bluuebunny/crossref_metadata_2025_split huggingface dataset:
Are We Over-Stimulating Our Laterals? Evaluating Completion Design Practices Based on Field Offset Well Pressure Measurements
Authors: Seth Puneet , Elliott Brendan , Ingle Trevor , Kumar Ashish , Zheng Shuang , Sharma Mukul 
Published: October 2020

Abstract
In recent years, hydraulic fracturing design has evolved significantly. Fluid volumes injected in a lateral have more than doubled to ~ 250,000 bbl/well (Weijers et al., 2019). Increased injection volumes coupled with a sub-optimal completion design can lead to over-stimulation at current well spacing densities. In many instances, dominant clusters that take a majority of the injected fluid during child well treatment intersect offset parent wells. This results in sub-optimal reservoir drainage, highly inefficient fluid and sand placement and negatively impacts the overall well productivity due to well interference. In this work, we analyze offset well pressure measurements in the Permian Basin to evaluate if a frac job is overstimulated. Additionally, we perform numerical modeling studies to evaluate the extent of overstimulation in different stimulation scenarios and provide recommendations to maximize the capital efficiency of a frac job.
We analyze the pressure response in offset parent wells in the Permian Basin during treatment of a nearby well. Fracture arrival times (time taken for the child well fractures to intersect with a nearby parent well) are investigated for multiple stages during child well stimulation. This information from field data is coupled with fracture modeling simulations to evaluate if a frac-job is over-stimulated. Stages that suggest over-stimulation are systematically analyzed and dynamic plots are presented, that compare the capital efficiency at different times during a frac job.
Optimal completion designs that achieve uniform distribution of injected fluid volumes into multiple clusters are key to successful fracturing jobs. Simulations as well as field data show that if a large job volume is pumped with a sub-optimal completion design, fracture arrival at the offset well is early, leading to over-stimulation and wasted capital. In such a scenario, dominant clusters that take most of the injected fluid can intersect nearby offset well early in the treatment, while significantly bypassing undepleted reservoir rock along the lateral (that should ideally be drained) due to low cluster efficiency. This results in a frac job with poor capital efficiency and a well with lower productivity (due to interference with offset well). We show that early fracture arrival times are indicative of fewer clusters propagating fractures with very non-uniform fluid distribution (low cluster efficiency), whereas late arrival times indicate more uniform fluid distribution in the clusters with high cluster efficiency.
We introduce a novel technique that analyzes field offset well pressure data and fracture arrival times at the offset well to diagnose stimulation efficiency and prevent over-stimulation. Our method provides operators with a relatively inexpensive way to improve capital efficiency during a frac-job.
Leveraging Fractured Well Performance With Economics Modeling to Increase Expected Value: A Tool For Strategic Decisions
Authors: Garza Omar , McLeroy Priscilla 
Published: October 2020

Abstract
In recent years, well performance from tight reservoirs in the Delaware Basin has been improving due to enhanced completion practices, better reservoir targeting and improved well designs in the region. One of the key components to the enhanced completion practices has been the implementation of progressively longer laterals. The rate of increase in lateral lengths have slightly slowed in recent years, as operators approach the point of no additional value creation as the well costs supersede the production gained from longer wells. This paper presents a tool created to evaluate the performance and economics of a given well given different reservoir, fluid, well design and completion parameters. The tool is also a probabilistic model that can quantify the impact of input parameters that the user feels uncertain about. As a result, it can provide management teams with an approach to make capital decisions under uncertainty. The proposed methodology presented in this paper is repeatable for different tight rock formations across different basins. An example of the tool's capability is demonstrated in this paper using an asset profile typical of the Delaware Basin's Wolfcamp A.
Quality Control of NMR Measurements in Unconventional Rocks Using Hilbert Transforms and Semi-Logarithmic Derivatives
Authors: Aérens Pierre , Medellin David , Torres-Verdín Carlos 
Published: October 2020

Abstract
Nuclear magnetic resonance (NMR) measurements are extremely valuable in the assessment of fluid-flow properties of rocks. However, inverted transverse-relaxation time (T2) distributions are often biased by positivity constraints and the regularization method. In some cases, it is difficult to determine whether the estimated pore-size distributions are correct or by-products of the inversion. On-site quality-control of inversion results is thus essential to avoid erroneous analyses based on non-physical results across unconventional rocks.
We introduce and compare two quality-control approaches based on two different signal processing practices: the semi-logarithmic derivative and the Hilbert transform. Validation of the inverted T2 distribution is performed by applying either processing method to the echo train decay of proton magnetization to estimate a pseudo-T2 distribution that is not affected by inversion artifacts. These two methods are data-driven processes for on-site, continuous quality control of borehole NMR measurements. In the first method, a pseudo-T2 distribution is constructed by taking the derivative of the echo train decay with respect to the natural logarithm of the relaxation time. For the second method, the Hilbert transform is applied to the raw proton magnetization decay to approximate the T2 distribution.
NMR laboratory measurements were performed on a wide variety of rocks, the associated T2 distributions were estimated using linear inversion and the two quality-control methods were applied to the same data. The reliability of our quality-control procedures was verified by benchmarking them against the inverted T2 distributions. Furthermore, these quality-control methods, when applied continuously to borehole NMR measurements, enable the optimization of the measurements in real-time to mitigate biased noise. By verifying the location of the dominant mode of the T2 distribution, the NMR operator can determine whether more stacking of proton magnetization decays is needed to attain a high-quality estimation of the pore-size distribution before performing the T2 inversion.
Our work provides the basis of effective quality-control methods for NMR measurements for the petrophysical interpretation of rocks with complex pore-size distributions, especially in unconventional rocks, where noise present in the measurements, especially at early acquisition times, can completely mask the useful signal originating from pore-size distributions and fluids. The fast and reliable quality control of estimated T2 distributions is not affected by inversion artifacts, relying only on unfiltered, raw data.
Microfluidic and Numerical Investigation of Trapped Oil Mobilization with Hydrophilic Magnetic Nanoparticles
Authors: Wang Ningyu , Liu Yifei , Cha Luming , Prodanovic Maša , Balhoff Matthew 
Published: October 2020

Abstract
Nanoparticles have great potential to mobilize trapped oil in reservoirs by reducing the oil-water interfacial tension, altering the rock wettability, stabilizing foams and emulsions, and heating the reservoir to decrease the oil viscosity. However, the direct application of magnetic forces on paramagnetic nanoparticles in reservoir engineering applications has not be extensively investigated. We demonstrate the enhanced oil recovery (EOR) potential of hydrophilic magnetic nanoparticles in oil production by direct observation using microfluidics.
We studied the mobilization of oil blobs by a ferrofluid (a suspension of hydrophilic magnetic nanoparticles in water) in a converging-diverging channel with varying depth (so-called 2.5D micromodel). The channel had a varying depth of 10-30 microns and a varying width of 50-200 microns, approximating a flow path in the rock. The nanoparticle suspension was injected at 0.1 microliter/hour. The channel was made of glass and thus the water-based ferrofluid was the wetting fluid.
Initial ferrofluid flooding experiments were performed under a static magnetic field. This magnetic field caused oil droplet deformation, dynamic break-up into smaller droplets, and subsequent residual oil saturation reduction. Significant oil blob displacement was observed within 2 hours after the magnetic field was applied. During the flooding, the oil saturation within the observation area of the micromodel reduced from 27.4% to 12.0%. We then hypothesized that a changing field would have an even larger effect in saturation reduction. We have thus designed experiments with a magnetic field of the same magnitude slowly rotating under the micromodel. We subsequently observed a completely different phenomenon, namely self-assembly of oil droplets, indicating formation of the hydrophilic magnetic nanoparticles microstructures (chains under the magnetic field). These magnetic nanoparticle microstructures were ever-changing under the rotating magnetic field. While the ability of ferrofluid to rotate small blobs was in itself interesting, in experiments without actual flooding (and thus synergy of hydrodynamic and magnetic forces) we did not observe any additional oil recovery.
Preventing the Next Big Well Control Event – A Leading Indicators Approach
Authors: Tamim Nafiz , Karlsen Geir , van Loopik Geert , Pettigrew James 
Published: October 2020

Abstract
The Oil and Gas industry has historically relied on lagging indicators (e.g., number of spill events, volume of spill, number of well kicks, personal safety statistics) for measuring and monitoring safety performance. Even though these metrics provide some useful information on an organization's safety culture, they do not offer any predictive insights.
Leading indicators are metrics for measuring and monitoring events that can lead to or contribute towards an incident. Well control incidents are low frequency-high consequence events. Carefully developed and tracked leading indicators can provide valuable information for preventing significant control events.
Currently, a collaborative project is underway to engage the upstream oil and gas industry to develop leading indicators-based dashboard tools for predicting and thereby preventing well control incidents. The goal of this project is to develop a set of leading indicators-driven predictive tools with customizable dashboard displays, for multiple levels of decision makers, to constantly monitor and understand well operations risk from a process safety standpoint.
This tool would provide the users (from frontline to management) with role-specific information from status of engineering barriers (e.g., hydrostatic head, BOP status and health) to organizational process safety elements (e.g., procedure, compliance, design, risk management). The ‘processed’ information presented in a dashboard setting can be considered as early warning signs of well control events, which should drive targeted corrective actions to minimize risks in well operations. The project has already identified significant work in this area both from academic and industrial sectors, which will help to build the foundation for moving forward towards building a robust and useful Leading Indicators Dashboard.
Robust Chemical Flood Design for Maximum Recovery Using Updated Fluid Property Models
Authors: Khodaparast Pooya , Johns Russell T. 
Published: October 2020

Abstract
State-of-the-art chemical flooding simulators typically use nonpredictive phase behavior and property models to design a surfactant flood. For example, a variation of the black-oil model is often used to represent phase behavior in several commercial simulators. We examine the available methods including more recent physics-based models such as the HLD-NAC equation-of-state and their effects on overall recovery, front speeds, and breakthrough times. We implement the HLD-NAC EoS model in UTCHEM to examine the impact of changing salinity and other variables on the phase behavior and the recovery process. A novel predictive viscosity model is also implemented for the first time in UTCHEM to give a more accurate prediction of viscosity. We isolate the impact of salinity and other gradients on recovery in a one-dimensional homogeneous reservoir.
Results show that the composition path can enter the Winsor II+ region for certain changes in variable gradients. When the two-phase region is entered, the trailing injected fluid surpasses the chemical slug and contacts the oil bank directly. The microemulsion phase saturation is then decreased to immobile values so that surfactant is now immobile and oil recovery is significantly decreased. We further show that the presence of polymer - both in the buffer and the chemical slug - has little effect on the appearance of the arrested microemulsion and oil bank. Polymer does partially offset the negative effects by providing conformance control immediately after the microemulsion phase is trapped. The salinity gradient should be designed so that the composition path avoids the II+ lobe in its entirety, giving a robust and mobile slug with or without polymer. We propose a limit in injection salinity under which the II+ lobe can be avoided. We also show that the less accurate viscosity model overestimates recovery in a two-dimensional simulation of the chemical flood.
Considerations and New Approaches for Talent Development of Gen-Z in Oil and Gas
Authors: Capello Maria Angela , Al-Khashti Bashar 
Published: October 2020

Abstract
New generations face learning in different ways, but managerial styles prevail for decades, creating a gap that greatly affects talent development effectiveness. This creates, more than a gap, a risk, especially for ensuring the outcome of the training of individuals of Generation Z in the oil and gas industry, where safety in front of hazards needs to prevail, and where production optimization is a leading goal for the very sustainability of the industry.
This paper focuses on establishing the main differences in the learning style of the so-called Gen-Z or Genzers (Generation Z), and why fixing the tools, systems, approaches and even settings of their training is vital to ensure the development of skills and leadership trajectories, which will necessarily, ground their professional careers and their corporate success.
The urgency of implementing step-changes in the approach that Human Resources and Training departments take for developing Gen-Z is peremptory, most particularly for the change of style in mentoring, recognition and supervisory styles that will have to be used by their leaders.
Edge Computing: Continuous Surveillance and Management of Production Operations in a Cost Effective Manner
Authors: Sharma Abhishek , Samuel Prince , Gey Gian-Marcio , Kumar Sujit 
Published: October 2020

Abstract
E&P operators are aggressively looking to increase production with operational efficiency gains. Proactive well and field production management requires digital enablement of operations, with no data silos and data flowing seamlessly from the subsurface to the hands of the operator. With huge amounts of data being collected, it is imperative to apply data-driven techniques to gain more insights that can be utilized to better manage production. A data-driven approach can provide huge benefits for organisations holding vast amount of reservoir, production, and facilities data. It could provide insights into non-linear multidimensional relationships between parameters so that the field development is better understood and optimized. It could allow companies using a proactive approach towards field operations and equipment maintenance resulting in additional cost savings.
This paper presents various case studies where operators improved operational efficiency and optimize production utilizing edge-driven Industrial Internet of Things (IIoT) solutions. These edge IIoT solutions enable fast-loop control through a combination of physics and data-driven workflows, which empowers the operator to proactively manage their assets and focus attention on potentially problematic wells. The solution's architectural setup and ability to deliver fast-loop control workflows at the edge enables operators to successfully detect and manage potential issues such as artificial lift pumps, ultimately improving the performance. Additionally, this approach reduces the dependency upon domain experts to frequently analyze data. The high-frequency data capturing resulted in predicting equipment performance with confidence and allowing remote well management to reduce health, safety and environment (HSE) risks while decreasing logistics and maintenance costs.
Machine Learning Method to Determine Salt Structures from Gravity Data
Authors: Chen Jie , Schiek-Stewart Cara , Lu Ligang , Witte Susanne , Eres Guardia Karin , Menapace Francesco , Devarakota Pandu , Sidahmed Mohamed 
Published: October 2020

Abstract
In this paper, we developed an innovative machine learning (ML) method to determine salt structures directly from gravity data. Based on a U-net deep neural network, the method maps the gravity downward continuation volume directly to a salt body mask volume, which is easily interpretable for an exploration geophyisicist. We also studied the feasibility to apply the method to different gravity field data. We conclude that the ML based method from gravity data complements seismic data processing and interpretation for subsurface exploration. For the region where no or limited seismic data are available, this ML based salt identification can save iterative efforts (&gt;50%) in the conventional gravity inversion process and identify major salt bodies in the region.
Water Isolation and Sand Control: Breaking Barriers with Expandable Steel Patch Technology
Authors: Guerrero Ximena , Medina Daniel Ricardo , Munoz Alberto , Rubiano Jhon , Bejarano Alied , Trujillo Hernando , Saltel Nicolas , Trillos Julian , Becerra Jerson , Castellanos Diego , Coronado Cesar 
Published: October 2020

Abstract
This paper describes the design, planning, and successful installation of a fit-for-purpose casing patch to isolate a water producing zone, the subsequent perforation of an adjacent zone, and a gravel pack completion in the same well for the first time worldwide. The proximity of the zones and the sand control requirements made the design and planning of this job a challenging task that is detailed in this manuscript.
The main producing zone in the SW-21 well watered out after few years of production. A second target was identified located just four feet below the main zone. To extend the life of the well and to add reserves from the secondary target, the upper 100% water zone had to be isolated. A fit-for-purpose, thin wall casing patch solution was designed to: allow perforation of the secondary target while maintaining patch integrity, allowing for the installation of sand control screens; and resist following gravel pack completion, by keeping the minimum recommended clearance between casing and screens, inside the minimal patch-reduced diameter.
The re-completions program consisted of: 1. Successful recovery of existing gravel pack from the main producing zone and thorough wellbore cleanup. 2. Casing patch installation consisting of a 23-ft long patch to isolate the water-producing zone. In this case, a specific engineering design analysis was required to ensure that, because of the very close distances between zones, the patch would still maintain integrity during perforation of the secondary target and the resulting patch overlap. 3. Successful integrity test to confirm upper interval isolation before perforating the lower interval. 4. A precise perforating operation carried out to perforate the secondary zone. Based on engineering recommendations, some length of the installed patch was perforated to guarantee a minimum unperforated distance of casing patch between zones to guarantee patch sealing features. 5. Once perforation was successfully accomplished, a gravel pack completion—inside the casing patch reduced diameter—was executed along the new zone for sand control purposes, and the well was put into production.
This paper presents the different interactions between a multidisciplinary research and development team, and completions and reservoir engineers to come up with a full solution for water isolation and sand control under such challenging conditions. For the first time in the world, a casing patch was used to isolate a water zone, and at the same time, perform a gravel pack completion inside the patch reduced diameter. Well performance, without any mechanical issues, confirms the success of the provided solution.