heterogeneity for this kind of reservoirs. This paper presents an approach to representative sector modeling and key factor impact on waterflooding performance study for a large sandstone reservoir in Middle East.
Firstly, Criteria of selecting representative sector models are established combining understanding of geological and dynamic characterization. Take one sector model for example, geological modeling process are detailed, and nine equal-probability geocellular models are built. Then model performances are compared through specific waterflooding patterns. Through detailed performance comparison of each well, each zone and each model of the 9 dynamic models, the reasons for model performance difference and key impacting factors on waterflooding performance are determined. And three models are selected as the optimistic, likelihood and pessimistic model for next development strategy optimization study.
For the multi-layered sandstone reservoir, three representative sectors are selected mainly based on the geological features of M1. One typical sector model is selected to show the details workflow of the approach. Nine geocellular models are built for the sector, which combined three different lateral connectivity patterns with three vertical gridding approaches representing different vertical connectivity. And through detailed model performance comparison, eight key factors impacting on waterflooding performance are determined. And four key factors impact on waterflooding performance are shown in detail.
This paper offers a case study of representative sector modeling and model selection for a multi-layered sandstone reservoir, and it also provide how to analyze the key factor impact on waterflooding performance. The results lay a foundation for the development strategy study and development plan designing. It also provides a methodology and reference case for engineers to study on other similar reservoirs.
CO2 Storage and Enhanced Gas Recovery: Using Extended Black Oil Modelling to Simulate CO2 Injection on a North Sea Depleted Gas Field
Authors: Iogna A. , Guillet-Lhermite J. , Wood C. , Deflandre J. P. 
Published: March 2017

Abstract
Offshore enhanced gas recovery (EGR) by CO2 injection is a potential solution to reduce greenhouse gas emissions and increase recoverable reserves on mature gas assets.
The main objective of the paper is to determine if an Extended Black Oil simulator could be used for EGR simulation on dry gas reservoir to quantify the incremental recoveries that could be achieved on a typical Southern North Sea mature gas field.
Technical and geological criteria governing a successful CO2 EGR programs have been assessed on simplified shoebox reservoir simulations in order to better understand EGR in preparation for full field model upscaling. Results have been compared with a full compositional model to validate the use of a CO2 solvent module as simulation simplification.
Shoebox simulations using an extended black oil model suggest that EGR is achievable on relatively homogeneous reservoirs with an incremental technical recovery factor ranging from 1 to 10%. Use of both vertical and horizontal shoebox models allowed assessment of sweeping efficiency in both dimensions and oriented completion and selectivity strategies. Sensitivity studies confirmed the link between recoverable reserves and CO2 injection flowrates and the risk of preferential paths when the reservoir is fractured or highly heterogeneous.
Upscaling from a simplified shoebox to a full field model has been realized on a depleted Southern North Sea field with sensitivities on injection flowrate, well conversion sequence and CO2 production cut off.
Using Extended Black Oil models for EGR project assessment has been demonstrated as a valid fast-track alternative for dry gas field EGR versus using full Compositional models, which requires more technical data, modelling workforce and computing time.
Mobility Control using Nanoparticle-Stabilized CO2 Foam as a Hydraulic Fracturing Fluid
Authors: Emrani Arezoo S. , Ibrahim Ahmed Farid , Nasr-El-Din Hisham A. 
Published: March 2017

Abstract
CO2-foam has been used as a fracturing fluid to develop unconventional resources and specifically for water-sensitive reservoirs. CO2-foam not only reduces formation damage by minimizing the quantity of aqueous fluid which enters the formation, but also reduces the water consumption for environmental conservation purposes. CO2-foam as a hydraulic fracturing fluid provides for rapid cleanup during flowback. Although it is common to use surfactants to generate and stabilize foams, they tend to degrade at high temperatures (&gt;212°F) and in high-salinity environments. The present work evaluates new foaming solutions that incorporate nanoparticles to investigate the mobility-control performance when such foams are used as hydraulic fracturing fluids.
Of special interest in this work is the study of mobility reduction factor (MRF) of CO2 foam, generated with polymer-based solution, e.g., guar gum, in the presence and absence of nanoparticles, to assess the apparent fluid viscosity at high temperature and high salinity. To achieve this objective, coreflood tests were conducted on different Buff Berea sandstone cores at both 77 and 250°F. CO2 gas was injected with the different solutions simultaneously to generate foam with 80% quality. The pressure drop across the core was then measured to estimate the MRF.
Results show that alpha olefin sulfonate (AOS) improves the MRF by 300% compared to NaCl solution. Adding silica nanoparticles and guar-gum to the AOS solution improves both foam stability and MRF. At 250°F, the AOS solution retained foam stability, while the MRF increased to 28 compared to that of at 77°F.
Choice of surfactant concentration is a critical parameter in generating stable foam. However, the economical use of surfactants is limited by various factors such as surface adsorption, process cost, surfactant loss, and surfactant degradation at high-temperature reservoirs. Nanoparticle solutions can be employed to improve CO2 foam stability as well as MRF factor. Adding nanoparticles is highly recommended for hydraulic fracturing applications, particularly in fracturing stimulation at high-temperatures.
Integration of Highly Permeable Thin Layers Into Flow Simulation
Authors: Correia Manuel Gomes , Schiozer Denis José 
Published: March 2017

Abstract
Giant reservoirs such as Lula (Santos Oil Basin, Brazil) and Ghawar (Saudi Arabia) have high permeability intervals, known as super-k zones, associated with thin layers. Modeling these small-scale flow features in large-scale simulation models is complex. Current methods are limited by high computational costs or simplifications that mismatch the representation of these features in simulation grid blocks. This work has two purposes: (1) present an upscaling workflow to integrate highly laminated or inter-bedded reservoirs with thin, highly permeable layers in reservoir simulations through a combination of (a) an explicit modeling of super-k layers using Parsons (1966) formula and (b) dualmedium flow models, and (2) compare this method with two conventional upscaling approaches, available in commercial software.
We use the benchmark model UNISIM-II-R, a fine single-porosity grid based on field information from the Brazilian Pre-salt and Ghawar oil fields, as the reference solution to compare the upscaling matching between the three methods. We compare; oil recovery, water cut, average reservoir pressure, waterfront, and the time consumption for simulation. Our proposed parsons dual-medium (PDP) methodology achieved better upscaling matches with the reference model and had minimal time consumption when compared with the representation of super-k layers through an implicit matrix modelling by single porosity flow models (IMP) and through the explicit representation of super-k zones in the fracture system of dual-medium flow models (DFNDP).