|Theme||Visible||Selectable||Appearance||Zoom Range (now: 0)|
Abstract Market-induced production shut-downs and restarts offer us an opportunity to gather step-rate and shut-in data for pressure transient analysis (PTA) and rate transient analysis (RTA). In this study, we present a unified transient analysis (UTA) to combine PTA and RTA in a single framework. In this new approach continuous production data, step-rate data, shut-in data and re-start data can be visualized and analyzed in a single superposition plot, which can be used to estimate both and infer formation pore pressure in a holistic manner by utilizing all available data. Most importantly, we show that traditional log-log and square root of time plots can lead to false interpretation of the termination of linear-flow or power-law behavior. Field cases are presented to demonstrate the superiority of the newly introduced superposition plot, along with discussion on the calibration of long-term bottom-hole pressure with short-term measurements.
Summary The pressure decline data after the end of a hydraulic fracture stage are sometimes monitored for an extended period of time. However, to the best of our knowledge, these data are not analyzed and are often ignored or underappreciated because of a lack of suitable models for the closure of propped fractures. In this study, we present a new approach to model and analyze pressure decline data that are available in unconventional horizontal wells with multistage, transverse hydraulic fracturing. The methods presented in this study allow us to quantify closure stress and average pore pressure inside the stimulated reservoir volume (SRV) and to infer the uniformity of proppant distribution without additional data acquisition costs. For the first time, field data of diagnostic fracture injection test (DFIT), flowback, and pressure decline of main fracturing stages from the same well are compared and analyzed. We found that the early-time main fracturing stage pressure decline trend is controlled by fracture tip extension, followed by progressive hydraulic fracture closure on the proppant pack, whereas late-time pressure decline reflects linear flow. When DFIT data are not available, pressure decline analysis of a main hydraulic fracturing stage can be a substitution if it can be monitored for an extended period to allow fracture closure on proppants and asperities.
Abstract The pressure decline data after the end of a hydraulic fracture stage is sometimes monitored for an extended period of time (30 minutes to hours). However, this data is not analyzed and often ignored or underappreciated due to a lack of suitable models for closure of propped fractures. In this study, we present a new approach to model and analyze pressure decline data that is available at the end of each plug and perf stage in horizontal wells. The new model, interpretation method and specialized plots presented in this study allow us to quantify closure stress, average pore pressure inside the stimulated reservoir volume (SRV) and normalized fracture stiffness/compliance evolution along the entire horizontal wellbore without additional data acquisition costs. Analysis of field stage-by-stage pressure decline data shows that the interpreted results are consistent with the analysis of DFIT data from an offset well for the same formation. We found that the early-time stage-by-stage pressure decline trend is controlled by progressive hydraulic fracture closure on the proppant pack, while late-time pressure decline reflects linear flow. Thus, the pressure decline rate alone is not a reliable indicator of the productivity or stimulation efficiency of a certain stage. When DFIT data is not available, pressure decline analysis of a main hydraulic fracturing stage can be used even if it can be monitored for a relatively short period of time (1 hour). Most important of all, we show that the slope of pressure derivative on a log-log plot and the normalized fracture stiffness plot can be used to infer the uniformity of proppant distribution.
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.
Quantifying in-situ stress and pore pressure has significant applications in earth sciences and subsurface engineering, such as fault zone studies, underground CO2 sequestration, oil and gas reservoir development, injection into deep wells, and geothermal energy exploitation. The extended leak-off test (XLOT)/ pump-in and flow-back test (PIFB) have been the industry-standard for stress determination during drilling for some time, where drilling mud is injected to create a small fracture in an vertical open-hole below a newly cemented casing. This is followed by a shut-in phase and/or flow-back phase. However, there is still no consensus as regards to which methods should be used to pick closure stress from XLOT/PIFB data, and the influence of drilling mud and near wellbore hoop stress can further complicate the interpretation process. In addition, the risks of formation damage and wellbore integrity issues are also major concerns when executing XLOT/PIFB during high-cost drilling operations.
Diagnostic Fracture Injection Tests (DFIT) is another standard method for estimating in-situ stress and other important reservoir/fracture parameters such as pore pressure and permeability. Such tests can be executed in either open-hole or cased-hole, and even carried out in horizontal wells. In very low permeability reservoirs, it may take several days for fracture closure and weeks to observe the after-closure flow regime. The required shut-in time for DFITs can be extremely long in unconventional reservoirs (weeks or months). In some circumstances, if the reservoir is naturally fractured and its effective permeability is strongly pressure-sensitive during the before-closure period, picking the closure stress in the DFIT data becomes ambiguous.
In this study, we present a new approach to estimate in-situ stress and pore pressure using a Rapid Injection Flow-Back Test (RIFT) in low permeability formations, where the fracture closure process is facilitated via controlled flow-back that is followed by a shut-in period. This significantly shortens the time required to conduct a test that allows us to estimate the in-situ stress and the pore pressure. The time-convolution solution for RIFT is derived by preserving the physics of unsteady-state reservoir flow, elastic fracture mechanics, material balance, and progressive fracture closure. Our new approach not only provides an unambiguous way to estimate in-situ stress (even in naturally fractured formations), but also allows us to estimate pore pressure with data from a test that lasts only a few hours. It also provides to estimate effective fracture volume. Both numerical simulations and field cases are presented to demonstrate the advantages of RFIT, along with a discussion of cautions and the potential pitfalls when designing and executing RIFT.
Summary Estimating reservoir-flow capacity is crucial for production estimation, hydraulic-fracturing design, and field development. Laboratory experiments can be used to measure the permeability of rock samples, but the results might not be representative at a field scale because of reservoir heterogeneity and pre-existing natural-fracture systems. Diagnostic fracture-injection tests (DFITs) have now become standard practice to estimate formation pore pressure and formation permeability. However, in low-permeability reservoirs, after-closure radial flow is often absent and this can result in significant uncertainties in interpreting DFIT data. In addition, the established methods for analyzing DFIT data make two oversimplified assumptions: Carter leakoff and constant fracture compliance (or stiffness) during fracture closure. However, both assumptions are violated during fracture closure; therefore, G-function-based models and subsequent related work can lead to an incorrect interpretation and are not capable of consistently fitting both before- and after-closure data coherently. Moreover, current after-closure analysis relies on classic well-test solutions with a constant injection rate. In reality, a “constant injection rate” does not equal “constant leakoff rate into the formation,” because more than 90% of the injected fluid stays inside the fracture at the end of pumping instead of leaking into the formation. The variable leakoff rate clearly violates the constant-rate boundary condition used in existing well-test solutions. In this study, we extend our previous work and derive time-convolution solutions to pressure-transient behavior of a closing fracture with infinite and finite fracture conductivity. We show that the G-function and the square-root-of-time models are only special cases of our general solutions. In addition, we found that after-closure linear-flow and bilinear-flow analysis can be used to infer pore pressure reliably but fail to estimate other parameters correctly. Most importantly, we present a new approach to history match the entire duration of DFIT data to estimate formation-flow capacity, even without knowing closure stress and the roughness properties of the fracture surface. Our approach adds significant value to DFIT interpretation and uncertainty analysis, especially in unconventional reservoirs where the absence of after-closure radial flow is the norm. Two representative field cases are also presented and discussed.
Zheng, Shuang (The University of Texas at Austin) | Manchanda, Ripudaman (The University of Texas at Austin) | Wang, HanYi (The University of Texas at Austin) | Sharma, Mukul (The University of Texas at Austin)
Abstract Diagnostic Fracture Injection Tests (DFIT) help to estimate various formation and fracture parameters such as closure stress, reservoir permeability, pore pressure, fracture compliance/stiffness and conductivity of un-propped fractures. All of the above require a precise depiction of the fracture closure process for accurate estimation of the various parameters. The fracture closure process is a strong function of the reservoir parameters such as stress, pressure, and permeability. Heterogeneity of these parameters in the reservoir and the nonlinear behavior of fracture closure with respect to fracture width further complicate the analysis of the observed pressure trends recorded during a DFIT. In this work, we discuss the application of a 3-D implicitly integrated poroelastic fracture-reservoir-wellbore model to simulate DFITs. The model is validated by simulating a DFIT for a homogeneous formation for which semi-analytical solutions are available. The surface pressure is implicitly calculated by the integrated model during closure of the fracture. The simulated closure pressure response is analyzed, and the results are compared with specified simulation inputs. Various models are used for interpreting the simulated DFIT response to identify the differences between the interpretation methods and validate the numerical simulation. The numerical model is then used to simulate pressure depletion in a typical unconventional reservoir by a horizontal well with multiple fractures. Our poroelastic model predicts the stress variation in the reservoir induced by depletion. DFIT simulations are then performed in a child well in this asymmetrically depleted environment at various distances from the depleted well. The pressure in the closing fracture is then analyzed to understand the effect of depletion, fracture asymmetry and production duration on the DFIT response. This work for the first time presents the expected DFIT response in a depleted reservoir (with a non-uniform stress and pore pressure distribution) and the best practices for analyzing such data. Such an analysis cannot be performed by any existing analytical methods and requires poroelastic numerical simulations. The impact of key depletion parameters on DFIT interpretation is explored for the first time. The results from this work can be directly applied to interpret DFIT data acquired in child wells to accurately determine reservoir closure stress, pore pressure, reservoir permeability, fracture compliance and fracture conductivity.
Abstract Estimating reservoir flow capacity is crucial for production estimation, hydraulic fracturing design and field development. Laboratory experiments can be used to measure the permeability of rock samples, but the results may not be representative at a field scale because of reservoir heterogeneity and pre-existing natural fracture systems. Diagnostic Fracture Injection Tests (DFIT) have now become standard practice to estimate formation pore pressure and formation permeability. However, in low permeability reservoirs, after-closure radial flow is often absent and this can cast significant uncertainties in interpreting DFIT data. In addition, the established methods for analyzing DFIT data make two oversimplified assumptions: (1) Carter's leak-off and, (2) Constant fracture compliance (or stiffness) during fracture closure. However, both assumptions are violated during fracture closure and this is why G-function based models and subsequent related works can lead to an incorrect interpretation and are not capable of consistently fitting both before and after closure data coherently (Wang and Sharma 2017). Moreover, current after-closure analysis relies on classic well-test solutions with constant injection rate. In reality, a "constant injection rate" does not equal "constant leak-off rate into the formation", because over 90% of the injected fluid stays inside the fracture at the end of pumping, instead of leaking into formation. The variable leak-off rate clearly violates the constant rate boundary condition used in existing well-test solutions. In this study, we extend our previous work and derive time-convolution solutions to pressure transient behavior of a closing fracture with infinite and finite fracture conductivity. We show that G-function and the square root of time models are only special cases of our general solutions. In addition, we found that after-closure linear flow and bilinear flow analysis can only be used to infer pore pressure reliably, but fail to estimate other parameters correctly. Most importantly, we present a new approach to history match the entire duration of DFIT data to estimate formation flow capacity, even without knowing closure stress and the roughness properties of the fracture surface. Our approach adds tremendous value to DFIT interpretation and uncertainty analysis, especially in unconventional reservoirs where the absence of after-closure radial flow is the norm. Two representative field cases are also presented and discussed.
Summary A new method is proposed to estimate the compliance and conductivity of induced unpropped fractures as a function of the effective stress acting on the fracture from diagnostic-fracture-injection-test (DFIT) data. A hydraulic-fracture resistance to displacement and closure is described by its compliance (or stiffness). Fracture compliance is closely related to the elastic, failure, and hydraulic properties of the rock. Quantifying fracture compliance and fracture conductivity under in-situ conditions is crucial in many Earth-science and engineering applications but is very difficult to achieve. Even though laboratory experiments are used often to measure fracture compliance and conductivity, the measurement results are influenced strongly by how the fracture is created, the specific rock sample obtained, and the degree to which it is preserved. As such, the results may not be representative of field-scale fractures. During the past 2 decades, the DFIT has evolved into a commonly used and reliable technique to obtain in-situ stresses, fluid-leakoff parameters, and formation permeability. The pressure-decline response across the entire duration of a DFIT reflects the process of fracture closure and reservoir-flow capacity. As such, it is possible to use these data to quantify changes in fracture conductivity as a function of stress. In this paper, we present a single, coherent mathematical framework to accomplish this. We show how each factor affects the pressure-decline response, and the effects of previously overlooked coupled mechanisms are examined and discussed. Synthetic and field-case studies are presented to illustrate the method. Most importantly, a new specialized plot (normalized system-stiffness plot) is proposed, which not only provides clear evidence of the existence of a residual fracture width as a fracture is closing during a DFIT, but also allows us to estimate fracture-compliance (or stiffness) evolution, and infer unpropped fracture conductivity using only DFIT pressure and time data alone. It is recommended that the normalized system-stiffness plot (NS plot) be used as a standard practice to complement the G-function or square-root-of-time plot and log-log plot because it provides very valuable information on fracture-closure behavior and the properties of fracture-surface roughness at a field-scale, information that cannot be obtained by any other means.
Summary The development of unconventional shale-gas formations in North America with horizontal multifractured wells is mature enough to identify production malpractices and abnormal productivity declines generally observed within 18–24 months of initial production. The primary objective of this study is to address all known causes of these productivity declines and to develop a fully coupled geomechanical/flow simulation model to simulate these production conditions. This model mimics the effect of depletion-induced in-situ stress variations on short-term and long-term productivity by taking into account several phenomena, such as stress-dependent matrix and natural-fracture permeability as well as reduction in hydraulic-fracture conductivity caused by proppant crushing, deformation, embedment, and fracture-face creep. Matrix-permeability evolutions, considering the conflicting effects of non-Darcy flow and compaction, have also been accounted for in this model. Numerical solutions for simplified hydraulic-fracture planar geometries are then obtained by use of a finite-element-method scheme. A synthetic case was defined to investigate the effects of each individual phenomenon on short-term and long-term production. Results show that the combined effects of permeability alterations in matrix and natural fractures as well as conductivity losses in hydraulic fractures may result in substantial cumulative-gas-production loss. The model also reproduces familiar field-observed trends, with lower long-term production corresponding to higher drawdowns. This behavior is attributed to the stress-dependent evolution of reservoir permeability and hydraulic-fracture conductivity. The results show that ignoring the effects of any of the previous phenomena results in overestimation of ultimate recovery. Furthermore, it is shown that proper management of pressure drawdown and the penalty for lower initial production rates in unconventional shale-gas reservoirs can yield substantially higher ultimate recovery. The model is fully versatile and allows modeling and characterization of all widely differing (on a petrophysical level) shale-gas formations as well as proppant materials used for the stimulation treatments. This integrated model can be used for optimization of key parameters during the hydraulic-fracture design, for fine tuning production history matching, and especially as a predictive tool for pressure-drawdown management.