McClure, Mark (ResFrac Corporation) | Bammidi, Vidya (Keane Group) | Cipolla, Craig (Hess Corporation) | Cramer, Dave (ConocoPhillips Company) | Martin, Lucas (Formerly with Apache Corporation, now with Marathon Oil Company) | Savitski, Alexei (Shell International Exploration and Production Inc.) | Sobernheim, Dave (Keane Group) | Voller, Kate (Range Resources Corporation)
This paper summarizes findings from a one-year study sponsored by seven operators and service companies to investigate interpretation of diagnostic fracture injection tests (DFIT’s). The study combined computational modeling, a diverse collection of field data, and operator experience. DFIT simulations were performed with a three-dimensional hydraulic fracturing, wellbore, and reservoir simulator that describes fracture propagation, contacting of the fracture walls, and multiphase flow. Interpretation procedures were applied to estimate stress, permeability, and pressure from the synthetic data. The interpretations were compared to the simulation input parameters to evaluate accuracy. Based on the results, new techniques were developed, existing techniques were refined, and an overall interpretation protocol was developed. The techniques were applied to interpret over thirty field DFIT’s drawn from shale plays across the US and Canada, and the methods were evaluated in the context of operator experience. The results are applicable to fracturing tests in formations with permeability ranging from nanodarcies to 10s of microdarcies. The minimum principal stress is estimated by identifying the ‘contact pressure’ when the fracture walls come into contact, causing fracture compliance and system storage coefficient to decrease. After the walls come into contact, the pressure transient is controlled by the interplay of changing fracture compliance, deviation from Carter leakoff, and multiphase flow. The contact pressure is slightly greater than the minimum principal stress. It can be identified from either a plot of dP/dG or a relative stiffness plot. Permeability is estimated using the G-function method, a newly developed h-function method that accounts for deviation from Carter leakoff, and impulse linear flow. These three methods, which are based on linear flow geometry, require an estimate of fracture area. We derive equations for estimating area using mass balance equations, accounting for wellbore storage and fluid leakoff. The results from field data show that impulse linear permeability estimates are usually 2-5 times lower than estimates derived from the G-function and h-function methods, apparently indicating a difference between effective permeability during leakoff and permeability during flow of reservoir fluid through the formation. Impulse radial flow regime may be used for estimating permeability, but should be used with caution. Simulation results indicate that a variety of processes can cause an apparent radial trend that is not actually radial flow. Simulations and field data indicate that ‘false radial’ is very common in gas reservoirs and, if applied, leads to a large overestimate of permeability. Production history matching using overestimated permeability will underestimate fracture length, potentially resulting in suboptimal choices for well and cluster spacing.
The reporting of potential resources is essential to assess the future development plan and profitability of a petroleum discovery, but if the project is under appraised and production data are absent, analysts often use analogs for preliminary estimates of technically recoverable volumes. To address this, a workflow is presented for selecting appropriate analogs for unconventional plays and using them to estimate the target play's potential. The proposed technique is demonstrated with a case study of the as-yet undeveloped Bowland Shale, which is the most prominent of the shale plays in the United Kingdom (UK) and is at the early stage of its assessment. The paper describes the current shale gas activity in the UK, highlighting the enviromental constraints placed on would-be Bowland Shale developers, which impact on drilling and production operations and stem from the geographic proximity of urban developments, infrastructure and nature, which limit the size of well pad footprint in the UK where land use is high. Studies have estimated the play's in-place resources for possible future development, but there are few estimates of its corresponding recoverable volumes due to lack of production history. At the outset, a database is created with published minimum-average-maximum ranges of key parameters such as total organic carbon, maturity level, gas filled porosity, permeability, etc. that play a major role in resources estimation and recovery potential for all unconventional plays. A comparison of triangular distributions, key parameter by key parameter, between the target shale play and the analog database, is then carried out using novel graphical and statistical methods to establish a "confidence factor" relating to the analog's viability. The most appropriate analog for the Bowland Shale is chosen from an exhaustive list of North American shale gas plays. Analytical approaches are then used to transform a model of the published type well performance of the selected analog by exchanging key model parameters with those of the target shale play. The paper shows how UK operational constraints can be statistically incorporated into the workflow and have a marked effect on the estimated recovery from the Bowland Shale.
From the beginning, the name of the game has been innovation. No single word has characterized drilling design and operations more completely during the 160 years since Colonel Drake first probed the Pennsylvania landscape for oil. This fundamental aspect of our business applies now more than ever across geographical and corporate boundaries. Examples of evolution in well construction during the past several years include new horizontal-well applications, breakthroughs in bit and directional-drilling technology, synthetic fluids, fracture-stimulation advancements, managed-pressure drilling, and the digital revolution. All this being said, few could have imagined the present state of the industry unfolding with the development of unconventional resources.
Recio, Antonio (Halliburton Energy Services) | Benoit, Denise (Halliburton Energy Services) | Potty, Ajish (Halliburton Energy Services) | Sun, Jianlei (Halliburton Energy Services) | Henkel, Kristina (Halliburton Energy Services)
This paper describes the development of a highly automated apparatus and customized software package to rapidly evaluate the performance of surfactant additives in dry gas shale reservoirs. A major challenge throughout the industry is the ability to reduce water saturation resulting from fluid leakoff into the formation matrix during stimulation operations. The new method presented in this paper to help identify the optimum surfactant for reducing post-treatment water saturation based on well-specific parameters. Conventional laboratory evaluation of stimulation fluid additives typically involves coreflow studies, which are excessively time consuming and have poor reproducibility as a result of core-to-core inconsistencies. The focus of this endeavor was to develop a statistically relevant method that can use drill cuttings samples and measures surfactant additive performance data with high confidence and reproducibility for the tested formation material.
Data analysis included analysis of variance (ANOVA) followed by post-hoc Tukey honest significant difference (HSD) range testing. Test apparatus results were also corroborated with coreflow studies. Eight surfactant additives were evaluated in the presence of four different fracture fluid formulations and formation samples. For each surfactant/fracturing fluid/formation test matrix, the software was able to rank surfactants performance based on the volume of fracturing fluid displaced from a column pack normalized to the pressure gradient. No individual surfactant performed best more than 40% of the time within this test series, and the surfactant-laden formulations always statistically outperformed the nonsurfactant control. The results imply that the addition of surfactants results in increased treatment fluid load recovery. Reservoir simulations were performed to investigate the effects of increased load recovery and depth of invasion of fracturing fluids on hydrocarbon production. The simulation results confirmed the assumption that minimal invasion of treatment fluid into the matrix of the formation resulting from increased load recovery does improve hydrocarbon production. The simulation data also suggest this observed hydrocarbon production improvement is particularly prevalent in the early time/cleanup period of the life of the well.
A key feature and novelty of the apparatus is the ability to evaluate numerous surfactants in series and the potential to perform up to 24 individual tests in an 8-hour shift. The results presented in this paper showcase the utility of the newly developed apparatus, which offers a new method for rapid customization of stimulation fluids.
It is common in unconventional plays to have offset wells with very different productivity, even though these wells were drilled at the same time, in the same landing zone and with the same completion design. Such well behaviour is always puzzling because subsurface properties are not expected to vary significantly at a small scale.
This problem has been identified in several pads in the Utica play. To try to understand this phenomena, a geological and statistical analysis has been performed on more than 400 wells and 7000 stages. The results show that differences between offset wells occur mainly when the two wells have their stages placed in slightly different facies. More precisely, we show that within a 40 feet thick landing zone, stages can be placed in 3 types of facies: (a.) facies A with a gamma-ray (GR) of ~70°API (~40% Vclay), (b.) facies B with a GR of ~60°API (~20% Vclay) and (c.) Facies C with a GR of ~50°API (~5% Vclay). Generally, for a given well, if more than 50% of its stages are in facies A, the production is 15% lower than a well with no stages in facies A.
Analysis of pressure data from completion indicate that the productivity decrease originates from limited fractures propagations when the completion is initiated in the clay-rich facies. Stages completed in facies A show a high near well-bore pressure loss and a low net pressure, which is consistent with the notion of shale choke, where fracture propagation is limited to the near well-bore. On the contrary, stages placed in the brittle facies C show high net pressures and low near well bore pressure losses, consistent with well- developed fracture geometry in the far-field. This difference in hydraulic fracture geometry could explain the difference in production between two neighboring wells.
Such results are important because it shows that stage placement is critical to productivity, even when the well has been accurately geosteered in the target zone. Optimizing the completion design by accounting for the heterogeneities should therefore significantly improve productivity and guide operation strategy.
Recent drilling and hydraulic fracturing activities in the Utica-Point Pleasant shale play have recorded total measured depth of over 27,000 feet a record for the longest onshore well in the United States (
One immediate solution to the current low energy prices is optimizing well spacing to enhance hydrocarbon recovery and, thus, the commercial feasibility of the project. Horizontal well spacing constitutes a fundamental parameter for the success of a shale-drilling venture. Determining the optimum horizontal well spacing in shale reservoirs represents a challenging task because of the complexity of controlling factors. These factors can be categorized into three groups: geological, engineering, and economic.
Geological modeling and reservoir simulation are the standard tools utilized in the industry to integrate these controlling factors. In this study, we employed these tools to perform sensitivity analysis of reservoir characteristics and future production optimization for a deep drilling case study in the Utica-Point Pleasant formations. We sought to find the optimum horizontal well spacing scenario as well as hydraulic fracturing design, in order to attain the highest net present value (NPV) for 50 years of gas production. Our reservoir model represented a portion of Utica-Point Pleasant formations at the depth of 13,000 feet and the dry gas window. A commercial reservoir simulator was coupled with an optimization algorithm to reach the best solution with a minimum simulation cost. In addition, we developed a smart proxy based on artificial neural networks (ANNs) for fast analysis of estimated ultimate recovery (EUR) and NPV. Although the outcome of our study is subjective to the chosen asset, the workflow provides a good example of horizontal well spacing and hydraulic fracturing design optimization as well as a simple and fast technology to predict the critical parameters.
Managers, geologists, reservoir and completion engineers are faced with important challenges and questions when it comes to producing from and operating shale assets. Some of the important questions that need to be answered are: What should be the distance between wells (well spacing)? How many clusters need to be included in each stage? What is the optimum stage length? At what point we need to stop adding stages in our wells (what is the point of diminishing returns)? At what rate and at what pressure do we need to pump the fluid and the proppant? What is the best proppant concentration? Should our completion strategy be modified when the quality of the shale (reservoir characteristics) and the producing hydrocarbon (dry gas, vs. condensate rich, vs. oil) changes in different parts of the field? What is the impact of soak time (starting production right after the completion versus delaying it) on production?
Shale Analytics is the collection of the state of the art data driven techniques including artificial intelligence, machine learning, and data mining that addresses the above questions based on facts (field measurements) rather than human biases. Shale Analytics is the fusion of domain expertise (years of geology, reservoir, and production engineering knowledge) with data driven analytics. Shale Analytics is the application of Big Data Analytics, Pattern Recognition, Machine Learning and Artificial Intelligence to any and all Shale related issues. Lessons learned from the application of Shale Analytics to more than 3,000 wells in Marcellus, Utica, Niobrara, and Eagle Ford is presented in this paper along with a detail case study in Marcellus Shale.
The case study details the application of Shale Analytics to understand the impact of different reservoir and completion parameters on production, and the quality of predictions made by artificial intelligence technologies regarding the production of blind wells. Furthermore, generating type curves, performing "Look-Back" analysis and identifying best completion practices are presented in this paper. Using Shale Analytics for re-frac candidate selection and design was presented in a previous paper [
Halite scale is a wide spread problem throughout several basins in the United States. This scale can form in surface equipment, downhole tubulars as well as affecting production. Traditional remediation of halite can be accomplished by dissolving the scale in fresh water as well as recycled water. In most cases the operator must factor in the cost of fresh water, trucking, manpower, anti-scale additives, and disposal of additional produced water. These treatments are often frequent with multiple applications per week.
The approach described in this paper will prevent the formation of halite scale for a given period of time. This is accomplished through the use of a new porous ceramic proppant-based chemical delivery system in which a halite inhibitor is infused. The infused halite inhibitor is encapsulated with a semi-permeable membrane to regulate the elution rate of the inhibitor from the porous proppant carrier. The chemical delivery system is added to the bulk proppant as a small weight percentage of the bulk proppant and is placed in the fracture as normal proppant.
Several wells in the multiple basins for several E&P companies were completed using this new chemical delivery system, which allowed for a significant amount of halite inhibitor to be placed within the proppant pack. As fluids flowed over the proppant pack the halite inhibitor was slowly released. This paper intends to describe the mechanism for which the inhibitor acts, the control release mechanism of the substrate and the engineering behind the placement and volumes of the halite infused proppant. This paper will also discuss the data collected from laboratory modeling and the implementation of these products in fracturing applications. The use of this chemical delivery system will allow these operators to defer remediation, lowering lease operating expenses.
This paper will be useful to all production and completions engineers and technicians operating in an area with halite scale issues. This new chemical delivery system allows for deferred implementation of traditional remediation strategies while extending the most productive time of the wells life. This halite inhibitor delivery system not only improves estimated ultimate recovery but also lowers lease operating expenses.
The Dry Utica play is an exciting unconventional gas development currently unfolding in the Appalachian Basin. Published results for several wells exceed an average Initial Production (IP) rate of 60 MMcf/day. However, complexities in the reservoir can make the developmental learning curve steep. Challenges include true vertical depths (TVDs) of 9,000 to 13,500 feet, pore pressures of 0.8 to 0.99 psi/ft, and bottom hole temperatures of up to 240 degrees Fahrenheit. In addition, the reservoir has high stresses, high closure pressures, complex and varying mineralogies. Among the greatest challenges in Dry Utica field development is cost effective proppant and frac fluid design and selection. In order to achieve an adequate return on investment: Proppant design has to be optimized to withstand high pore and closure pressures and overall high stresses, but also be cost effective. Frac fluid design has to be compatible with varying mineralogies to avoid a steep decrease in fracture conductivity.
Proppant design has to be optimized to withstand high pore and closure pressures and overall high stresses, but also be cost effective.
Frac fluid design has to be compatible with varying mineralogies to avoid a steep decrease in fracture conductivity.
This paper discusses field testing of proppant design and selection and how cost, geological, reservoir, and rock properties affect the completion design and well production. The paper will also review frac fluid design used for proppant transportation and placement, and potential issues with formation mineralogies, as well as mitigation. Field case histories with managed production draw down and how that can affect proppant inside a fracture will also be reviewed.