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Abstract Characterization of hydraulic fracture system in multi-fractured horizontal wells (MFHW) is one of the key steps in well spacing optimization of tight and shale reservoirs. Different methods have been proposed in the industry including core-through, micro-seismic, off-set pressure data monitoring during hydraulic fracturing, pressure depletion mapping, rate-transient analysis, pressure-transient analysis, and pressure interference test. Pressure interference test for a production and monitoring well pair includes flowing the production well at a stable rate while keeping the monitoring well shut-in and recording its pressure. In this study, the coupled flow of gas in hydraulic fractures and matrix systems during pressure interference test is modeled using an analytical method. The model is based on Laplace transform combined with pseudo-pressure and pseudo-time. The model is validated against numerical simulation to make sure the inter-well communication test is reasonably represented. Two key parameters were introduced and calculated with time using the analytical model including pressure drawdown ratio and pressure decline ratio. The model is applied to two field cases from Montney formation. In this case, two wells in the gas condensate region of Montney were selected for a pressure interference test. The monitoring well was equipped with downhole gauges. As the producing well was opened for production, the bottom-hole pressure of the monitoring well started declining at much lower rate than the production well. The pressure decline rate in the monitoring well eventually approached that of the producing well after days of production. This whole process was modeled using the analytical model of this study by adjusting the conductivity of the communicating fractures between the well pairs. This study provides a practical analytical tool for quantitative analysis of the interference test in MFHWs. This model can be integrated with other tools for improved characterization of hydraulic fracture systems in tight and shale reservoirs.
Brinkley, Kourtney (Devon Energy) | Ingle, Trevor (Devon Energy) | Haffener, Jackson (Devon Energy) | Chapman, Philip (Devon Energy) | Baker, Scott (Devon Energy) | Hart, Eric (Devon Energy) | Haustveit, Kyle (Devon Energy) | Roberts, Jon (Devon Energy)
Abstract This case study details the use of Sealed Wellbore Pressure Monitoring (SWPM) to improve the characterization of fracture geometry and propagation during stimulation of inter-connected stacked pay in the South Texas Eagle Ford Shale. The SWPM workflow utilizes surface pressure gauges to detect hydraulically induced fracture arrivals athorizontal monitor locations adjacent to the stimulated wellbore (Haustveit et al. 2020). A stacked and staggered development in Dewitt County provided the opportunity to jointly evaluateprimary completion and recompletion efforts spanning three reservoir target intervals. Fivemonitor wells at varying distances across the unit were employed for SWPM during the stimulation of four wells. An operational overview, analysis of techniques, correlation with seismic attributes, image log interpretations, and fracture model calibration are provided. Outputs from this workflow allow for a refined analysis ofthe overall completion strategy. The high-density, five well monitor array recorded a total of 160 fracture arrivals at varying vertical and lateral distances, with far-field fracture arrivalsprovidingsignificant insight into propagation rates and geometry. Apronounced trend occurred in both arrival frequency and volumes pumped as monitor locations increased in distance from the treatment well. Specific to target zone isolation, it was identified that traversing vertically in section through a high stress interval yielded a 30% reduction inarrival frequency. An indirect relationship between horizontal distance and arrival frequency was also observed when monitoring from the same interval. A decrease in fracture arrivals from 70% down to 8% was realized as offset distance increased from 120 to 1,700 ft. The results from this study have proven to be instrumental in guiding interdisciplinary discussion. Assessing fracture geometry and propagation during stimulation, particularly in the co-development of a stacked pay reservoir, is paramount to the determination of proper completion volume, perforation design, and well spacing. Leveraging the observations of SWPM ultimately provides greater confidence in field development strategy and economic optimization.
Guo, Yifei (The University of Texas at Austin) | Ashok, Pradeepkumar (The University of Texas at Austin) | van Oort, Eric (The University of Texas at Austin) | Patterson, Ross (Hess Corporation) | Zheng, Dandan (Hess Corporation) | Isbell, Matthew (Hess Corporation) | Riopelle, Austin (Marathon Oil Corporation)
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.
Dontsov, Egor (ResFrac Corporation) | Suarez-Rivera, Roberto (W. D. Von Gonten Laboratories) | Panse, Rohit (W. D. Von Gonten Laboratories) | Quinn, Christopher (W. D. Von Gonten Laboratories) | LaReau, Heather (BP America Production Company, BPx Energy Inc.) | Suter, Kirke (BP America Production Company, BPx Energy Inc.) | Hines, Chris (BP America Production Company, BPx Energy Inc.) | Montgomery, Ryan (BP America Production Company, BPx Energy Inc.) | Koontz, Kyle (BP America Production Company, BPx Energy Inc.)
Abstract As the number of wells drilled in regions with existing producing wells increases, understanding the detrimental impact of these by the depleted zone around parent wells becomes more urgent and important. This understanding should include being able to predict the extent and heterogeneity of the depleted region near the pre-existing wells, the resulting altered stress field, and the effect of this on newly created fractures from adjacent child wells. In this paper we present a workflow that addresses the above concern in the Eagle Ford shale play, using numerical simulations of fracturing and reservoir flow, to define the effect of the depletion zone on child wells and match their field production data. We utilize an ultra-fast hydraulic fracture and depletion model to conduct several hundred numerical simulations, with varying values of permeability and surface area, seeking for cases that match the field production data. Multiple solutions exist that match the field data equally well, and we used additional field production data of parent-child well-interaction, to select the most plausible model. Results show that the depletion zone is strongly non-uniform and that large reservoir regions remain undepleted. We observe two important effects of the depleted zone on fractures from child wells drilled adjacent to the parents. Some fractures propagate towards low pressure zones and do not contribute to production. Others are repelled by the higher stress region that develops around the depletion zone, propagate into undepleted rock, and have production rates commensurate to that from other child wells drilled away from depleted region. The observations are validated by the field data. Results are being used to optimize well placement and well spacing for subsequent field operations, with the objective to increase the effectiveness of the child wells.
US shale producer Chesapeake Energy announced on Wednesday that CEO Doug Lawler is stepping down. The interim chief will be Mike Wichterich who was appointed by the company's creditors as its new chairman upon its exit from bankruptcy in February. "On behalf of the Board of Directors, Chesapeake's employees and its shareholders, I would like to thank Doug for the vision and leadership he provided for the past 8 years. He guided Chesapeake through a difficult period, repositioned Chesapeake's portfolio of assets, and built a corporate culture which will serve as a platform for future success. I firmly believe that the investment thesis supporting Chesapeake is compelling, and my confidence in the renewed strength of the company continues to grow," Wichterich said in a statement.
Abstract Basin-wide heterogeneity of production in unconventional resources creates additional risk in field development planning. In the past few years, several data-driven models have been developed to increase the accuracy in predicting the recovery from shale gas and tight oil wells. However, many of the machine learning methods with so called "black box" approach provide deterministic results. Therefore, understanding the uncertainty associated with different development scenarios would be difficult to obtain. We have investigated the underlying statistical distribution functions that govern the production rates and decline behavior of unconventional wells. Identification and quantification of these distribution functions provide a strong tool to accurately forecast the cumulative production of a large group of wells in an unconventional basin. By understanding the relationship among geologic characteristics of different sections of the asset, and the impact of varying drilling and completion parameters, capital allocation can be done in a more efficient manner. In this paper, we have identified the statistical distribution parameters of decline behavior is a Power Law model. In doing so, we have used unsupervised clustering techniques to find an optimal number of clusters that enable observing well behaved and identifiable underlying distribution functions. Furthermore, we quantified different types of distribution functions in a trial and error workflow to provide a tool for accurately evaluating the impact of varying geologic parameters on the decline behavior of these wells. Our results show that the leading term (or leading coefficient), which also highly correlates with long term cumulative recovery, demonstrates Gamma distribution, while the power degree (or power coefficient) demonstrate Normal distribution. Peak production rate (maximum average daily rate), terminal rate (rate after switch point), and the time of terminal rate occurrence, all demonstrate Log Normal distribution.
Abstract The objective of this study was to perform an integrated analysis to gain insight for optimizing fracturing treatment and gas recovery from Marcellus shale. The analysis involved all the available data from a Marcellus Shale horizontal well which included vertical and lateral well logs, hydraulic fracture treatment design, microseismic, production logging, and production data. A commercial fracturing software was utilized to predict the hydraulic fracture properties based on the available vertical and lateral well logs data, diagnostic fracture injection test (DFIT), fracture stimulation treatment data, and microseismic recordings during the fracturing treatment. The predicted hydraulic fracture properties were then used in a reservoir simulation model developed based on the Marcellus Shale properties to predict the production performance. In this study, the rock mechanical properties were estimated from the well log data. The minimum horizontal stress, instantaneous shut-in pressure (ISIP), process zone stress (PZS), and leak-off mechanism were determined from DFIT analysis. The stress conditions were then adjusted based on the results of microseismic interpretations. Subsequently, the results of the analyses were used in the fracturing software to predict the hydraulic fracture properties. Marcellus Shale properties and the predicted hydraulic fracture properties were used to develop a reservoir simulation model. Porosity, permeability, and the adsorption characteristics were estimated from the core plugs measurements and the well log data. The image logs were utilized to estimate the distribution of natural fractures (fissures). The relation between the formation permeability and the fracture conductivity and the net stress (geomechanical factors) were obtained from the core plugs measurements and published data. The predicted production performance was then compared against production history. The analysis of core data, image logs, and DFIT confirmed the presence of natural fractures in the reservoir. The formation properties and in-situ stress conditions were found to influence the hydraulic fracturing geometry. The hydraulic fracture properties are also impacted by stress shadowing and the net stress changes. The production logging tool results could not be directly related to the hydraulic fracture properties or natural fracture distribution. The inclusion of the stress shadowing, microseismic interpretations, and geomechanical factors provided a close agreement between the predicted production performance and the actual production performance of the well under study.
Abstract As operators shift their focus toward operating within cashflow, understanding the true potential of these unconventional resources is becoming increasingly important. Simultaneously, accurate modeling of EURs in shale wells is becoming increasingly complicated. There are multiple factors at play for this increase in complexity, key amongst them, are well interactions. Well interactions or interference have increased with the concentration of field development in core areas of various basins and have completely changed with production behavior in shale wells. The present paper handles this multi-variable problem by incorporating well design, completion and petrophysical variables in a prediction model. Furthermore, the analysis is presented from a viewpoint of parent, child, parent/child and co-completed wells to accurately understand the variability in the driving factors. Terminal decline rate in shale wells is the decline rate wells settle at once the pressure transient reaches the boundary of the well. At this point, the well transitions to a boundary dominated flow regime and continues to drain from a fixed area. Estimating the rate of terminal decline is critical in accurate EUR modeling because changes in transition point can have a significant impact on production behavior of the well and in-turn EUR. The present paper attempts to predict the transition point using an ACE Non-Linear Regression model which is trained on a large multi-variate dataset. Variables incorporated in this analysis include terminal decline month, gas-oil-ratio based of the first three months of production, horizontal length, oil EUR, proppant per foot, average distance from the base of the producing zone, nearest neighbor mean spacing, and hydrocarbon in-place. In order to determine spacing status and nearest wellbore distances, a segment-wise analytical distance approach was taken. These distances and spacing status flags were incorporated into a multi-variate model in-order to model terminal decline rates. The transformations observed from the model showed high dependence on terminal decline month and oil EUR. However, this was less pronounced in parent/child and child wells. In parent/child and child wells completion metrics and HCIP more significantly influenced production behavior. Specifically, child wells saw a higher dependence on first three-month GOR and lateral length compared to parent/child wells which had a higher dependence on proppant per foot and average distance from the base of the producing formation. Additionally, spacing showed a moderate impact on transition point and associated terminal decline rates, but overall increased spacing caused a delayed transition point and consequently a lower terminal decline rate. Understanding how cause-and-effect relationships between parent and child wells differ offers a unique perspective into production behavior and consequently provides better insights into infill wells placement and production prediction. The present paper offers a unique perspective in looking at a key decline variable, transition point, for shale reservoirs. By using multivariate analysis, it incorporates the incremental complexity of the modeling effort and attempts to provide best practices in understanding the impact on production behavior. Furthermore, by incorporating a segment-wise analytical distance approach to determine spacing, the paper adds to the existing body of literature by providing a new perspective for a well interaction standpoint and defines the cause and effect relationships within.
Fakher, Sherif (Missouri University of Science and Technology) | Elgahawy, Youssef (University of Calgary) | Abdelaal, Hesham (University of Lisbon) | Imqam, Abdulmohsin (Missouri University of Science and Technology)
Abstract Carbon dioxide (CO2) injection in low permeability shale reservoirs has recently gained much attention due to the claims that it has a large recovery factor and can also be used in CO2 storage operations. This research investigates the different flow regimes that the CO2 will exhibit during its propagation through the fractures, micropores, and the nanopores in unconventional shale reservoirs to accurately evaluate the mechanism by which CO2 recovers oil from these reservoirs. One of the most widely used tools to distinguish between different flow regimes is the Knudsen Number. Initially, a mathematical analysis of the different flow regimes that can be observed in pore sizes ranging between 0.2 nanometer and more than 2 micrometers was undergone at different pressure and temperature conditions to distinguish between the different flow regimes that the CO2 will exhibit in the different pore sizes. Based on the results, several flow regime maps were conducted for different pore sizes. The pore sizes were grouped together in separate maps based on the flow regimes exhibited at different thermodynamic conditions. Based on the results, it was found that Knudsen diffusion dominated the flow regime in nanopores ranging between 0.2 nanometers, up to 1 nanometer. Pore sizes between 2 and 10 nanometers were dominated by both a transition flow, and slip flow. At 25 nanometer, and up to 100 nanometers, three flow regimes can be observed, including gas slippage flow, transition flow, and viscous flow. When the pore size reached 150 nanometers, Knudsen diffusion and transition flow disappeared, and the slippage and viscous flow regimes were dominant. At pore sizes above one micrometer, the flow was viscous for all thermodynamic conditions. This indicated that in the larger pore sizes the flow will be mainly viscous flow, which is usually modeled using Darcy's law, while in the extremely small pore sizes the dominating flow regime is Knudsen diffusion, which can be modeled using Knudsen's Diffusion law or in cases where surface diffusion is dominant, Fick's law of diffusion can be applied. The mechanism by which the CO2 improves recovery in unconventional shale reservoirs is not fully understood to this date, which is the main reason why this process has proven successful in some shale plays, and failed in others. This research studies the flow behavior of the CO2 in the different features that could be present in the shale reservoir to illustrate the mechanism by which oil recovery can be increased.
Abstract A common practice in gas-shale reservoir simulation, which arbitrarily increases intrinsic matrix permeability to match the production data, has been proven inefficient and unreliable. Alternatively, accurate estimations of gas apparent permeability (AP) in matrix is desired. This work presents an analytical AP model considering rarefaction in nanopores and coupling experimentally confirmed mechanisms in shale matrix for theoretical completeness. Meanwhile, physical terms in AP model are simplified with semi-empirical correlations for the practicability in large-scale field simulation. Compared with other gas transport models in nanopores, the newly-developed analytical model has been successfully validated against molecular dynamic (MD) simulation, direct simulation Monte Carlo (DSMC), Lattice Boltzmann (LB) simulation, and experimental flux results for five types of gases (i.e., methane, nitrogen, helium, argon, and oxygen) with the minimum deviation. It is observed that analytical models excluding Knudsen diffusion mechanism cannot fully characterize rarefaction effect. Next, Knudsen diffusion cannot be explained as the only underlying mechanism of rarefaction because the mass flux is largely underestimated in transition flow regime. However, the weighted superposition of second-order slip boundary and Knudsen diffusion can provide the satisfactory fitting with data. This work provides an analytical model which not only considers non-negligible multi-physics in shale reservoirs (i.e., rarefaction effect, multilayer adsorption, surface diffusion and confinement effect) but also simplifies non-linear physical terms using semi-empirical linear correlations to facilitate AP calculations in core-scale simulations.