bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Method for Calculating More Accurate Stratigraphic Positioning of Horizontal Wells Using Continuous Inclination and Azimuthal Gamma Ray Images Even While Sliding
Authors: Gutiérrez Carrilero Susana , Holmes Anne , Hinz David , Wang Jiaxin , Crawford Jeffrey , Stockhausen Ed , Wang Haijing 
Published: October 2018

Abstract
Geosteering long lateral wells in narrow target windows demands accurate stratigraphic positioning, true vertical depth (TVD) positioning, and apparent dip determinations. Using positive displacement motors with alternating slide and rotate drilling modes to control the well trajectory, along with standard 90-ft surveys and single-detector azimuthal gamma ray (GR) tools, have proven to be inadequate. To overcome these issues, a new method has been developed that combines continuous measurements and uses a four-detector azimuthal GR tool.
The bottomhole assembly (BHA) used here is equipped with two inclinometer packages and a four-detector azimuthal GR logging-while-drilling (LWD) tool. A high-resolution survey is calculated using a combination of the two continuous inclination survey data sets for the deeper portion of the well and the stationary survey data from the shallow (low inclination) portion of the well, which provides a more accurate well path that better reflects the TVD positioning of the wellbore. The four-detector azimuthal GR tool is used to generate high-quality wellbore images, both while sliding and rotating. This enables more accurate structural dip angles to be determined from the continuous GR images. It also leads to better stratigraphic and structural positioning of the wellbore and a better understanding of changes in stratigraphy across the length the lateral section. Combining more accurate surveys with complete GR images and more accurate dip picking enables a better determination of the stratigraphic position of the wellbore and its path through stratigraphic layers. The wellbore can be divided into various up- and down-drilled sections that can be compared side-by-side using true vertical thickness (TVT) methods to show lateral continuity of the beds.
Successful Replacement of Conventional Organophilic Clay with Novel Polymer as Viscosifier and Filtration Control Agent in Mineral-Oil-Based Drilling Fluids
Authors: Zhou Jing , Cortes Jairo , Nasr-El-Din Hisham 
Published: October 2018

Abstract
Oil-based drilling fluids (OBDF) can enhance wellbore stability in water-sensitive reservoirs and protect metal surfaces of drilling equipment to minimize corrosion due to H2S and CO2. Components of OBDF include oil as the continuous phase and water as the dispersed phase, in conjunction with viscosifiers, emulsifiers, filtration control agents, and weighting materials. Two of the most common types of continuous phases in oil-based drilling fluids are diesel and mineral oil. Mineral oil is less toxic than diesel, and oil retention properties of OBDF with mineral oil are less than OBDF with diesel. Organophilic clays are clay minerals that have been treated with oil-wetting agents, which will make the clay oil-dispersible. Organophilic clays mixed in OBDF do not exhibit same viscosity or suspension characteristics as in water-based drilling fluids, because electrical interaction between particles is minimal, making it difficult to build viscosity and gel strength in high pressure and high temperature (HP/HT) wellbore conditions. A new mineral-oil-based drilling fluids (MOBDF) proposed was obtained by the successful replacement of conventional organophilic clay with a novel polymer.
Conventional organophilic clay and novel polymer were aged at 150°F for 16 hours. To evaluate the alteration of the wettability caused by the MBDOF and its components, surface tension and contact-angle measurements were made in the laboratory. With similar weight proportions, the apparent and kinetic viscosities of organophilic clay and cross-linked polymer were also compared.
Rheological properties and filtration characteristics tests were conducted using a rotational viscometer and a HP/HT filter press, under three simulated wellbore conditions (140°F/ 300 psi, 190°F/300 psi, and 250°F/500 psi). Filter cake is formed due to positive pressure between OBDF and pore throats pressure. As a barrier between wellbore and formation, it can minimize solids and fluids invasion. Core flooding test was conducted to evaluate permeability of the filter cakes and CT scan was used to measure the density distribution of the filter cakes. Emulsion droplets formed by mixing MOBDF filtrate fluids with formation water were observed to analyze emulsion plugging damage.
Experimental results show that the novel polymer has a promising future of practical application, by providing thermal stability and stable rheological properties for MOBDF in HP/HT conditions. It also brings lower filtration volume, higher quality filter cake and slightly greater emulsion plugging damage to formations than organophilic clay-based drilling fluids.
Advanced Formation Evaluation to Optimize Shale Development in Permian Basin
Authors: Ingerman Vladimir 
Published: October 2018

Abstract
Permian Basin reserves exceed the reserves of the largest conventional field in the world, Ghawar, Saudi Arabia [1].
To develop this field many companies use ‘factory drilling’ or ‘geometrical approach’. This approach decreases the cost of drilling and make sense for source rocks because these are hydrocarbons saturated rocks or the rocks where hydrocarbons have been cooked. Geometrical approach would be ideal for homogeneous formations, but as it will be shown below shale place are very inhomogeneous vertically and laterally. While a drilling cost for a single well is reduced, this approach significantly increases the overall development costs and environmental impact because of drilling a big number of low producing wells.
We found the way to solve this problem developing a technology that uses standard open-hole log data to calculate Production Profile that shows predicted production along the entire well.
Optimizing Drilling Parameters Using a Random Forests ROP Model in the Permian Basin
Authors: Nasir Ehsaan , Rickabaugh Caleb 
Published: October 2018

Abstract
A random forests Rate Of Penetration (ROP) model, along with heat maps, was used to challenge and optimize the drilling parameters for new wells based on the surface drilling data acquired from previous wells. The goal was to analyze the data to observe surface drilling parameter trends aiding in increased bit life and reduced bit wear resulting in maximizing ROP and minimizing Mechanical Specific Energy (MSE).
The four key variables investigated were weight on bit (WOB), surface RPM, mud flowrate and the drilling formation. Surface drilling data for this study was utilized from wells, within a 20 mile radius, where the same bit and motor drilled the entire vertical interval to TD. Heat maps and ROP models (created using support vector regression, random forests and boosted trees) were employed for this purpose. Data was cleaned up using cutoffs (from the minimum and maximum values expected by the drilling engineer) and plotting data distributions. K-fold Cross validation was applied when generating the ROP models. The aim was to focus on the optimization of drilling parameters using surface data only, due to the lack of sub-surface data availability. Using the methodology developed, the drilling parameters could be optimized to extend bit life and reduce bit trips by maximizing ROP and minimizing MSE.
The random forests ROP model was found to be the best with a 12% mean absolute error. The error could have been reduced further by introducing additional variables into the model that capture the changes in formation mechanical properties, downhole parameters and vibrations. This paper only focuses on learnings from surface drilling data. After a certain threshold (which differed for the different formations encountered) an increase in WOB didn' t result in a corresponding increase in ROP. Moreover, most of the ROP gains were observed to be in the shallower formations drilled. For the deeper formations, it was more beneficial to reduce MSE as the ROP was relatively lower no matter what the parameters.
This study used random forests, support vector regression and boosted tree methods to generate ROP models instead of neural networks. Even though neural networks are the most extensive, random forests are generally faster and were the most accurate of the three aforementioned methods used. The less time and computational resources required when compared to neural networks made random forests an attractive option for such a study.
Augmenting Hybrid Physics-Based Multivariate Analysis with the Alternating Conditional Expectations Approach to Optimize Permian Basin Well Performance
Authors: Lolon Ely , Agarwal Karn , Mayerhofer Michael , Oduba Oladapo , Melcher Howard , Weijers Leen 
Published: October 2018

AbstractThe oil and gas industry has used multivariate analysis (MVA) to evaluate how geology, reservoir, and drilling/completion parameters (well characteristics) relate to well production. Although many techniques are used, multiple linear regression (MLR) has been especially popular due to its ease of use and the interpretability of its parameters. However, when the relationship between response and predictor variables is highly complex or nonlinear, this technique can yield erroneous and misleading results. Recent work showed the benefit of combining statistical MLR with fracture and numerical reservoir (physics-based) modeling, which yields a more physically realistic production response to suggested completion changes (Mayerhofer, 2017). However, this work is limited to using the nonlinear relationships between production outcomes and only a few independent variables (i.e., proppant/fluid volumes pumped and fracture spacing). For practicality, other important predictors are still assumed to be linearly correlated to the response variable (e.g., predicted cumulative oil).In this paper, we describe the implementation of the Alternating Conditional Expectations (ACE) approach and the interpretation of its results, and we highlight the main advantages and limitations of the approach in MVA using a simulated dataset and field data from the Permian Basin. The ACE approach is a non-parametric regression method (i.e., no explicit assumption about the relationships between dependent or response and independent or predictor variables is required). It maximizes the linear correlation between the response and predictor variables in the transformed space (the optimal transformations are derived solely from the given data) resulting in higher R-squared (R2) and smaller Root-Mean-Square-Error (RMSE) values compared to those obtained from the MLR. Because a priori assumptions about the functional form for a transformation (e.g., linear, monotonic, periodic, and polynomial) do not have to be imposed, the ACE-guided transformation can give new insights into the relationship between the response and predictor variables.We have successfully identified nonlinear relationships between well production and completion/reservoir properties for horizontal wells in the Permian Basin by means of ACE plots, and we have developed closed functional forms for these relationships. When integrated into the overall workflow of MVA, coupled with completion cost models, the ACE model could produce more realistic and accurate well performance predictions— using not only completion/reservoir parameters that are easily calibrated or "history-matched" as in the physics-based models, but also parameters that cannot be conveniently evaluated with the physics-based models.
Is There Anything Called Too Much Proppant?
Authors: Srinivasan Karthik , Ajisafe Foluke , Alimahomed Farhan , Panjaitan Maraden , Makarychev-Mikhailov Sergey , Mackay Bruce 
Published: October 2018

Abstract
Unconventional completions in North America have seen a paradigm shift in volumes of proppant pumped since 2014. There is a clear noticeable trend in both oil prices and proppant volumes – thanks to low product and service costs that accompanied the oil price crash in early 2015. As the industry continues to recover, operators are reevaluating completion designs to understand if these proppant volumes are beyond what is optimal. This paper analyzes trends in completion sizes and types across all major unconventional oil and gas plays in the US since 2011 and tracks their impact on well productivity.
Completion and production data since 2011 from more than 70,000 horizontal wells in seven major basins (Gulf Coast, Permian, Appalachian, Anadarko, Haynesville, Williston and Denver Julesburg basins) and 11 major oil/gas producing formations were analyzed to examine developments in proppant and fluid volumes. Average concentration of proppant per gallon of fluid pumped was used to understand transitional trends in fracturing fluid types with time. Production performance indicators such as First month, Best 3 or Best 12 months of oil and gas production were mapped against completion volumes to evaluate if there are added economic advantages to pumping larger designs.
In general, all major basins have seen progressive improvements in average well performance since 2011, with the Permian Basin showing the highest improvement, increasing from an average first-six-months oil production of 25,000 bbl in 2011 to 75,000 bbl in 2017. The Gulf Coast basin, where the Eagle Ford formation is located, has seen a 6-fold increase in proppant volumes pumped per foot of lateral since 2011 while the Permian and Appalachian basins hit peak proppant volumes in 2015 and 2016 respectively. In Permian and Eagleford wells, higher proppant volumes in general have resulted in better production up to a certain concentration. In Williston and Denver basins, most operators are moving away from gelled fluids, and reduced average proppant concentration per fluid volume pumped shows inclination toward hybrid or slickwater designs. While some of these observations are tied to reservoir quality, proppant volumes have begun to peak as operators have either reached an optimal point or are in the process of reducing volumes.
Demand for proppant is expected to nearly double by 2020. As oil prices continue to recover, well AFEs continue to increase, despite multiple efforts to improve capital efficiency. The need for enhanced fracture conductivity and extended half-lengths on EURs are been discussed by combining actual observed production data and sensitivities using calibrated production models. The industry is moving toward large-volume slickwater fracturing operations using smaller proppants, but he operating landscape is expected to see a correction when such designs become less economical.
Modeling of Matrix-Fracture Transfer with Non-Uniform Block Distributions in Unconventional Low-Permeability Fractured Reservoirs
Authors: Ding Didier-Yu 
Published: October 2018

Abstract
Unconventional tight-oil and shale-gas reservoirs are usually naturally fractured, and developing this kind of reservoirs requires stimulation via hydraulic fracturing to create conductive fluid flow paths via open fracture networks for practical exploitation. The presence of the multi-scale fracture network, including hydraulic fractures, stimulated and non-stimulated natural fractures, and micro-fractures, increases the complexity of the reservoir simulation. The matrix block sizes are not uniform, and they can vary in a very wide range, from several tens of centimeters to several tens of meters. In such a reservoir, the matrix provides most of the pore volume for storage, but makes few contributions to the global flow, while the fracture supplies the flow, however, with negligible contributions to reservoir porosity. The hydrocarbon is mainly produced from matrix-fracture interaction. So, it is essential to model accurately the matrix-fracture transfers with a reservoir simulator.
For the fluid flow simulation in tight-oil and shale-gas reservoirs, dual-porosity models are widely used. In a dual-porosity model, fractures are homogenized, and a shape factor, based on the homogenized matrix block size, is applied to model the matrix-fracture transfer. However, in real cases, the discrete fracture networks are very complex and non-uniformly distributed. One cannot determine an equivalent matrix block to compute the shape factor. So, a dual-porosity model is not accurate for the simulation of tight-oil and shale-gas reservoirs due to the presence of complex multi-scale fracture networks.
In this paper, we will study the MINC (Multiple Interacting Continua) method for the flow modeling in fractured reservoirs. MINC is usually considered as an improvement of the dual-porosity model. However, a standard MINC approach, using transmissibilities derived from the MINC proximity function, cannot always handle correctly the matrix-fracture transfers when the matrix block sizes are not uniformly distributed. To overcome this insufficiency, we present some new approaches for the MINC subdivision and the transmissibility computations. Several examples are presented to show that using the new approaches improves significantly the dual-porosity model and the standard MINC method for non-uniform block size distributions.
Boosting Oil Recovery in Naturally Fractured Shale Using CO2 Huff-n-Puff
Authors: Pankaj Piyush , Mukisa Herman , Solovyeva Irina , Xue Han 
Published: October 2018

Abstract
Although hydraulic fracturing in Liquid-Rich Unconventional Reservoirs (LUR) have become a norm, the recovery factor continues to be low. Use of Enhanced Oil Recovery (EOR) techniques in LUR have recently become more popular to improve the recovery. The objective of this study is to numerically investigate the advantages and disadvantages of the application of CO2 huff-n-puff technique in the LUR formations having complex fracture networks.
The study explores the fluid flow mechanisms for oil recovery in the naturally fractured reservoir. A calibrated 3D mechanical earth model with geomechanical and petrophysical property from the Eagle Ford was used for the study. Complex hydraulic fracture model was used to simulate the hydraulic fractures, proppant and fluid distribution around the wellbore. Numerical reservoir simulation on a Perpendicular Bi-section (PEBI) grid was used to capture the permeability, porosity and conductivity distribution due to the proppants in the hydraulic fractures. CO2 huff-n-puff technique using numerical reservoir simulation is used to determine the well performance and recovery factor arising from reservoir fluid viscosity reduction and gas expansion. Effect of fluid thermodynamics to recovery systems in the low permeability reservoir medium is fully captured in approach. Equation of state prepared for simulating the CO2 impact on the oil is prepared with correlating the collected down hole oil sample.
Numerical reservoir simulation study coupled with the complex fracture simulation model presents the insights of new means to improve RF in LUR through the injection of CO2. Such EOR method would be critical to increase the long term economic benefits. The study demonstrates that the infill well requirements can be mitigated if the EOR method of Huff-n-puff is utilized in cyclic modes over various time periods of production. Up to 9% extra RF was observed when CO2 Huff-n-puff technique was used as compared to production dependent only on hydraulic fracture stimulation. Parametric sensitivity on job sizes and start timing of EOR in a producing well is used to evaluate the RF. However, the hydraulic fracture geometry and the created footprint along with the time of injection has a larger effect in improving the EOR effectiveness.
The methodology provides the demonstration of simulating the EOR methods in unconventional reservoirs for economic assessment. The workflow demonstrates modeling CO2 flooding as an EOR technique on the full wellbore level with complex hydraulic fracture geometry. The approach demonstrated here can be applied to other basins in the unconventional formations to improve the recovery factor.
Importance of Accurate Reservoir Fluid Characterization in Unconventional Offshore Resources and How Asphaltene Behavior Impacts Reserve Prediction
Authors: Seibold Patricia , Krueckert Karsten Karl 
Published: October 2018

Abstract
Reservoir fluids are a complex hydrocarbon system that passes unique compositional stages when pressure and temperature change. Proper collection and accurate evaluation of a representative reservoir fluid sample during the exploration phase is one of the first crucial steps describing the chemical and physical nature of the hydrocarbon mixture. Understanding the importance of having a proper fluid characterization from the beginning of the development stage gets particularly essential in context of asphaltene precipitation and potential damage in unconventional reservoirs. Even in conventional reservoirs, formation damage caused by asphaltene deposition can have a severe impact on oil production and the prediction of remaining recoverable hydrocarbons in place. Multiple fraccing of unconventional tight oil reservoirs, conducted to produce economically despite low permeabilities, enhances the effect of uncertainty in reserve estimation. Precipitated asphaltenes potentially pjlug small pore throat channels in the near wellbore zone whereas high permeable fractures connect a wide area deep into the reservoir. Possibilities to maintain the reservoir pressure, e.g. water injection, are often limited due to the low permeability, consequently making it hardly manageable to stay above the asphaltene onset pressure in tight oil reservoirs.
Having a firm understanding of the reservoir fluid and the asphaltene properties helps to reduce unexpected occurrences during production and later field life as well as predicting remaining recoverable reserves in place.
This paper describes the fluid characterization of unconventional resources in a complex offshore environment and the effort undertaken to get a proper understanding about the hydrocarbon fluid phase. Challenging interpretations of conducted experiments about the asphaltene nature have been intensively studied to support forthcoming decisions in the field development process. Furthermore, the outcome of those analyses has led to a detailed investigation about the impact of asphaltene behavior in tight oil reservoir formation and the impact in prediction of remaining recoverable hydrocarbons.
Reducing Drilling Risks in Highly Over-Pressurized Quintuco-Vaca Muerta Formation, a Case History in Neuquén Basin /Argentina
Authors: Frydman Marcelo , Acevedo Andres , Castellanos Jose Miguel , Casanova Ocdomar , Hasbani Jose , Gutierrez Oscar , Giroto Gaspar 
Published: October 2018

Abstract
Different oil operators have faced technical and economic challenges while drilling in Neuquén basin. Drilling in a tectonic active setting creates problems ranging from influxes and stuck pipe incidents to circulation losses. The presence of natural fractures with an abnormally high pore pressure environment in Quintuco formation increases the gas kicks risks during drilling. Drilling nearby wells has evidenced many severe events, like many days to control a hydrocarbon influx with simultaneous losses. Stuck pipe is the responsible for lost BHAs and considerable NPT spent on freeing the pipe, performing additional wiper trips and hole cleaning. Minimizing non-productive time associated with wellbore instability reduces the risk of dangerous accidents at the wellbore site and it is required to complete the well on time and within the budget. This article describes a methodology to reduce drilling risks, in complex pore pressure conditions at Quintuco formation in Neuquén Basin. The proposed method is based on two main assumptions: the 3D pore pressure characterization based on elastic wave velocities on two different levels in Quintuco formation; and the intensity of the influx events is characterized by the presence of fracture corridors. The value added by the integrated team's efforts was demonstrated by drilling the next two wells with significant reductions in costs and nonproductive time.