In recent years, in unconventional reservoirs, main fracture parameters including fracture permeability and fracture volume can be early evaluated using flowback data analysis. For analysis purposes, diagnostic plots, straight-line methods, and simulation model history-matching techniques are utilized. Usually, immediate gas and water production occur during flowback in shale gas wells. In this paper, solution of water diffusivity equation for different flow regimes during the early time of well life was used to analyze water performance. These flow regimes were determined based on the diagnostic plot of water rate vs. time. The analysis from Water RTA was used to calculate initial water in place (OWIP) and fracture parameters. The difference between the OWIP and the injected fracturing fluid was correlated against the formation water saturation. The main conclusions from this analysis are; 1) High quality shale if the OWIP equal to the total injected water volume, and water-production data usually do not show the transient period and in some cases, boundary dominated flow (BDF) is present.
Hydraulic fracturing pumping data is recorded in the field at one-second intervals. Engineers spend hours identifying events such as Instantaneous Shut-in Pressure (ISIP) in the time-series data that is generated. The ISIP flag is placed at the end of the stage pumping time, immediately after shut-in and before the pressure starts to drop. This is estimated by placing a straight line on the early pressure decline and locating the point in time where the pressure rate is zero. Manual selection of this flag is time-consuming, prone to error, and inconsistent due to differing interpretation methods across the industry. The purpose of this study is to demonstrate an automated process to identify accurate and consistent ISIP events in a high-frequency time-series data set using machine learning algorithms.
This study is based on the analysis of metered high-frequency fracturing treatment data from wells landed in different formations across North America coupled with supervised machine learning algorithms. The pumping data includes treating pressure and slurry rate for 870 stages from the Wolfcamp, Bone Spring, Granite Wash, Barnett, Meramec, Niobrara, Codell, Bakken, Three Forks, Haynesville, Bossier, Caney, and Marcellus formations, for a total of over 7 million rows of data per channel. Eighty percent of the data is used to train the model, seven percent is used for validation, and the remaining thirteen percent forms the test set used for the final evaluation. To allow the algorithm to run leaner, the dataset was pre-processed using smoothing techniques, and the rate of change of the main data channels were added. The selected algorithm, an artificial neural network (ANN), was trained to recognize and isolate the necessary data from the treating plot that will be used to predict the ISIP. Once the data is isolated, a filter is used to extract the portion of the data to be used. A second machine learning algorithm, linear regression, is then applied to the portion of extracted data to predict the ISIP value when the slurry rate is equal to zero.
Classification techniques were used to generate an accurate suggestion of the reduced dataset needed to recognize the ISIP event in a high-frequency treating plot. The neural network achieved a classification accuracy (on the training and validation sets) of approximately 98 percent when isolating the target region. The subsequent ISIP predictions from the linear regression on the test set had an average accuracy of +/- 50 psi when compared to the manually picked values. Considering that the typical range for ISIP values is between 2,500 psi and 9,000 psi, 50 psi represents a 0.5% to 2% error. A limitation of this method is that it requires periodic re-training with new field data to improve the prediction robustness and to maintain high accuracy.
Automatically labeling relevant regions of high-frequency hydraulic fracturing treatment plots using classification techniques can lead to simple and effective procedures for identifying events of interest. Accurate flag selection makes processing large volumes of fracture treatment data viable and significantly reduces the time spent reviewing field data for quality control. The method will also allow rapid reprocessing of historical data. The benefits of using simple (and accurate) models include ease of deployment, ease of debugging, and extremely fast prediction and re-training (updating the model).
Improved completion design and field development strategies have provided commodity price resilience by sustained efficiency gains across most major US Shale plays. This rapid evolution in completion practices, however, has created behind pipe opportunities. Refracturing offers a viable solution to maximize on these opportunities, however, its effectiveness is dependent on a variety of factors. The present paper explores the implementation of refracturing as a re-development strategy in legacy shale plays and evaluates it as a truly multivariable problem.
The paper takes into consideration petrophysical parameters, initial completion design, chemical composition, formation quality, time from original completion, refrac completion design and production performance to quantify impact on refrac KPIs such as IP ratio, EUR ratio, decline trend impact, amongst others. The paper does this by using an ACE (alternating conditional expectation) non-linear regression model that incorporates the KPI’s as response variables and utilizes the transforms of a wide range of input variables to identify cause and effect relationships. By running this analysis across multiple legacy shale plays, including the Haynesville, and Barnett, the paper provides best-practices to maximize refracturing success.
While refrac can offer a viable solution in obtaining incremental production, depending on the basin, a refrac can be a tenth of the expense of a new well and can beneficially impact the production from the existing well. In most cases, the analysis found EUR predictions improved by 30% - 200%. While correlations varied across basins and completion design, an inverse correlation was found between refrac KPIs and initial frac intensity.
Although, refracturing in horizontal shale wells is a well-established practice, a significant amount of analysis on their performance is focused on one or two key variables. The present paper adds to the existing body of literature by using data analytics and machine learning to evaluate this strategy from a truly multivariable standpoint. The paper also provides best practices to evaluate and predict refrac performance to de-risk refrac as a field re-development strategy.
Morales, Adrian (Chesapeake Energy Corp.) | Holman, Robert (Chesapeake Energy Corp.) | Nugent, Drew (Chesapeake Energy Corp.) | Wang, Jingjing (Chesapeake Energy Corp.) | Reece, Zach (Chesapeake Energy Corp.) | Madubuike, Chinomso (Chesapeake Energy Corp.) | Flores, Santiago (Chesapeake Energy Corp.) | Berndt, Tyson (Chesapeake Energy Corp.) | Nowaczewski, Vincent (Chesapeake Energy Corp.) | Cook, Stephanie (Chesapeake Energy Corp.) | Trumbo, Amanda (Chesapeake Energy Corp.) | Keng, Rachel (Chesapeake Energy Corp.) | Vallejo, Julieta (Chesapeake Energy Corp.) | Richard, Rex (Chesapeake Energy Corp.)
An integrated project can take many forms depending on available data. As simple as a horizontally isotropic model with estimated hydraulic fracture geometries used for simple approximations, to a large scale seismic to simulation workflow. Presented is a large-scale workflow designed to take into consideration a vast source of data.
In this study, the team investigates a development area in the Eagle Ford rich in data acquisition. We develop a robust workflow, taking into account field data acquisition (seismic, 4D seismic and chemical tracers), laboratory (geomechanical, geochemistry and PVT) measurements and correlations, petrophysical measurements (characterization, facies, electrical borehole image), real time field surveillance (microseismic, MTI, fracture hit prevention and mitigation program through pressure monitoring) and finally integrating all the components of a complex large scale project into a common simulation platform (seismic, geomodelling, hydraulic fracturing and reservoir simulation) which is used to run sensitivities.
The workflow developed and applied for this project can be scaled for projects of any size depending on the data available. After integrating data from various disciplines, the following primary drivers and reservoir understanding can be concluded. At a given oil price, optimum well spacing for a given completion strategy can be developed to maximize rate of return of the project. Many operators function in isolated teams with a genuine effort for collaboration, however genuine effort is not enough for a successful integrated modelling project, a dedicated multidisciplinary team is required.
We present what is to our knowledge, one of the most complete data sets used for an integrated modelling project to be presented to the public. The specific lessons from the project are applied to future Eagle Ford projects, while the overall workflow developed can be tailored and applied to any future field developments.
Zafar is a strategy consultant with Accenture and is based out of Mumbai. Before Accenture, he worked for 5 years at Halliburton designing drill bits for oil and gas companies in South Asia. He has been a volunteer with TWA since 2013 supporting multiple sections prior to transitioning to a leadership role in 2018. He is a keen technophile, an avid debater, and a passionate Toastmaster. He has participated in and won several public speaking and debate competitions. His hobbies include running, collecting key-rings, building robots, and keeping abreast of global geopolitics. Kristin Cook is the Advisor to TWA. She is an MS candidate in Energy and Earth Resources at the University of Texas at Austin. Her interests include energy policy, oil and gas project development, and energy security and geopolitics. Prior to starting graduate school, Cook worked for 5 years as a production engineer in the San Juan Basin, a natural gas field in northwestern New Mexico.
Polymers are used to viscosify the fluid. Crosslinkers are used to change the viscous fluid to a pseudoplastic fluid. Biocides are used to kill bacteria in the mix water. Buffers are used to control the pH of the fracture fluid. Surfactants are used to lower the surface tension. Fluid-loss additives are used to minimize fluid leakoff into the formation. Stabilizers are used to keep the fluid viscous at high temperature. Breakers are used to break the polymers and crosslink sites at low temperature.
Zhan, Lang (Shell International Exploration and Production) | Tokan-Lawal, Adenike (Shell International Exploration and Production) | Fair, Phillip (Shell International Exploration and Production) | Dombrowski, Robert (Shell International Exploration and Production) | Liu, Xin (Shell International Exploration and Production) | Almarza, Veronica (Shell Exploration and Production Company) | Girardi, Alejandro (Shell Exploration and Production Company) | Li, Zhen (Shell Exploration and Production Company) | Li, Robert (Shell Exploration and Production Company) | Pilko, Martin (Shell Exploration and Production Company) | Joost, Noah (Shell Exploration and Production Company)
Hydraulic fractures play a central role in performance of multi-stage fractured horizontal wells (MFHW) in tight and shale reservoirs. Fracture conductivity variations and connection quality between fractures and wellbore (i.e. the choking skin) strongly affect well productivity. However, convincing and high-quality evaluation of hydraulic fractures for these reservoirs is scarce in literature because quantifying the fracture properties requires de-coupling them from fracture geometry and formation properties, which is difficult in most field conditions. A data gathering and hypothesis testing program was implemented using six multi-fractured horizontal wells in a pad in Delaware basin to improve our ability to reliably forecast well performance. A systematic approach utilizing production, shut ins, and bottom-hole pressure measurements (BHP) was conducted and used to evaluate the apparent flow capacity of hydraulic fractures. Two independent techniques were used in the data analyses. Pressure transients for individual wells and significant well-to-well interference signals are used to characterize the hydraulic fractures, respectively. Both techniques render similar decline rate interpretations for the sets of fracture conductivity/permeability from analysis of the pressure data, but the uncertainty of the estimated results from these two methods have large difference.
The first method used the radial-linear flow regime in successive pressure buildups in three of the six wells. Simulations and theoretical analysis show that this flow regime allows de-coupling fracture conductivity from fracture geometry and matrix properties. This flow regime yields the total apparent fracture conductivity (TAFC), which represents the lump sum effect of fracture conductivity. In addition, this technique characterizes the connection condition between the dominant fractures and bore-hole, which can be estimated from the early derivative horizontal line in pressure transient log-log diagnostic plot with minimum assumptions. Specifically, the estimated total apparent fracture conductivity ranges from 1140 – 1630 md*ft at early time of well life to 525 – 855 md*ft after 100 – 139 days in production, or about 45% to 61% reduction among these wells.
The second method uses time-lag of pulse interference response between an active and an observation well. With assumptions of low, mid, and high values of fracture porosity, fracture compressibility and fluid viscosity, characteristic fracture permeability can be estimated. Because of the large uncertainty related to the assumed fracture porosity and fracture compressibility, the pulse interference method is not likely to deliver the same certainty range as successive pressure buildups using the radial-linear flow regime.
The results of this work provide better understanding of the mechanisms of flow transport inside hydraulic fractures and at the connection between hydraulic fractures and wellbore. The estimated TAFC and its significant decline help improve hydraulic fracturing designs and build representative reservoir models for more reliable well performance modeling and forecasting.
Gao, Jia Jia (Department of Civil & Environmental Engineering, National University of Singapore) | Lau, Hon Chung (Department of Civil & Environmental Engineering, National University of Singapore) | Sun, Jin (Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences)
Conventional drilling design tends to inaccurately predict the mud density needed for borehole stability because it assumes that the porous medium is fully saturated with a single fluid while in actuality it may have two or more fluids.
This paper provides a new semi-analytical poroelastic solution for the case of an inclined borehole subjected to non-hydrostatic stresses in a porous medium saturated with two immiscible fluids, namely, water and gas. The new solution is obtained under plane strain condition. The wellbore loading is decomposed into axisymmetric and deviatoric cases. The time-dependent field variables are obtained by performing the inversion of the Laplace transforms. Based on the expansion of Laplace transform solution, we derive the unsaturated poroelastic asymptotic solutions for early times and for a small radial distance from an inclined wellbore. The model is verified by analytical solutions for the limiting case of a formation saturated with a single fluid. The impact of unsaturated poroelastic effect on pore pressure, stresses and borehole stability is investigated.
Our results show that the excess pore pressure due to the poroelastic effect is generally higher for the saturated case than the unsaturated case due to the large difference between the compressibility of fluid phases. The time-dependency of the poroelastic effect causes the safe mud pressure window of both the unsaturated and saturated cases to narrow with increasing time with the unsaturated case giving a narrower safe mud pressure window. Furthermore, this window narrows with increasing initial gas saturation. The commonly used assumption that the formation is fully saturated by one fluid tends to be conservative in predicting the mud density required for borehole stability.
This new semi-analytical poroelastic solution enables the drilling engineer to more accurately estimate the time-dependent stresses and the pore pressure around a borehole, thus allowing him to design the mud weight to ensure borehole stability.
The primary purpose of using traditional friction reducers in stimulation treatments is to overcome the tubular drag while pumping at high flow rates. Hydraulic fracturing is the main technology used to produce hydrocarbon from extremely low permeability rock. Even though slickwater (water fracturing with few chemical additives) used to be one of the most common fracturing fluids, several concerns are still associated with its use, including usage of freshwater, high-cost operation, and environmental issues. Therefore, current practice in hydraulic fracturing is to use alternative fluid systems that are cost effective and have less environmental impact, such as fluids which utilize high viscosity friction reducers (HVFRs), which typically are high molecular weight polyacrylamides. This paper carefully reviews and summarizes over 40 published papers, including experimental work, field case studies, and simulation work. This work summarizes the most recent improvements of using HVFR’s, including capability of carrying proppant, reducing water and chemical requirements, its compatibility with produced water, and environmental benefits in hydraulic fracturing treatments. A further goal is to gain insight into the effective design of HVFR based fluid systems.
The findings of this study are analyzed from over 26 field case studies of many unconventional reservoirs. In comparing to the traditional hydraulic fracture fluids system, the paper summaries many potential advantages offered by HVFR fluids, including: superior proppant transport capability, almost 100% retained conductivity, cost reduction, minimizing chemicals usage by 50%, less operating equipment on location, reducing water consumption by 30%, and fewer environmental concerns. The study also reported that the common HVFR concentration used was 4gpt. HVFRs were used in the field at temperature ranges from 120°F to 340°F. Finally, this work addresses up-to-date challenges and emphasizes necessities for using high viscosity friction reducers as alternative fracture fluids.
Ely, John W. (Ely & Associates Corp) | Harper, Jon (Ely & Associates Corp) | Nieto, Esteban N. (Ely & Associates Corp) | Kousparis, Dimitrios (Paris Oil and Gas Corporation) | Kousparis, Andrew (Paris Oil and Gas Corporation) | Crumrine, Curt (W.B. Osborne Oil and Gas Corporation)
The Northern extension of the "COMBO" Barnett Shale is located primarily in Montague, Cooke, and Clay counties in the North Texas region. This play is unique in that the shale in the area is very rich in total organic content (TOC) and contains a relatively high concentration of carbonates throughout. This extension is primarily inside the the oil window of the Barnett, rather than predominately within the more gas-rich region, which dominates the rest of the shale's development throughout North Texas (See