Turning a Breakthrough Technology into a Scalable Process: Sealed Wellbore Pressure Monitoring

2021 ◽  
Author(s):  
Jessica Iriarte ◽  
Samid Hoda ◽  
Ryan Guest ◽  
Mary Van Domelen
Keyword(s):  
Hydraulic Fracturing ◽  
Pressure Gauge ◽  
Diagnostic Technique ◽  
Fracture Network ◽  
Machine Learning Algorithms ◽  
Valuable Insight ◽  
Pressure Monitoring ◽  
Interpretation Biases ◽  
Wellbore Pressure ◽  
Treatment Data

Abstract A breakthrough patent-pending pressure diagnostic technique using offset sealed wellbores as monitoring sources was introduced at the 2020 Hydraulic Fracturing Technology Conference. This technique quantifies various hydraulic fracture parameters using only a surface gauge mounted on the sealed wellbore(s). The initial concept, operational processes, and analysis techniques were developed and deployed by Devon Energy. By scaling and automating the process, Sealed Wellbore Pressure Monitoring (SWPM) is now available to the industry as a repeatable workflow that greatly reduces analysis time and improves visualizations to aid data interpretations. The authors successfully automated the SWPM analysis procedure using a cloud-based software platform designed to ingest, process, and analyze high-frequency hydraulic fracturing data. The minimum data for the analysis consists of the standard frac treatment data combined with the high-resolution pressure gauge data for each sealed wellbore. The team developed machine learning algorithms to identify the key events required by a sealed wellbore pressure analysis: the start, end, and magnitude of each pressure response detected in the sealed wellbore(s) while actively fracturing offset wells. The result is a rapid, repeatable SWPM analysis that minimizes individual interpretation biases. The primary deliverables from SWPM analyses are the Volumes to First Response (VFR) on a per stage basis. In many projects, multiple pressure responses within a single stage have been observed, which provides valuable insight into fracture network complexity and cluster/stage efficiency. Various methods are used to visualize and statistically analyze the data. A scalable process facilitates creating a statistical database for comparing completion designs that can be segmented by play, formation, or other geological variations. Completion designs can then be optimized based upon the observed well responses. With enough observations and based on certain spacings, probabilities of when to expect fracture interactions could be assigned for different plays.

Pressure-Monitoring Technique Uses Sealed Wellbore Pressure as Source

2021 ◽  
Vol 73 (03) ◽  
pp. 51-52
Author(s):  
Chris Carpenter
Keyword(s):  
Closed System ◽  
Growth Rates ◽  
Pressure Gauge ◽  
Local Deformation ◽  
Pressure Response ◽  
Pressure Monitoring ◽  
Fracture Intersection ◽  
Monitoring Technique ◽  
Wellbore Pressure ◽  
Fracture Growth

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 199731, “Monitoring the Pulse of a Well Through Sealed Wellbore Pressure Monitoring: A Breakthrough Diagnostic With a Multibasin Case Study,” by Kyle Haustveit, SPE, Brendan Elliott, SPE, and Jackson Haffener, SPE, Devon Energy, et al., prepared for the 2020 SPE Hydraulic Fracturing Technology Conference and Exhibition, The Woodlands, Texas, 4-6 February. The paper has not been peer reviewed. A pressure-monitoring technique using an offset sealed wellbore as a monitoring source has led to advancements in quantifying cluster efficiencies of hydraulic stimulations in real time. Sealed wellbore pressure monitoring (SWPM) is a low-cost, nonintrusive method used to evaluate and quantify fracture-growth rates and fracture-driven interactions during a hydraulic stimulation. The measurements can be made with only a surface pressure gauge on a monitor well. To date, more than 1,500 stages have been monitored using the technique. The complete paper reviews multiple SWPM case studies, collected from projects in the Anadarko and Permian Delaware basins; this synopsis will concentrate on the concepts behind, and the validation of, the technique. Introduction SWPM is performed on a well that acts as a closed system. The well cannot be connected to a formation through perforations or other types of access points; the casing must be sealed. Uncompleted wells can be used if the shallowest perforations are isolated from the formation. In an existing producing well, a plug must be set above the shallowest perforations to create a closed system from the top of the plug to surface where the pressure measurement is recorded. The wellbore should be filled with low-compressibility fluid (e.g., completion brine) to amplify the pressure response created during monitoring. Fractures intersecting the sealed wellbore cause local deformation, which results in a small volume reduction in the closed system (system being the fluid volume inside of the casing) and generates a discernible and distinct pressure response. Pressure can be recorded either using a surface gauge or a downhole gauge. Multiple sealed wellbores can be used as monitor wells for a single treatment well, allowing for a more-detailed understanding of fracture growth rates during a stimulation. The field execution of SWPM is simple and does not require any tools to enter the wellbore. A surface gauge provides the necessary data needed to evaluate the fracture interactions with the monitor wellbore. There is no need to alter zipper operations if sealed wellbores are available. The main restriction SWPM introduces to operations is the necessity to leave new wellbores, designated as monitors, unprepped by not opening toe sleeves or shooting perforations for Stage 1 until monitoring of the offset treatment wells is complete. Because the pressure response in the monitor well is a result of a fracture intersection at the wellbore, the method reduces the uncertainty related to the location of the monitor point commonly associated with other offset pressure-monitoring techniques.

scholarly journals Numerical modeling of complex hydraulic fracture networks based on the discontinuous deformation analysis (DDA) method

2021 ◽  
pp. 014459872098153
Author(s):  
Yanzhi Hu ◽  
Xiao Li ◽  
Zhaobin Zhang ◽  
Jianming He ◽  
Guanfang Li
Keyword(s):  
Hydraulic Fracturing ◽  
Hydraulic Fracture ◽  
Fracture Network ◽  
Discontinuous Deformation Analysis ◽  
Deformation Analysis ◽  
Fracture Networks ◽  
Proposed Model ◽  
Discontinuous Deformation ◽  
Shale Reservoirs ◽  
Dda Method

Hydraulic fracturing is one of the most important technologies for shale gas production. Complex hydraulic fracture networks can be stimulated in shale reservoirs due to the existence of numerous natural fractures. The prediction of the complex fracture network remains a difficult and challenging problem. This paper presents a fully coupled hydromechanical model for complex hydraulic fracture network propagation based on the discontinuous deformation analysis (DDA) method. In the proposed model, the fracture propagation and rock mass deformation are simulated under the framework of DDA, and the fluid flow within fractures is simulated using lubrication theory. In particular, the natural fracture network is considered by using the discrete fracture network (DFN) model. The proposed model is widely verified against several analytical and experimental results. All the numerical results show good agreement. Then, this model is applied to field-scale modeling of hydraulic fracturing in naturally fractured shale reservoirs. The simulation results show that the proposed model can capture the evolution process of complex hydraulic fracture networks. This work offers a feasible numerical tool for investigating hydraulic fracturing processes, which may be useful for optimizing the fracturing design of shale gas reservoirs.

scholarly journals Knowledge discovery in Chinese herbal medicine: a machine learning perspective

2021 ◽  
Vol 336 ◽  
pp. 06024
Author(s):  
Nan Liang ◽  
Qing Liang ◽  
Fenglei Ji
Keyword(s):  
Machine Learning ◽  
Herbal Medicine ◽  
Knowledge Discovery ◽  
Chinese Herbal Medicine ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Current Status ◽  
Network Pharmacology ◽  
Valuable Insight ◽  
Chinese Herbal

Traditional Chinese Medicine (TCM) has attracted more and more attention due to its remarkable effects on treating diseases, and Chinese herbal medicine (CHM) is an important partition of TCM, rich in natural active ingredients. Researchers are trying multiple analytical methods to dig out more valuable information about CHM and reveal the principle of TCM. Machine learning is playing an important role in the studies. Knowledge discovery of CHM using machine learning mainly includes quality control of CHM, network pharmacology in CHM, and medical prescriptions composed by CHM, aiming to understand TCM better, provide more efficiency methods in the production of CHM and find novel treatment of disease not curable nowadays. In this paper, we summarized the basic idea of frequently used classification and clustering machine learning algorithms, introduced pre-processing algorithms commonly used to simplify and accelerate machine learning procedure, presented current status of machine learning algorithms’ applications in knowledge discovery of CHM, discussed challenges and future trends of machine learning’s application in CHM. It is believed that the paper provides a valuable insight for the starters trying to apply machine learning in the study of CHM and catch up the recent status of related researches.

Advancements in Step Down Tests to Guide Perforation Cluster Design and Limited Entry Pressure Intensities - Learnings from Field Tests in Multiple Basins

2021 ◽  
Author(s):  
Somnath Mondal ◽  
Min Zhang ◽  
Paul Huckabee ◽  
Gustavo Ugueto ◽  
Raymond Jones ◽  
...  
Keyword(s):  
Pressure Drop ◽  
Hydraulic Fracturing ◽  
Hydraulic Fracture ◽  
Fracture Propagation ◽  
Field Tests ◽  
Pressure Drops ◽  
Wellbore Pressure ◽  
Hydraulic Fracture Propagation ◽  
Step Down ◽  
Cluster Design

Abstract This paper presents advancements in step-down-test (SDT) interpretation to better design perforation clusters. The methods provided here allow us to better estimate the pressure drop in perforations and near-wellbore tortuosity in hydraulic fracturing treatments. Data is presented from field tests from fracturing stages with different completion architectures across multiple basins including Permian Delaware, Vaca Muerta, Montney, and Utica. The sensitivity of near-wellbore pressure drops and perforation size on stimulation distribution effectiveness in plug-and-perf (PnP) treatments is modeled using a coupled hydraulic fracturing simulator. This advanced analysis of SDT data enables us to improve stimulation distribution effectiveness in multi-cluster or multiple entry completions. This analysis goes much further than the methodology presented in URTeC2019-1141 and additional examples are presented to illustrate its advantages. In a typical SDT, the injection flowrate is reduced in four or five abrupt decrements or "steps", each with a duration long enough for the rate and pressure to stabilize. The pressure-rate response is used to estimate the magnitude of perforation efficiency and near-wellbore tortuosity. In this paper, two SDTs with clean fluids were conducted in each stage - one before and another after proppant slurry was injected. SDTs were conducted in cemented single-point entry (cSPE) sleeves, which present a unique opportunity to measure only near-wellbore tortuosity using bottom-hole pressure gauge at sleeve depth, negligible perforation pressure drops, and less uncertainty in interpretation. SDTs were conducted in PnP stages in multiple unconventional basins. The results from one set of PnP stages with optic fiber distributed sensing were modeled with a hydraulic fracturing simulator that combines wellbore proppant transport, perforation size growth, near-wellbore pressure drop, and hydraulic fracture propagation. Past SDT analysis assumed that the pressure drop due to near-wellbore tortuosity is proportional to the flow rate raised to an exponent, β = 0.5, which typically overestimates perforation friction from SDTs. Theoretical derivations show that β is related to the geometry and flow type in the near-wellbore region. Results show that initial β (before proppant slurry) is typically around 0.5, but the final value of β (after proppant slurry) is approximately 1, likely due to the erosion of near-wellbore tortuosity by the proppant slurry. The new methodology incorporates the increase in β due proppant slurry erosion. Hydraulic fracturing modeling, calibrated with optic fiber data, demonstrates that the stimulation distribution effectiveness must consider the interdependence of proppant segregation in the wellbore, perforation erosion, and near-wellbore tortuosity. An improved methodology is presented to quantify the magnitude of perforation and near-wellbore tortuosity related pressure drops before and after pumping of proppant slurry in typical PnP hydraulic fracture stimulations. The workflow presented here shows how the uncertainties in the magnitude of near-wellbore complexity and perforation size, along with uncertainties in hydraulic fracture propagation parameters, can be incorporated in perforation cluster design.

Determination of the Near-Wellbore Pressure Drop for Dual Casing in Hydraulic Fracturing and Refracturing Applications

2022 ◽  
Author(s):  
Joern Loehken ◽  
Davood Yosefnejad ◽  
Liam McNelis ◽  
Bernd Fricke
Keyword(s):  
Pressure Drop ◽  
Hydraulic Fracturing ◽  
Complex Flow ◽  
Cement Layer ◽  
Natural Rock ◽  
Wellbore Pressure ◽  
Flow Through ◽  
The Difference ◽  
Coefficient Of Discharge

Abstract Due to the increases in completion costs demand for production improvements, fracturing through double casing in upper reservoirs for mature wells and refracturing early stimulated wells to change the completion design, has become more and more popular. One of the most common technologies used to re-stimulate previously fracked wells, is to run a second, smaller casing or tubular inside of the existing and already perforated pipes of the completed well. The new inner and old outer casing are isolated from each other by a cement layer, which prevents any hydraulic communication between the pre-existing and new perforations, as well as between adjacent new perforations. For these smaller inner casing diameters, specially tailored and designed re-fracturing perforation systems are deployed, which can shoot casing entrance holes of very similar size through both casings, nearly independent of the phasing and still capable of creating tunnels reaching beyond the cement layer into the natural rock formation. Although discussing on the API RP-19B section VII test format has recently been initiated and many companies have started to test multiple casing scenarios and charge performance, not much is known about the complex flow through two radially aligned holes in dual casings. In the paper we will look in detail at the parameters which influence the flow, especially the Coefficient of Discharge of such a dual casing setup. We will evaluate how much the near wellbore pressure drop is affected by the hole's sizes in the first and second casing, respectively the difference between them and investigate how the cement layer is influenced by turbulences, which might build up in the annulus. The results will enhance the design and provide a better understanding of fracturing or refracturing through double casings for hydraulic fracturing specialists and both operation and services companies.

Monitoring the Pulse of a Well Through Sealed Wellbore Pressure Monitoring, a Breakthrough Diagnostic With a Multi-Basin Case Study

2020 ◽  
Author(s):  
Kyle Haustveit ◽  
Brendan Elliott ◽  
Jackson Haffener ◽  
Chris Ketter ◽  
Josh O'Brien ◽  
...  
Keyword(s):  
Pressure Monitoring ◽  
Wellbore Pressure

scholarly journals Cuffless Blood Pressure Monitoring

2020 ◽  
Vol 15 (10) ◽  
pp. 1531-1538 ◽  
Author(s):  
Jay A. Pandit ◽  
Enrique Lores ◽  
Daniel Batlle
Keyword(s):  
Blood Pressure Monitoring ◽  
Heart Rhythm ◽  
Machine Learning Algorithms ◽  
Masked Hypertension ◽  
Pressure Monitoring ◽  
Nocturnal Hypertension ◽  
Ambulatory Bp Monitoring ◽  
Repeated Use ◽  
Cuffless Blood Pressure ◽  
Novel Devices

Current BP measurements are on the basis of traditional BP cuff approaches. Ambulatory BP monitoring, at 15- to 30-minute intervals usually over 24 hours, provides sufficiently continuous readings that are superior to the office-based snapshot, but this system is not suitable for frequent repeated use. A true continuous BP measurement that could collect BP passively and frequently would require a cuffless method that could be worn by the patient, with the data stored electronically much the same way that heart rate and heart rhythm are already done routinely. Ideally, BP should be measured continuously and frequently during diverse activities during both daytime and nighttime in the same subject by means of novel devices. There is increasing excitement for newer methods to measure BP on the basis of sensors and algorithm development. As new devices are refined and their accuracy is improved, it will be possible to better assess masked hypertension, nocturnal hypertension, and the severity and variability of BP. In this review, we discuss the progression in the field, particularly in the last 5 years, ending with sensor-based approaches that incorporate machine learning algorithms to personalized medicine.

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