bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigation of Vertical Fracture Complexity Induced Stress Interference in Multilayer Shale Gas Reservoirs with Complex Natural Fractures
Authors: Pei Yanli , Yu Wei , Sepehrnoori Kamy 
Published: October 2020

Abstract
The depletion of producing layers leads to significant stress changes in adjacent targets, especially when complex natural fractures are present. Due to weak bedding interfaces or small stress barriers, hydraulic fractures can easily penetrate neighboring layers, and this further increases the chance of multilayer stress disturbance. In this work, we investigate the effects of vertical fracture complexity, i.e., hydraulic fracture penetration and interlayer natural fracture existence, on stress interference between different layers using a data set from a typical shale gas well in the Sichuan Basin. Two geological contexts, i.e., without interlayer natural fractures (w/o INF) and with interlayer natural fractures (w/ INF), are considered under different degrees of fracture penetration and interlayer connectivity. An in-house iteratively coupled geomechanics and compositional reservoir simulator is used to model the three-dimensional pressure and stress changes. The non-uniform hydraulic fractures and stochastic natural fractures are incorporated in our coupled simulation with an embedded discrete fracture model (EDFM). Comprehensive spatial-temporal stress analysis quantifies the approximate range of orientation change of SHmax and magnitude change of Shmin under various reservoir conditions. Numerical results indicate that the presence of natural fractures in the interlayer upgrades the risk of stress interference between different pay zones. A larger hydraulic fracture penetration increases gas production, but also exerts a significant impact on stress reorientation and redistribution in the upper potential layer. The orientation change of SHmax along the prospective infill location is below 10 degrees in the w/o INF cases but up to 30 degrees in the w/ INF cases with a moderate number of interlayer natural fractures. The average magnitude change of Shmin is within 3.5 MPa along the prospective infill location for most w/o INF cases, whereas that in the w/ INF cases is above 10 MPa at most times. Moreover, the existence of natural fractures in the interlayer brings forward the occurrence of maximum orientation change in the upper layer by around one year. While inducing non-negligible stress drop in the upper layer, higher interlayer matrix permeability does not significantly reorient the horizontal principal stresses. Varying the density of interlayer natural fractures not only affects the stress magnitude but also causes considerable orientation change in the upper layer. The findings from this work help understand the extent of stress interference in the upper potential layer of the Sichuan Basin under different vertical fracture complexities. It is of guiding significance for future hydraulic fracture design and child-well operations in similar highly fractured tight formations.
Making Sense Out of a Complicated Parent/Child Well Dataset: A Bakken Case Study
Authors: Fowler Garrett , McClure Mark , Cipolla Craig 
Published: October 2020

Abstract
We use a high-quality dataset in the Bakken Shale to calibrate a numerical model to a complex and diverse set of parent/child observations. Two vertical wells (V1 and V2) were drilled 1000 ft and 1200 ft away from a legacy well with 10 years of production, H1. A DFIT was performed in the V1, followed by a 24 hour low-rate injection in the H1 (a microseismic depletion delineation, MDD, test). Subsequently, a small frac job was performed in the V1, followed by DFITs in the V1 and V2. The dataset yields a diversity of data to calibrate a numerical model: historical production of the H1, pressure response in the H1 from the MDD injection and the V1 fracture treatment, production rate uplift in the H1 following the V1 frac, microseismic, and pressure response during the three DFITs. The entire dataset was history matched in a single continuous simulation with a numerical simulator that fully integrates hydraulic fracture and reservoir simulation. The simulation was set up to closely match a geologic model that was built in prior work. The integrated simulation allows simulation of the fractures reopening around the H1 as a consequence of the MDD, the transport of proppant from the V1 to the H1 well, and the subsequent communication and poroelastic stress response. The Biot coefficient was calibrated to match the observed change in stress at the H1 well after ten years of depletion. The fracture toughness was calibrated to match the observed fracture geometry from the microseismic around the V1 well during fracturing. A proppant transport parameter called ‘maximum immobilized proppant’ was tuned to the production and DFIT data. The match to the V2 DFIT suggests that it is not directly in contact with the V1 fracture, even though the wells are relatively close together along fracture strike. The initial V1 DFIT suggests that it has, at most, weak contact with the H1. The second V1 DFIT, performed after the fracturing treatment, demonstrates communication with the H1, and consequently, depletion. The observations demonstrate that the H1 was able to produce from the previously undepleted rock around the V1, even though it was 1000 ft away. Overall, the results indicate that Bakken wells can achieve substantial (at least 1000 ft) effective half-length, that frac hits on parent wells in the Bakken do not necessarily result in production degradation and can even increase production, that the apparent Biot coefficient is relatively low (∼0.34), that the amount of proppant trapping due to localized screenout is relatively low (but nonzero), and this entire, complex dataset can be explained using a planar fracture modeling approach.
Multivariate Time Series Modelling Approach for Production Forecasting in Unconventional Resources
Authors: Alimohammadi Hamzeh , Rahmanifard Hamid , Chen Nancy 
Published: October 2020

Abstract
Evaluating the potential of the unconventional resources is a key for the development of this type of reservoirs. The currently adopted models for the well production forecast including decline curve analysis often fail to capture the complexity of flow performance by over-simplifying it and cannot produce reliable results due to the operational problems and most importantly the inadequate production history. In this study, a deep learning approach is developed to predict the long-term well performance based on a moderate duration of production data.
A data-driven procedure was implemented based on deep neural networks for flowrate predication using multivariate inputs. The production forecast was formulated as a time series regression problem where multiple inputs including tubing-head pressure and bottom-hole temperature are used as the input of a reverse model that estimates flow rate. Different recurrent neural networks (RNNs) including Long Short Term Memory, Gated Recurrent Units, and Bidirectional Recurrent Neural Networks were tested in this study to select the most time-efficient and accurate model of production forecasting.
The method presented in this paper provided a time efficient process which learned multi-domain sequence and was used to forecast production in unconventional resources. The developed deep learning networks did not require any feature handcrafting and could learn directly form the raw data. Reconstructed and predicted flowrates using deep learning was also used to estimate missing flowrate history. The study showed that deep neural networks have great capability to tolerate noise and optimize computation when multivariate input is used.
The technique can also be applied to other type of forecasting problems of prediction of pressure and rate in conventional reservoirs, prediction rate from temperature, and multi-well production forecasting.
Water Shutoff and Zonal Isolation for High Permeability Depleted Reservoir Using Organically Crosslinked Polymer Sealant System
Authors: Al-Azmi Nasser , Al-Sabea Salem , Abdullah Abu-Eida , Patra Milan , Khandelwal Nakul , Gaur Rishika , Chawla Sapna 
Published: October 2020

Abstract
Increasing water cut in oil-producing zones is a common issue, particularly in mature fields. Currently, most decisions are governed by economics, and incurring additional expenses, such as handling produced water, is undesirable. Depending upon the source of the water production, chemical isolation provides one effective solution to this issue.
This paper describes a cost-effective coiled tubing (CT) intervention to implement permanent zonal isolation for water shutoff using an organically crosslinked polymer (OCP) sealant system and a modified organically crosslinked polymer (m-OCP) sealant system to provide a controlled, shallow penetration solution to the problem in a high-permeability, low-pressure reservoir.
The traditional water shutoff method uses rig intervention for cement squeezes, which targeting shallow penetration can be time consuming and expensive in a high-permeability, low-pressure reservoir.
The OCP sealant system is an organically crosslinked polymer that is thermally activated to effectively seal the targeted interval. The m-OCP sealant system combines particulates with the OCP sealant system to provide leakoff control to help promote shallow matrix penetration.
The production logging tool (PLT) data for the candidate well indicated that the maximum water cut originated from the lower perforations and a single zone. CT intervention was selected to accurately place the OCP and m-OCP sealant systems and to permanently block water production by creating polymer barriers inside the reservoir and to remove any remaining OCP/m-OCP from the wellbore.
OCP and m-OCP are resistant to acid and H2S and provide the required radial penetration. This system provides a predictable and controlled set time (as shown by laboratory testing). Because this system does not develop compressive strength, a simplified cleanout with a jetting nozzle is required to wash it from the well.
After completing the zonal isolation with the OCP sealant system, the pressure test for the zone indicated a good seal. An electric submersible pump (ESP) was run on the completion string, and initial test results showed that the water cut was reduced from 97 to 75%, and oil production increased from 175 to 300 bpd. Increased production will recover all intervention and chemical costs within 20 days.
The polymer sealant system with the customized intervention solution successfully reduced the water cut for this west Kuwait field. The same approach can be applied to other similar fields worldwide.
Data Science Applied to Pedagogical Methodologies Focused on Changing the Negative Perception of the Oil and Gas Industry in Colombia
Authors: Guevara Israel , Ardila David , Daza Kevin , Ovalle Oscar , Pastor Paola , Ramirez Leyla 
Published: October 2020

Abstract
In Colombia, one of the biggest challenges for the oil and gas industry is to generate a sound reputation and a new perception about its benefits to the communities located in the area of influence. Even though, the oil and gas industry generates between 9 to 11% of the Gross Domestic Product (GDP) in Colombia, there is a negative perception of local communities due to the impacts of the operations of the industry on the people and environment; as a consequence, the implementation of pedagogical methodologies to educate communities about the sustainable view of the modern Oil and gas Industry, and the importance to the access to energy and water is a need.
In this sense, programs such as Energy4Me and PetrolCopa Reto Escolar have been implemented over the last two years in different regions of Colombia, which have allowed the collection of a considerable amount of data with great technical and social value from more than 10000 participants. This information has been refined, processed and analyzed to show how data science generates added value in the continuous improvement of the methodologies implemented by the data center of SPE Colombian Section; thus, improving relationship between industry and local communities through a fluent communication and knowledge channel.
The analysis of the information and its implementation in these educational programs was carried out through the application of different statistical methods and digital tools for processing and monitoring information, which resulted in the design of optimal processes for the collection of structured and unstructured data such as; community behavior parameters, social problems, demographic characteristics and acquired technical knowledge. This process took into account at the same time other related variables such as the heterogeneity of rural communities, logistical and operational challenges and the social conditions of each region. The data gathering process involved 500 volunteers in more than 5000 people from different regions, ethnic groups, ages, gender and level of education. Once the information was correlated and the methodological approach of the programs improved, trends and direct relationships were established between the data analyzed and the decrease in the rate of rejection by the communities towards Oil and Gas industry in the study regions.
Smart Custom Well Design Based On Automated Offset Well Analysis
Authors: Selveindran Anand , Wesley Avinash , Chaudhari Nitish , Pirela Helmut 
Published: October 2020

Abstract
Offset well analysis is the process of investigating and integrating historical drilling performance from neighboring wells into prospect well design. Traditional offset analysis is a time and resource intensive process that requires a lot of manual input and analysis to make various design decisions. Our proposed workflow automates much of this analysis, while allowing the user to customize designs based on operating metrics resulting in a quicker and more comprehensive offset well analysis that provides the user with intelligent offset recommendations and a base design for the prospect well. Historical data is queried from a structured engineering and operation database comprising of data ranging from subsurface geology, drilling to production and end-of-well. We gather this historical data from nearby wells and learn from those in order to produce a first pass design for the prospect well to begin with. With this data, our proposed workflow implements algorithms to identify representative offset wells with similar geology, trajectory and other characteristics. A similarity analysis based on various geological sequences across the wells is conducted by a deep neural network algorithm, which is trained to analyze sequential patterns within. Trajectory similarity is performed using well surveys (dogleg severity, inclination, and azimuth). A recurrent neural network is employed to learn the well survey patterns and classify wells with similar trajectories. Finally, drilling performance metrics are used to rank the offsets and aid selection of the best offset design to be used as a base template for the prospect well. The proposed workflow significantly reduces analysis time; the software analysis time is less than five minutes. The user can almost instantaneously query the database and obtain wells that are similar in terms of trajectory and geology, and rank those wells on certain pre-defined metrics. The engineer is also able to view key events and hazards history for the offset wells. This provides the engineer with a compilation of hazards and risks by depth and cause, allowing the engineer to focus on mitigating risks and designing better and safer wells. The engineer can accept the top ranked offset and automatically select casing design based on default metrics of cost, time, and NPT, or can implement other metrics and create a composite casing design from different hole-sections from different offsets.
Fracture Wing Growth Study Using Synchronized Surface Pressure Data from Monitored Offsetting Wells
Authors: Rainbolt Michael , Cooper Drew , Timmons Taylor 
Published: October 2020

Abstract
Extensive literature has been published concerning Fracture Driven Interactions (FDIs). Many of these works describe FDI anatomy, physics and impact on existing wells including the success or failure of various mitigation techniques. In this paper, time synchronized FDI surface pressure data from existing offsetting wells is used to study fracture wing growth. This includes timing, fracture half-length estimation and observing the movement of injected fluid sequentially from well-to-well during fracturing operations.
In 2019, an in-fill Eagle Ford well development consisting of two newly drilled wells and seven offsetting existing wells was performed. The new wells were located such that each treatment well was bounded on both sides by existing wells. Further, there were first order wells (closest well to treatment well) and second order wells (next well over from the first order well) bounding one of the treatment wells and FDIs generated pressure communication were seen in both the first order well and the second order well. Six of the existing wells were preloaded. This was done to test the efficacy of preloading to protect the existing wells from FDI damage.
The workflow was organized into first deriving detailed data from all FDIs that occurred in individually monitored wells. This was followed by examining well pairs bounding the two treatment wells to study fracture wing development in each stage. Lastly, first order and second order wells that had sequential FDIs from the treatment wells were examined to study fluid volumes and timing between wells as well as FDI magnitude dampening in second order wells. All monitored wells were left shut-in during the completion operations. The wireless surface pressure monitoring sensors were time-synchronized to internet time and the data was viewed in real-time.
The authors’ found that preloading dampened FDIs but did not completely stop them. The degree of the success of preloading was graded by determining a reduction of recovery time (if any) and how well production rates were protected. At the time of this writing, flowback operations are ongoing and one primary well recovered to pre-frac rates within one week. We anticipate a corresponding reduction of recovery time in the other wells.
This paper presents methods and processes that offer a solution to identify candidate stages for FDI mitigation and potential optimization of project economics. The time synchronization with internet time eliminated all uncertainty with regards to timing. As will be shown, for this type of study, there cannot be uncertainty with timing. No inconsistencies in timing were found. It was also determined that FDI data must be viewable in real-time for it to be used to make on-the-fly mitigation decisions. In this project, a "passive well defense" technique was utilized; preload but take no other actions.
Effect of Surface Tension on Sweeping Performance of Injected Gas During Intermittent Gas Lift in Liquid Loaded Horizontal Wells
Authors: Croce Daniel D. , Zerpa Luis E. 
Published: October 2020

Abstract
As the reservoir pressure drops in the vicinities of horizontal gas wells drilled in tight reservoirs, the produced gas loses its ability to drag liquids to surface. This results in the accumulation of liquid in the bottom of the well. Since conventional artificial lift methods fail to remove the stagnant liquid in an efficient and reliable manner, the accumulated liquid limits the well production down to unprofitable levels. As an alternative solution to this problem, it is proposed a method called Backsweep, which relies on the use of intermittent gas injection in the horizontal section of the well. Results obtained in an experimental flow loop, using water and compressed air, show an improvement on the liquid removal efficiency (i.e., produced liquid volume / stagnant liquid volume) at Eotvos (Eo) numbers around 12, obtained by reducing the internal diameter (ID) of the flowlines, but with increased frictional pressure drops per unit length. This work focuses on the effect of changing the surface tension and viscosity of the stagnant liquid, to optimize the liquid removal efficiency, avoiding increases in frictional pressure drop from reducing the ID of the line. Sucrose, xanthan gum and sodium chloride at different concentrations, were used for this purpose. Xanthan gum at a concentration of 0.05% w/w delivered the best results of the three substances, with an increase of over 15% (up to 77% in average) when compared to only using water, as the Eo number was reduced in 5% and the viscosity number (Nvis) was increased in over 70 times. The improvement on the liquid removal efficiency of the device at lower Eo is associated to a shaper nose of the Taylor bubble and larger convergence angle of the flow lines in the liquid film next to the wall.
Unconventional Measurements Bootstrap Reservoir Simulation
Authors: VonGonten W. D. , Woods Terry , Yang Yi-Kun , Picha Tim , Lindsay Garrett , Ali Safdar 
Published: October 2020

Abstract
Production history matching data is an important step in any study that seeks to optimize unconventional completions and well development criteria. Understanding the reservoir mechanisms during production allows for better optimization of the hydraulic fracture system. Generating a model that fits historical data can be easy but honoring the true petrophysics and fluid dynamics of the reservoir is often challenging. Some of the major challenges during reservoir simulation are uncertainties in water saturation, permeability, phase behavior, and effective fracture surface area during production. This paper discusses how fit-for-purpose core measurements help reduce the uncertainty in these parameters, ultimately requiring a multiple porosity reservoir simulation model to account for these improved measurements and understandings.
Industry accepted core analysis techniques under-estimate reservoir water saturation due to loss of water from evaporation and core handling techniques (preservation, crushing, time). Proper evaluation of the void space will be shown and how this is better calibrated to field data. A review of how steady-state liquid permeability testing provides better estimates for reservoir permeability and deliverability in shale reservoirs will be discussed. Coupling these measurements with imbibition effects from hydraulic fracturing fluids and lab studies showing oil-wet and water-wet pore systems acting independently of each other, a slightly "outside of the box" reservoir simulation model was needed to mimic these physics.
The proposed reservoir simulation methodology consists of multiple porosities and was developed to incorporate near-wellbore hydraulic fracture effects that are observed during lab testing. Combining this methodology with other lab measurements and a fully three-dimensional (3D) hydraulic fracture model, the number of "knobs" that need to be turned to get a good history match are reduced.
Two examples will be presented in this paper showing how the proposed model better honors the physics of lab measurements and provides the user more flexibility during reservoir simulation, especially when buildup data is available. Reducing the uncertainty in these parameters has provided a workflow that helps minimize the multiple non-unique realizations during the history match process and provides a more reliable model for the engineer while reducing the amount of time needed to obtain a match.