bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Novel Coupled Approach to Investigate the Spatiotemporal Evolution of Fracturing-Induced Seismicity: Case Study
Authors: Hui Gang , Chen Shengnan , Gu Fei 
Published: April 2021

Abstract
The recent seismicity rate increase in Fox Creek is believed to be linked to the hydraulic fracturing operations near the region. However, the spatiotemporal evolution of hydraulic fracturing-induced seismicity is not well understood. Here, a coupled approach of geology, geomechanics, and hydrology is proposed to characterize the spatiotemporal evolution of hydraulic fracturing-induced seismicity. The seismogenic faults in the vicinity of stimulated wells are derived from the focal mechanisms of mainshock event and lineament features of induced events. In addition, the propagation of hydraulic fractures is simulated by using the PKN model, in combination with inferred fault, to characterize the possible well-fault hydrological communication. The original stress state of inferred fault is determined based on the geomechanics analysis. Based on the poroelasticity theory, the coupled flow-geomechanics simulation is finally conducted to quantitatively understand the fluid diffusion and poroelastic stress perturbation in response to hydraulic fracturing. A case study of a moment-magnitude-3.4 earthquake near Fox Creek is utilized to demonstrate the applicability of the coupled approach. It is shown that hydraulic fractures propagated along NE45° and connected with one North-south trending fault, causing the activation of fault and triggered the large magnitude event during fracturing operations. The barrier property of inferred fault under the strike-slip faulting regime constrains the nucleation position of induced seismicity within the injection layer. The combined changes of pore pressure and poroelastic stress caused the inferred fault to move towards the failure state and triggered the earthquake swarms. The associated spatiotemporal changes of Coulomb Failure Stress along the fault plane is well in line with the spatiotemporal pattern of induced seismicity in the studied case. Risks of seismic hazards could be reduced by decreasing fracturing job size during fracturing stimulations.
2000-2020: Two Decades of Evolution of Hydraulic Fracturing-Induced Seismicity in the Western Canada Sedimentary Basin
Authors: Rodríguez-Pradilla Germán , Eaton David , Popp Melanie 
Published: April 2021

Abstract
The goal of this work is to calibrate a regional predictive model for maximum magnitude of seismic activity associated with hydraulic-fracturing in low-permeability formations in the Western Canada Sedimentary Basin (WCSB). Hydraulic fracturing data (i.e. total injected volume, injection rate, and pressure) were compiled from more than 40,000 hydraulic-fractured wells in the WCSB. These wells were drilled into more than 100 different formations over a 20-year period (January 1st, 2000 and January 1st, 2020). The total injected volume per unit area was calculated utilizing an area of 0.2° in longitude by 0.1° in latitude (or approximately 13x11km, somewhat larger than a standard township of 6x6 miles). This volume was then used to correlate with reported seismicity in the same unit areas.
Collectively, within the 143 km2 area considered in this study, a correlation between the total injected volume and the maximum magnitude of seismic events was observed. Results are similar to the maximum-magnitude forecasting model proposed by A. McGarr (JGR, 2014) for seismic events induced by wastewater injection wells in central US. The McGarr method is also based on the total injected fluid per well (or per multiple nearby wells located in the same unit area). However, in some areas in the WCSB, lower injected fluid volumes than the McGarr model predicts were needed to induce seismic events of magnitude 3.0 or higher, although with a similar linear relation. The result of this work is the calculation of a calibration parameter for the McGarr model to better predict the magnitudes of seismic events associated with the injected volumes of hydraulic fracturing. This model can be used to predict induced seismicity in future unconventional hydraulic fracturing treatments and prevent large-magnitude seismic events from occurring.
The rich dataset available from the WCSB allowed us to carry out a robust analysis of the influence of critical parameters (such as the total injected fluid) in the maximum magnitude of seismic events associated with the hydraulic-fracturing stimulation of unconventional wells. This analysis could be replicated for any other sedimentary basin with unconventional wells by compiling similar stimulation and earthquake data as in this study.
A Data Analytics Framework for Analyzing the Effect of Frac Hits on Parent Well Production
Authors: Guo Yifei , Ashok Pradeepkumar , van Oort Eric , Patterson Ross , Zheng Dandan , Isbell Matthew , Riopelle Austin 
Published: April 2021

Abstract
Well interference, which is commonly referred to as frac hits, has become a significant factor affecting production in fractured horizontal shale wells with the increase in infill drilling in recent years. Today, there is still no clear understanding on how frac hits affect production. This paper aims to develop a process to automatically identify the different types of frac hits and to determine the effect of stage-to-well distance and frac hit intensity on long-term parent well production.
First, child well completions data and parent well pressure data are processed by a frac hit detection algorithm to automatically identify different frac hit intensities and duration within each stage. This algorithm classifies frac hits based on the magnitude of the differential pressure spikes. The frac stage to parent well distance is also calculated. Then, we compare the daily production trend before and after the frac hits to determine the severity of its influence on production. Finally, any evident correlations between the stage-to-well distance, frac hit intensity and production change are identified and investigated.
This work utilizes 3 datasets covering 22 horizontal wells in the Bakken Formation and 37 horizontal wells in the Eagle Ford Shale Formation. These sets included well trajectories, child well completions data, parent well pressure data and parent well production data. The frac hit detection algorithm developed can accurately detect frac hits in the available dataset with minimal false alerts. The data analysis results show that frac hit severity (production response) and intensity (pressure response) are not only affected by the distance between parent and child wells, but also affected by the directionality of the wells. Parent wells tend to experience more frac hits from the child frac stages with smaller direction angles and shorter stage-to-parent distances. Formation stress change with time is another factor that affects frac hit intensity. Depleted wells are more susceptible to frac hits even if they are further from the child wells. Also, we observe frac hits in parent wells due to a stimulation of a child well in a different shale formation.
This paper presents a novel automated frac hit detection algorithm to quickly identify different types of frac hits. This paper also presents a novel way of carrying out production analysis to determine whether frac hits in a well have positive or negative influence long-term production. Additionally, the paper introduces the concept of the stage-to-well distance as a more accurate metric for analyzing the influence of frac hits on production.
Multi-Well Pressure History Matching in Delaware Play Helps Optimizing Fracturing for Subsequent Pads
Authors: Suarez-Rivera Roberto , Panse Rohit , Sovizi Javad , Dontsov Egor , LaReau Heather , Suter Kirke , Blose Matthew , Hailu Thomas , Koontz Kyle 
Published: April 2021

Abstract
Predicting fracture behavior is important for well placement design and for optimizing multi-well development production. This requires the use of fracturing models that are calibrated to represent field measurements. However, because hydraulic fracture models include complex physics and uncertainties and have many variables defining these, the problem of calibrating modeling results with field responses is ill-posed. There are more model variables than can be changed than field observations to constrain these. It is always possible to find a calibrated model that reproduces the field data. However, the model is not unique and multiple matching solutions exist. The objective and scope of this work is to define a workflow for constraining these solutions and obtaining a more representative model for forecasting and optimization. We used field data from a multi-pad project in the Delaware play, with actual pump schedules, frac sequence, and time delays as used in the field, for all stages and all wells. We constructed a hydraulic fracturing model using high-confidence rock properties data and calibrated the model to field stimulation treatment data varying the two model variables with highest uncertainty: tectonic strain and average leak-off coefficient, while keeping all other model variables fixed. By reducing the number of adjusting model variables for calibration, we significantly lower the potential for over-fitting. Using an ultra-fast hydraulic fracturing simulator, we solved a global optimization problem to minimize the mismatch between the ISIPs and treatment pressures measured in the field and simulated by the model, for all the stages and all wells. This workflow helps us match the dominant ISIP trends in the field data and delivers higher confidence predictions in the regional stress. However, the uncertainty in the fracture geometry is still large. We also compared these results with traditional workflows that rely on selecting representative stages for calibration to field data. Results show that our workflow defines a better global optimum that best represents the behavior of all stages on all wells, and allows us to provide higher-confidence predictions of fracturing results for subsequent pads. We then used this higher confidence model to conduct sensitivity analysis for improving the well placement in subsequent pads and compared the results of the model predictions with the actual pad results.
A Signal Processing Approach for Analysis of Fracture Injection Test in Geothermal Reservoirs: A Case Study on the Utah FORGE Formation
Authors: Eltaleb Ibrahim , Rezaei Ali , Soliman M. Y. , Dindoruk Birol 
Published: April 2021

Abstract
Assessment of in-situ stresses and hydraulic fracturing stimulation are two critical parameters for successful heat extraction from Enhanced Geothermal Systems (EGS). Fracture injection and injection/flow back tests are two conventional techniques for estimating the minimum horizontal stress in subsurface formations. Because of the heat exchange during the test, ultra-low permeability of the host rock, and natural fractures, the conventional methods yield inaccurate results in geothermal reservoirs. In this paper, we present a new methodology based on the signal processing approach for analyzing DFIT in geothermal reservoirs. The applicability of our technique is demonstrated using several test data from the Utah FORGE project.
The main advantage of our methodology is that it does not depend on any assumption regarding fracture geometry and rock properties. Also, unlike most similar studies, we consider the effect of heat exchange between fracturing fluid and the hot rock. In our methodology, the recorded pressure and temperature are treated as signals, and a wavelet transform is applied to separate them to high pass (noise) and low pass (approximation) components. Using the noise energy of the two signals, we then identify different events such as fracture closure. Also, an analytical technique is used to correct the pressure by extracting the effect of fluid compressibility and heat exchange between the rock and injected fluid. We show that the G-Function technique underestimates the minimum horizontal stress in tight formations. After applying the corrections for pressure, the underestimation becomes more apparent. However, our approach gives consistent results before and after the pressure correction.
Using the developed technique, we analyzed several injection tests from the Utah FORGE project. Both recorded pressure and temperature have been analyzed. Results show that the energy of the pressure signal noise decreases to a minimum level at the fracture closure. The fracture closure is confirmed by applying the same technique on the recorded temperature. The moment of closure using the proposed methodology is compared to the G-function approach, before and after correction of the pressure for temperature.
Unlike physics-based techniques, the proposed method does not have any pre-assumption about the fracture's geometry or type of the well. The method solely relies on the pressure and temperature signals that are recorded during the injection and shut-in periods. Combining several analysis techniques to analyze DFIT (including the analysis of monitored temperature for a geothermal reservoir) is unique and maybe the first of its kind.
Data-Driven Causal Analyses of Parent-Child Well Interactions for Well Spacing Decisions
Authors: Sakhardande Rohan , Devegowda Deepak 
Published: April 2021

Abstract
The analyses of parent-child well performance is a complex problem depending on the interplay between timing, completion design, formation properties, direct frac-hits and well spacing. Assessing the impact of well spacing on parent or child well performance is therefore challenging. A naïve approach that is purely observational does not control for completion design or formation properties and can compromise well spacing decisions and economics and perhaps, lead to non-intuitive results. By using concepts from causal inference in randomized clinical trials, we quantify the impact of well spacing decisions on parent and child well performance.
The fundamental concept behind causal inference is that causality facilitates prediction; but being able to predict does not imply causality because of association between the variables. In this study, we work with a large dataset of over 3000 wells in a large oil-bearing province in Texas. The dataset includes several covariates such as completion design (proppant/fluid volumes, frac-stages, lateral length, cluster spacing, clusters/stage and others) and formation properties (mechanical and petrophysical properties) as well as downhole location. We evaluate the impact of well spacing on 6-month and 1-year cumulative oil in four groups associated with different ranges of parent-child spacing. By assessing the statistical balance between the covariates for both parent and child well groups (controlling for completion and formation properties), we estimate the causal impact of well spacing on parent and child well performance. We compare our analyses with the routine naïve approach that gives non-intuitive results.
In each of the four groups associated with different ranges of parent-child well spacing, the causal workflow quantifies the production loss associated with the parent and child well. This degradation in performance is seen to decrease with increasing well spacing and we provide an optimal well spacing value for this specific multi-bench unconventional play that has been validated in the field. The naïve analyses based on simply assessing association or correlation, on the contrary, shows increasing child well degradation for increasing well spacing, which is simply not supported by the data. The routinely applied correlative analyses between the outcome (cumulative oil) and predictors (well spacing) fails simply because it does not control for variations in completion design over the years, nor does it account for variations in the formation properties.
To our knowledge, there is no other paper in petroleum engineering literature that speaks of causal inference. This is a fundamental precept in medicine to assess drug efficacy by controlling for age, sex, habits and other covariates. The same workflow can easily be generalized to assess well spacing decisions and parent-child well performance across multi-generational completion designs and spatially variant formation properties.
Optimizing Completion Design and Well Spacing in the Powder River Basin Niobrara Oil Play
Authors: Burget Blake , Dannemiller Neal , Garrett Dylan , Kling Erik 
Published: April 2021

Abstract
A seven-step workflow to help subsurface teams establish an initial thesis for optimal completion design (cluster spacing, proppant per cluster) and well spacing in emerging / under-explored resource plays is proposed and executed for the Powder River Basin Niobrara unconventional oil play. The workflow uses Rate Transient Analysis (RTA) to determine the Ac∗k parameter and then walks the reader through how to sequentially decouple the parameter into its constituent parts (frac height (h), number of symmetrical fractures achieved (nf), permeability (k) and fracture half-length (xf)). Once these terms were quantified for each of the case study wells, they were used in a black oil reservoir simulator to compare predicted verses actual cumulative oil performance at 30, 60, 90,120 & 180 days. A long-term production match was achieved using xf as the lone history match parameter. xf verses proppant per effective half-cluster yielded an R2 value of &gt; 0.90. 28 simulation scenarios were executed to represent a range of cluster spacing, proppant per cluster and well spacing scenarios. Economics (ROR and/or NPV10/Net Acre) were determined for each of these scenarios under three different commodity pricing assumptions ($40/$2.50, $50/$2.50 and $60/$2.50). An initial thesis for optimal cluster spacing, proppant per designed cluster and well spacing were determined to be 12’, 47,500 lbs and 8-14 wells per section (based on whether or not fracture asymmetry is considered) when WTI and Henry Hub are assumed to be $50 & $2.50 flat.
Early Applications of Viscosifying Friction Reducers for Hydraulic Fracturing Operations in the Vaca Muerta Formation, Argentina
Authors: Sentinelli Roberto , Moreno Leandro , Pellicer Marcelo , Van Domelen Mark 
Published: April 2021

Abstract
Early hydraulic fracturing completions in the Vaca Muerta Formation in central Argentina have incorporated the use of conventional fluid systems, such as linear and crosslinked guar-based polymers. Within the past few years, however, the benefits of viscosifying friction reducers (VFR) have been demonstrated in the industry, predominantly within the United States. The objective of this project was to trial the VFR fluid technology in fracturing operations in this area for potential use for full field development.
After studying the potential advantages of the VFR technology including cost savings, simplified operations and enhanced well production, a project was initiated to determine if those same benefits could be obtained. To accomplish this, studies were performed to ensure economic and technical justification through a stepwise process of laboratory testing, logistical and operational considerations, a single well field trial, and a five well development phase evaluation project. The pilot project was performed on a horizontal, 27 stage lateral in the Aguada Pichana Oeste field in the Neuquen Basin of Argentina. The five well development phase evaluation project was performed in the Lindero Atravesado field.
Positive laboratory test results led to a field trial using this technology, during which several benefits of the VFR fluid system began to emerge. Operational efficiency was an early success, including a reduction in the quantity of chemicals on location, more simplified pumping schedules, and low pumping pressures. Secondly, significant cost savings were realized compared to previous fluid system packages. Finally, positive production results were observed, leading to the decision to incorporate this technology into full field development operations. This paper will review the results of the stepwise evaluation process along with a focus on the economic benefits and well production from the development phase evaluation project.
This paper describes the transition by Pan American Energy (PAE) from conventional fracturing fluids to viscosifying friction reducer (VFR) technology in the Vaca Muerta Formation. The paper highlights the performance of a relatively new treatment fluid which delivered positive results in a strategic international asset. The project has led to full field development using this technology. The same efficiencies provided by this system can potentially be realized through applications in other basins.
High Fidelity Fibre-Optic Observations and Resultant Fracture Modeling in Support of Planarity
Authors: Shahri Mojtaba , Tucker Andrew , Rice Craig , Lathrop Zach , Ratcliff Dave , McClure Mark , Fowler Garrett 
Published: April 2021

Abstract
In the last decade, we have observed major advancements in different modeling techniques for hydraulic fracturing propagation. Direct monitoring techniques such as fibre-optics can be used to calibrate these models and significantly enhance our understanding of subsurface processes.
In this study, we present field monitoring observations indicating consistently oriented, planar fractures in an offset-well at different landing zones in the Permian basin. Frac hit counts, location, and timing statistics can be compiled from the data using offset wells at different distances and depths. The statistics can be used to calibrate a detailed three-dimensional fully coupled hydraulic fracturing and reservoir simulator. In addition to these high-level observations, detailed fibre signatures such as strain response during frac arrival to the monitoring well, post shut-in frac propagation and frac speed degradation with length can be modeled using the simulator for further calibration purposes.
Application to frac modeling calibration is presented through different case studies. The simulator was used to directly generate the ‘waterfall plot’ output from the fibre-optic under a variety of scenarios. The history match to the large, detailed synthetic fibre dataset provided exceptional model calibration, enabling a detailed description of the fracture geometry, and a high-confidence estimation of key model parameters. The detailed synthetic fibre data generated by the simulator were remarkably consistent with the actual data. This indicates a good consistency with classical analytical fracture mechanics predictions and further confirm the interpretation of planar fracture propagation.
This study shows how careful integration of offset-well fibre-optic measurements can provide detailed characterization of fracture geometry, growth rate, and physics. The result is a detailed picture of hydraulic fracture propagation in the Midland Basin. The comparison of the waterfall plot simulations and data indicate that hydraulic fractures can, in fact, be very well modeled as nearly-linear cracks (the ‘planar fracture modeling’ approach).