bluuebunny/crossref_metadata_2025_split huggingface dataset:
DFIT Analysis and Interpretation in Layered Rocks
Authors: Zheng Shuang , Manchanda Ripudaman , Wang HanYi , Sharma Mukul 
Published: January 2020

Abstract
Diagnostic fracture injection tests (DFITs) are often used to estimate formation properties such as closure stress, pore pressure, and matrix permeability. These estimations are typically based on analysis of pressure data assuming the closure of simple planar fractures in homogeneous reservoirs. These interpretations are incorrect when dealing with complex reservoir environments such as layered reservoirs with different properties and stresses. This paper investigates the impact of such complex environments on DFIT interpretation and presents a systematic method to analyze the data.
A 3-D implicitly integrated poroelastic fracture-reservoir-wellbore model is used to simulate DFITs. DFIT fracture propagation and well shut-in are simulated with implicitly computed fluid leak-off and fracture closure. The model is validated by simulating a DFIT for a homogeneous reservoir and the implicitly calculated surface pressure is interpreted to obtain the simulation inputs (stress, pore pressure, permeability, etc.). A multi-layer reservoir model is then built in the numerical simulation domain and a DFIT is simulated in the target layer. The properties and thickness of the layers are varied to analyze their impact on the observed DFIT signature.
We analyze the impact of layer thicknesses, layer stresses, pressure and permeability of each layer, stress contrast between the layers, fracture interaction with bedding planes and the rock roughness and hardness of each layer on the DFIT pressure signature. We show that the layer property variations can cause different but characteristic DFIT pressure responses. Fracture propagation into layers with different stresses induces multiple closure events in the observed pressure signature, which provides a quantitative representation of the fracture height growth. The emergence of these closure events in the pressure signature are found to be dependent on the hardness and modulus of the rock layers and the fluid communication between the closing parts of the fracture. The DFIT signature patterns are also found to correlate with the interaction of the fracture with bedding planes (cross/arrest/divert) and provide valuable insights into fracture containment.
In this work we present best practices for performing DFIT analysis in layered reservoirs. Results from simulated DFITs in layered reservoirs clearly show the effect of key heterogeneity parameters on DFIT responses. The results from this work can be used to more accurately determine reservoir closure stress, pore pressure, reservoir permeability, fracture compliance, fracture conductivity, and fracture containment in heterogeneous reservoirs.
The Effects of Down-Spacing in the Delaware Basin Wolfcamp Play: A Case History
Authors: Bommer Peter Anthony , Bayne Marcus 
Published: January 2020

Abstract
The effect of horizontal well spacing on stimulation performance and well results is of keen scientific and economic interest to the industry. The objective of this paper is to demonstrate these effects in a grouping of five horizontal Wolfcamp wells drilled in a down-spaced configuration where inter-well distances were reduced from 1320′ to 660′.
The subject project is located in Ward County, Texas, on a 640 acre lease. A stand-alone Wolfcamp A2 zone well (legacy well) was drilled on the project acreage in late 2016 followed by the drilling of four development wells directly offsetting the legacy well in mid-2018. The four development wells were spaced 660′ apart as opposed to the existing norm of 1320′. This paper presents various pressure, microseismic, tracer, and production data collected during and following the zipper stimulation of the four development wells. This rich data set yielded significant information about the drainage characteristics of the legacy well, the effect of pressure depletion on fracture geometry, the nature of fracture driven interactions (FDI) in down-spaced wells, and the inter-relationship of these factors in their effect on production results. Active well defense was performed in the legacy well and results from these defense operations is also reported.
Inter-well spacing of 660′ between wells in the same zone resulted in significantly diminished production results compared to the base case resulting in lowered projected rates of return for the well group. Depletion in the legacy well resulted in larger fracture geometries in the nearest development wells, but not in wells 990′ away. This resulted in larger stimulated volumes in the nearer wells but also diminished oil production. The inferential conclusion is that localizing stimulation energy in the near vicinity of the treated well yields improved well results. Concerning FDI, the data indicate that wells within 660′ of each other are likely to interfere with each other, while the opposite was true for wells that were 990′ apart.
Real-Time Hydraulic Fracturing Pressure Prediction with Machine Learning
Authors: Ben Yuxing , Perrotte Michael , Ezzatabadipour Mohammadmehdi , Ali Irfan , Sankaran Sathish , Harlin Clayton , Cao Dingzhou 
Published: January 2020

Abstract
During hydraulic fracturing jobs, engineers must monitor the wellhead pressure and adjust the pumping schedule in real time to avoid screenout, optimize the proppant and fluid amounts, and minimize cost. In this paper, we use machine learning to predict wellhead pressure in real time during hydraulic fracturing. The new algorithm can assist engineers in monitoring and optimizing the pumping schedule.
We explored several neural network models. For each hydraulic fracturing stage, we train a machine learning (ML) model with the data from the first several minutes and predict the wellhead pressure for the next several minutes; we then add the data for the next several minutes, train a second ML model and predict the pressure for the next couple of minutes; and so on. We used several performance metrics to compare different models and select the best model for deployment to the Cloud, where a real-time completions platform is developed and hosted.
We selected more than 100 hydraulic fracturing stages from several wells completed in the Delaware Basin and tested several ML methods on the historical data. The wellhead pressure can be predicted with an acceptable accuracy by a slightly nonlinear machine learning model. We tested the ML model on the Cloud, where real-time streaming data such as slurry rate and proppant concentration are gathered. The computation is fast enough that a real-time wellhead pressure can be predicted.
Sound Completion Engineering Techniques Lead to Superior Production of the Codell Sandstone In Laramie County, Wyoming
Authors: Kosters Bryan , Shaw Kevin , D'Souza Shodan , Clark Justin , Besler Monte , Barham Michael 
Published: January 2020

Abstract
In the era of unconventional oil and gas drilling, time constraints often fast-track projects that lack sound completion practices. A multi-year production study of the Codell Sandstone in Laramie County, Wyoming has developed better completion practices that improved production and Estimated Ultimate Recovery (EUR).
Helis Oil and Gas Co., LLC formed a team of experts to identify and execute best completion engineering practices for their horizontal Codell wells. Utilizing data from the production study and leaning on experience, the team identified seven core areas for improving Codell completions. The team (1) recommended performing fracture diagnostics, (2) investigated methods to increase Stimulated Reservoir Volume (SRV), (3) optimized the job size, (4) reviewed proper chemical additive selection, (5) included on-site real-time micromanagement of treating pressure, (6) reviewed wireline procedures, and (7) performed post-fracture treatment analysis.
The Laramie County comparative study included 247 wells completed during the 4-year time period of 2014 to 2018. Helis Oil and Gas Co., LLC completed a total of 13 wells with the enhanced workflow. Considering normalized average cumulative production per well metric, Helis wells outperformed offset wells by 58% in the first 6 months of production. Extending the time frame to the first 12 months of production, on average, the Helis wells produced 75% more oil. A total of 5 Helis wells outpaced the P10 normalized production curve within the first year of production. Examining normalized decline curves, Helis wells continued to outperform. Furthermore, 10 of the 13 Helis wells outperformed the P10 normalized decline curve after 12 months of production.
These techniques help get out of the mindset of the cookie cutter approach with assembly line frac designs. Focusing on these core principles and systematically applying engineered completion techniques to the Codell workflow has helped Helis Oil and Gas Co., LLC achieve superior production and outperform all other operators in the area.
Evaluating Limited Entry Perforating & Diverter Completion Techniques with Ultrasonic Perforation Imaging & Fiber Optic DTS Warmbacks
Authors: Murphree Chase , Kintzing Malcolm , Robinson Stephen , Sepehri Jay 
Published: January 2020

Abstract
The objective of this project was to evaluate extreme, limited-entry perforating and particulate diverter completion techniques with ultrasonic perforation imaging and distributed temperature sensing (DTS). The scope of this project includes multiple, Midland Basin, horizontal wells completed with varied completion designs. Ultrasonic images of the perforations were obtained prior to fracturing and post-fracturing to observe erosion patterns of each design. Fiber optic DTS warmbacks gathered temperature profiles of each wellbore after stimulation to quantify fracture initiation points (FIP) of each design.
Perforation imaging results showed that all perforation clusters were eroded. This indicates that all clusters of perforations received some amount of treatment fluid and proppant. The data collected also suggest that perforation erosion occurs quickly, and the rate of perforation erosion decreases dramatically after a critical mass of proppant is pumped through the perforations, potentially negating high perforation friction designs early in the stage. Despite all clusters showing some level of perforation erosion, fiber optic DTS warmback data only showed fracture initiation points for ∼70% of the clusters (cluster efficiency of 70%). This data suggests that multiple clusters could be receiving fluid and proppant while contributing to a single fracture network and not creating a unique, dominate fracture for each perforation cluster. Another possibility is that although some clusters were receiving treatment slurry, the amount of stimulation was not sufficient to create and sustain a major fracture.
The data gathered in this project should change conventional thought processes on a number of subjects including perforation erosion, limited-entry, diverters, proppant placement, fracture growth, and DTS interpretations.
Case History of Drainage Mapping and Effective Fracture Length in the Bakken
Authors: Cipolla Craig , Litvak Michael , Prasad R. S. , McClure Mark 
Published: January 2020

Abstract
Understanding effective fracture length and characterizing drainage patterns is critical for optimal development of unconventional resources. This paper documents a comprehensive field experiment in the Bakken formation, where several fracture diagnostic technologies and drainage mapping methods were used in a unique project setup to measure effective fracture length and map drainage.
Two vertical wells (V1 and V2) were drilled 1,000 ft away from a Bakken lateral (H1) with 10 years of production (Fig. 1). The two vertical wells were 200 ft apart. V2 was used for microseismic and deformation (downhole tilt) measurements, while V1 was used for pressure measurements and hydraulic fracture characterization. The project consisted of re-pressurizing the existing lateral (parent well), using microseismic monitoring to map drainage (designated MDD, Dohmen et al. 2013, 2014, 2017). A DFIT was performed in the V1 well before the MDD to measure local stress and pore pressure. Following the MDD, a small propped fracture treatment was pumped in the V1. The H1 well was then produced for 4 months and DFITs pumped in the V1 and V2 wells. This comprehensive fracture diagnostic dataset was integrated with detailed core and log measurements, hydraulic fracture modeling, and advanced reservoir simulation to characterize the hydraulic fracture performance.
The H1 MDD indicated that the major pressure depletion (drainage) was approximately 500 ft on either side of the lateral. H1 BHP showed local reservoir pressure was 1,000 psi. The initial V1 DFIT showed virgin reservoir pressure, but surprisingly, the 20 bbl DFIT injection was detected on the H1 BHP gauge. Microseismic mapping of the V1 fracture treatment (15 klbs, 600 bbl) showed a planar fracture with a half-length of 1,000 ft. The V1 fracture "hit" the H1, measured by microseismic and confirmed by a 1,650 psi increase in H1 BHP. The microseismic showed a symmetrical fracture, suggesting that the H1 re-pressurization mitigated the detrimental effects of parent well depletion that can cause severe asymmetry. Downhole tilt and microseismic showed fracture height quickly extended downward through the lower Bakken shale into the Three Forks. The V1 was not produced. However, the H1 oil rate doubled after the V1 frac hit, indicating significant stimulation. V1 DFIT #2 showed 1,800 psi depletion, while the V2 DFIT showed approximately 1,000 psi depletion, confirming that the V1 fracture is "flowing" into the H1 lateral 1,000 ft away. The reservoir simulation history match indicated low fracture conductivity, but enough to improve well productivity and drain oil over 1,000-ft from the H1 lateral.
This paper details a comprehensive fracture diagnostic dataset gathered in a unique field laboratory where a single hydraulic fracture from a vertical well is used to characterize fracture conductivity and flowing length.
The Effective Cluster Spacing Plays the Vital Role in Unconventional Reservoir Development – Permian Basin Case Studies
Authors: Xiong Hongjie 
Published: January 2020

Abstract
Through near 3000 horizontal producing wells on University Lands in the Permian Basin, we have performed a series of case studies to systematically investigate the most critical parameters to maximize well performance and the value of field development. In addition to summarizing multiple study results, the paper concludes and elaborates that the effective cluster spacing is the most critical parameter that we may be able to control and can influence the most in the unconventional reservoir development.
The paper first shows three observation cases of perforation cluster spacings and their corresponding well performance. To understand why the effective cluster spacing is so vital to well performance, we then illustrate the fundamental theory to understand the pressure propagation timing and depletion patterns in different reservoirs. We compare the mechanistic modeling results of pressure depletion and corresponding recovery efficiencies with different effective cluster spacings by multiple modeling approaches, including single-porosity model, and dual-porosity model, which has validated our case study results and is very insightful for us to optimize perforation cluster spacings.
We then discuss the possible reasons of often-observed well interference. With a large data sample, the paper illustrates the good correlation between well performance and completion effectiveness. The paper presents the EUR and NPV evaluation results of different field development case histories, such as between tight cluster spacing and wide cluster spacing. We will also briefly discuss the current technologies and practices to improve cluster efficiency in the completion process.
Based upon the multiple case studies, theory investigation, and rigorous modeling, we have concluded that the effective cluster spacing is the most critical factor to influence well performance and the field development value.
The workflow illustrated in the paper can be used for operators to systematically optimize their cluster spacings as well as field development plans. To maximize the value of developing unconventional reservoirs, it is vital to optimize cluster spacing and cost-effectively achieve tighter effective cluster spacing.
Diagnosing Multistage Fracture Treatments with Distributed Fiber-Optic Sensors
Authors: Pakhotina Iuliia , Sakaida Shohei , Zhu Ding , Hill A. Daniel 
Published: January 2020

Abstract
Distributed acoustic sensing technology is a diagnostic method that has been implemented in the oil and gas industry for flow monitoring during injection or production. One of the applications is to estimate fluid distribution during hydraulic fracturing treatment. This is an invaluable diagnostic tool for multistage fracture treatments because of the large number of parameters and high uncertainty involved in these fracture treatments. Distributed acoustic sensor (DAS) measurements are based on data extracted from a fiber optic cable installed in a wellbore. Fiber optic cable strain is sensitive to temperature and acoustic variations induced by fluid flow with different fluid properties and fracture geometries. These parameters are evaluated from the back-scattered laser pulse through the fiber using coherent Rayleigh backscattering for DAS and Raman backscattering for distributed temperature sensing (DTS). The DAS interrogation system acquires strain response to acoustic variations along the measured depth of the wellbore for all periods of time.
This study presents a method of interpretation of flow rate distribution from acoustic signals from DAS measurements. Raw acoustic measurements are transformed to energy attribute distribution for all necessary depth locations and timeframe. It allows to calculate energy for each perforation cluster location. This calculation demands proper depth interval consideration for each perforation cluster. Local minimums of time average energy attribute allow to find depth window where integrate DAS channels measurements for each time step occurs. Based on the previous experimental and computational fluid dynamic investigations, the correlation between acoustic signal and flow rate is applied to interpret the measured DAS data to flow distribution.
In this paper, the system of equations which connects acoustic energy response with clusters flow rate distribution during the injection period using these correlations is introduced. The solution of this system allows to calculate cumulative volume for each perforation cluster on each time step and in the end of fracture treatment. As additional verification of flow rate distribution, the results of DAS interpretation were compared with interpretation results of DTS. A field example is used to illustrate the interpretation procedure.
From this work, it is concluded that besides qualitative analysis, the DAS interpretation method provides a quantitative estimation of flow distribution. Based on the current assumptions, the interpretation results from DAS and DTS are comparable with satisfactory agreement. The combined DAS and DTS interpretations help to understand cluster efficiency in multistage fracture treatments.
Field-Scale Computational Fluid Dynamics CFD Modeling of Proppant Transport and Distribution Within a Horizontal Hydraulic Fracturing Stage
Authors: Almulhim Abdulraof , Kebert Brent , Miskimins Jennifer , Hunter William , Soehner Gage 
Published: January 2020

Abstract
Treating every perforation cluster during a hydraulic fracturing treatment is a key element to ensuring the effectiveness and overall success of the well stimulation process. With completion costs being 50% of the total well cost in shale reservoirs and the reliance on hydraulic fracturing as a key technology for development, operators are concerned with maximizing the well performance by optimizing the stimulation design. In multi-stage horizontal well treatments, equal diversion of the fracturing fluid and proppant to all perforation clusters is desired, as bias proppant distribution may cause early screen-out and/or leave some fractures unpropped.
Computational fluid dynamics (CFD) is a branch of fluid mechanics that numerically solves Navier-Stokes equations and predicts the fluid flow behavior within a specified computational domain. CFD also has the capability to model the flow of dispersed particles within a fluid through the use of a discrete phase model (DPM). Recently, CFD has been utilized by various researchers as a tool to model fracturing slurry flow within perforation clusters to predict proppant transport and distribution trends.
This work models the fluid and particle flow using CFD DPM within a single hydraulic fracturing stage to improve our understanding of the proppant transport and distribution between multi-perforation clusters. The paper presents the CFD modeling methodology and results of two main perforation designs including traditional 0° phasing, vertical perforations and modified 45° angled shot perforations. To be able to compare the modeling to actual field conditions and field diagnostics, slickwater fracturing fluid with 40/70 and 100 mesh sand at a varying proppant concentration from 1 to 2 ppg are used in the model to replicate a field-scale 15-cluster stage. The modeling outcomes are then compared and validated to actual well post-job diagnostics; proppant tracers and perforation erosion signs captured by downhole cameras. These field results help to calibrate the CFD models, which then allowed sensitivity analysis and design improvement.