Microseismicity is a physical phenomenon which allows us to estimate the production capability of the well after hydraulic fracturing (HF) in a naturally fractured (NF) reservoir. Some of the microseismic events are reactivations of NFs induced by a direct hit of HF, while others are induced by the fluid leak-off from the previous stages or by elastic waves emitted into the reservoir with hydraulic fracture plane propagation. The former NFs have a chance to be propped there as the latter will not significantly increase their contribution to the production. Identification of such microseismic events helps to reduce uncertainty in the description of fracture network geometry.
Based on inferred data from core analysis NF densities and orientations, we generated multiple realizations of the semi-stochastic Discrete Fracture Network (DFN). In order to constrain them, we used time evolution of microseismic cloud in addition to results of core analysis. Fluid and proppant pumping schedule is used to identify such microseismic events because they should be located close to the pressure diffusion front generated by hydraulic fluid. Events outside of proposed region may be triggered by other factors, such as stress-strain relaxation from other stages and correspondent fractures. In most cases, they are not wide enough to take proppant from the main HF. This approach was used to reduce range of production for DFN realizations.
This workflow is implanted to a 15-stage hydraulic fracture treatment on a horizontal well placed in a siltstone reservoir with intrinsic fractures. The spatio-temporal dynamics of microseismic events are classified into two groups by the front of nonlinear pressure diffusion caused by 3-dimensional hydraulic fracturing, considered as effective and ineffective events. DFNs with only effective microseismicity and with all the induced events are generated. Then, two types of DFN related uncertainties on production are performed to evaluate the impact of filtration. Results of aleatory uncertainty quantification caused by the randomness of DFN modeling indicate the filtered events can generate a production DFN with a more consistent connected fracture area. Moreover, sensitivity analysis caused by lack of accuracy in natural fracture characterization shows the production area of DFN with filtration process is more insensitive to the variation of fracture parameters. Finally, a history match with production data and pressure data indicates this DFN model properly represents the reservoir and completion.
Our methodology characterizes well the conductive fracture network utilizing core data, microseismic data, and pumping schedule. It could restore the true productivity of each fractured stage from a massive microseismic cloud, which helps understand the contribution of fracturing job right after the treatment.
Unconventional shale resources are drilled horizontally following the geologic bed dip upward or downward and completed with multi-stage fracturing to maximize reservoir contact. A recent study in Oklahoma claimed that toe-up (inclined upward) laterals yield the highest production rate and estimated ultimate recovery. The objective of this study is to investigate drilling fluid hydraulics and well control operations in toe-up laterals and compare the results to toe-down laterals.
This study uses a multiphase steady-state hydraulics and a dynamic well control simulator. A hydraulics model was developed and verified with a data from a recently drilled Marcellus shale lateral in Monongalia County, WV in 2015. Static and dynamic pressure profiles were examined at drilling flow rate and at slow pump rate. Further, this research studies gas kick behavior and well control practices for kicks experienced at shallow, middle, and deep zones in the lateral section. Additionally, it considers the impact of operational parameters and influx characteristics on wellbore integrity.
The results of this study showed that the developed hydraulics model successfully predicted the pump pressure with an accuracy of 0.97. Larger kick sizes result in higher pit gain, gas flow rate, choke, and casing shoe pressures in toe-down laterals. In contrast, in toe-up laterals, the higher the kick size, the longer the circulation times with an insignificant impact on the choke and shoe pressures. In toe-up laterals, gas bubbles migrated towards the toe and accumulated in high side pockets. Likewise, choke experienced less pressure, volume, and gas discharge rate for extended periods of time in toe-up laterals. Therefore, higher circulation rates and longer circulation times were essential to flush out the dispersed and trapped gas bubbles. The closer the kick location to the vertical section of the well, the shorter the circulation time needed. However, kicks experienced at the heel resulted in higher pit gain, gas discharge rate, choke pressure, and consequently high casing shoe pressure.
Identifying the consequences of drilling toe-up laterals on hydraulics and well control is crucial for drilling operations. This improves rig and personnel safety and reduces the blowout associated risks. Accordingly, it is critical to verify the well integrity by monitoring surface choke, casing shoe, and constant bottomhole pressures throughout the entire well control operations.
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.
Even though the advances in horizontal drilling and hydraulic fracturing techniques have unlocked the gas contained in Marcellus shale, the quantification of the petrophysical properties remain challenging due to complex nature of the shale. Shale permeability is commonly measured by the unsteady state methods, such as pulse-decay or GRI methods, because the shale has a permeability in nano-Darcy range. The permeability values by determined by these techniques have been found often to have large margin of uncertainty as a result of inconsistent experimental protocols and the complex interpretations methods.
In this study, petrophysical properties of the Marcellus shale core plugs were measured using an innovative laboratory setup, referred to as Precision Petrophysical Analysis Laboratory (PPAL). PPAL is designed to accurately measure the petrophysical properties of ultra-low permeability core plugs under the reservoir conditions. PPAL measurements are performed under steady-state isothermal conditions flow conditions and the analysis of the results do not require complicated interpretations. The key advantage of the PPAL is the capability to measure the permeability and porosity of the shale core plugs under a wide range of confining and pore pressures. In addition, the impact of gas adsorption (or desorption) on the measurements can be monitored. The core plugs used in this study were made available through the Marcellus Shale Energy and Environment Laboratory (MSEEL), a dedicated field laboratory in the Marcellus Shale. MSEEL has been established to undertake field and laboratory research to advance and demonstrate new subsurface technologies and to enable surface environmental studies related to unconventional energy development. The filed site is owned and operated by Northeast Natural Energy, LLC and contains several horizontal Marcellus Shale wells. In addition, a vertical well has been drilled specifically for obtaining core, log, and other data for scientific purposes (science well).
The results of the core plug permeability measurements indicated that that the permeability values decline as the gas (pore) pressure increases. Reliable values of the absolute permeability can be obtained by the application of the double-slippage correction for all pore pressure ranges but more specifically for pore pressures below 900 psia. Klinkenberg correction on the other hand, can only provide reliable values for the absolute permeability when the pore pressures are above 900 psia. The determined absolute permeability values were found to be impacted by the net stress. The analysis stress data with the aid of Walsh plot provided the estimates of the fracture (fissure) closure pressure. The closure pressure was found to be dependent on the absolute permeability.
In-situ stresses and heterogeneity of the formation rock are the dominant factors that influence hydraulic fracturing process. The rheology of frac fluid also significantly affects hydraulic fracturing treatment regarding fracture propagation, proppant transport, formation property alteration, and flow back process. Non-Newtonian CO2 foams stabilized by nanoparticles has been recently studied as a promising frac fluid, which is advanced in less water contents, proppant placement, fast clean, and maintaining conductive channels. For the application of the new frac fluid for unconventional reservoir development, it is critical to investigate fracture propagation and proppant transport using CO2 foams.
This study simulated hydraulic fracturing and proppant transport by viscous gas foams in a horizontal well perforated in Eagle Ford Shale formation of Zavala County, TX. A 3D numerical model was setup with heterogeneous reservoir properties using a commercial fracturing simulator - GOHFER. To represent formation heterogeneity, the rock mechanical properties were derived from well logs including Gamma Ray, Resistivity, Neutron Porosity, and Density Porosity logs, characterized by Young's modulus (3 × 106 ~ 6 × 106 psi), Biot constant (0.6 ~ 0.8), and Poisson's ratio (0.2 ~ 0.4). The flow behavior of CO2 foams stabilized by nanoparticles was characterized by Carreau rhelogy model based on the experimental data. During the pumping schedule for multistage fracturing process, the effects of variable injection rate (20 ~ 40 BPM), CO2 foams quality (50 ~ 80 %), incremental proppant distribution (0 ~ 5 PPA), and fluid leakoff were investigated.
The results showed that a laterally un-even shape of fracture propagation profile was developed during multi-stage CO2 fracturing, which represents the reservoir heterogeneity with varying in-situ stress and poroelastic properties. The results also indicated that the rheology of frac fluid significantly influences the fractures propagation. As the viscosity of CO2 foams increases with variation of foam quality from 50% - 80%, fracture width increases but fracture length decreases. The fluid loss during fracturing was quantified by pressure dependent leakoff approach. For different CO2 foams quality (50% - 80%), fluid leakoff rate decreases with increasing the CO2 foam quality.
This study provides a pioneering insight and improved fracture treatments design by non-Newtonian frac fluid - CO2 foams application with increased fracture conductivity and efficiency, which is vital for hydrocarbon exploitation from unconventional reservoirs.
The scope of this paper is to use publicly sourced data as a starting point for production analysis of two distinct well populations. The well populations that will be examined are horizontal Marcellus Shale wells (1) frac'd earlier in time with a defined plug-to-plug stage spacing and (2) frac'd at the same time or later in time with 1.5 to 3 times the number of stages, a production acceleration technique known as Reduced Cluster Spacing (RCS).
Public production databases were used to create snap shots of completion activity over time. To speed work flow, a more robust and regularly updated commercially available database that contains both completion and production data was used. Two distinct populations of wells for analysis were identified. A conservative decline curve analysis (DCA) was made to forecast estimated ultimate recovery (EUR) for all wells using only public data. For selected wells, reciprocal production rate versus square root of time plots were generated.
This paper will attempt to answer the following questions: (1) were statistically meaningful populations of both stimulation techniques found to exist; (2) how much production uplift did RCS achieve both early on and later time; (3) was there a real increase in EUR; (4) was there a difference in stimulation efficiency; and, (5) what can we learn by plotting P10, P50, and P90 values and EUR distribution curves for specific well populations.
To the authors' knowledge this would be the first SPE paper to explore this topic over such large Marcellus Shale well populations in Pennsylvania.
Conventional rock classification in carbonate reservoirs typically requires considerable amount of core data, which usually may not be available at the depth resolution required for each target interval. In cases of tight carbonate rocks with extremely low porosity (less than 5% in average) and permeability (less than 0.1 md), a reliable rock classification is essential for well stimulation modeling. Such rock classification should take into account depth-by-depth petrophysical, compositional, and elastic properties of the formation. In this paper, we apply an integrated rock classification technique to enhance (a) well-log-based estimates of petrophysical, compositional, and elastic properties and (b) selection of appropriate candidate zones for acid fracturing treatment design in a tight carbonate reservoir in northern slope of Tazhong Uplift, Tarim Basin, China.
We first perform multi-mineral analysis and estimate volumetric concentrations of minerals, porosity, and fluid saturations. Since shear wave sonic logs are not available in most of the wells, we estimate elastic moduli using effective medium models including self-consistent approximation and differential effective medium theory. Corrections including the impact of fluids are developed using Biot-Gassmann fluid substitution. The inputs to the effective medium models include (a) the petrophysical and compositional properties obtained from well logs, (b) bulk and shear moduli for each mineral and fluid component, and (c) shape of rock inclusions (i.e., grains and pores). Core measurements are used for cross validating the well-log-based estimates of elastic moduli and petrophysical properties. Accordingly, we proposed a rock classification technique using unsupervised neural network that integrated depth-by-depth volumetric concentrations of minerals, porosity, and elastic moduli. Finally, we derived permeability models in each rock type and estimated the permeability in the target depth intervals. Variogram analysis on well-log-based estimates of permeability provides correlation lengths as inputs to acid fracturing treatment modeling.
We successfully applied the technique introduced here to a challenging tight gas interval of Tarim field in China. The estimated porosity and permeability were in good agreement with laboratory core measurements. The identified rock classes were verified by core samples and thin sections. We estimated elastic moduli with average relative errors of approximately 13% compare to the core measurements. The estimated elastic moduli were used as a key input for modeling of acid-fracturing treatments and improved stimulation success.
The rock classification technique introduced here provides important input parameters for well stimulation modeling, gives insight into evaluation of acid fracturing in tight carbonate reservoir, and helps with selection of best candidate zones for acid fracturing treatment design.
Well operation is one of the key foundations for optimal production of hydrocarbons from unconventional shale plays. However, optimal production practices do not follow the versatility of "one size fits all" phenomenon. Completion strategy, Pressure-Volume-Temperature (PVT) properties and petrophysical properties vary from play to play. Hence, the well operating practices should be custom tailored to suit the completion and fluid properties.
In this paper, we propose optimal shut-in practices for dry gas shale reservoirs. We elaborated our study from a Marcellus shale dataset. Marcellus shale dry gas window has in place fluid properties that differ from liquid rich reservoirs like Eagle Ford and Wolfcamp shales. Therefore, production best practices borrowed "as-is" from liquid rich reservoirs and applied to dry gas reservoirs (or vice versa) may not affect the well ultimate recoveries in a positive manner and in some cases, may even reduce the expected ultimate recoveries (EUR's).
We show that the practice of "well conditioning", "resting" or "soak-in" i.e. shutting in the well for a significant time after hydraulic fracturing and before connecting to pipeline as well as frequent shut-in impedes the water unloading from the dry gas reservoirs. This leads to reduction in matrix permeability with an additional skin introduced by water imbibition.
Our methodology by simultaneously history matching gas rate, flowing bottomhole pressure (FBHP) and water rates in a reservoir simulator. We observe that after shut-in, water to gas ratio (WGR) decreases and gas rate increases. However, this increased gas rate is accompanied with higher declines in rates and pressures and ultimately leads to lower EUR's. The reduction in EUR in our case is modeled as a function of water saturation increase in the matrix due to imbibition. Thus, EUR in our study is a function of duration of shut-in and the time in well life at which the shut-in occurs.
With the increase in average lateral length for horizontal wells comes increased challenges for reaching total depth (TD) with the production casing. Any production interval left un-cased will not contribute to initial or ultimate production or be booked as reserves, which can have a major detrimental impact on the financials of these wells.
ALTISS Technologies has designed a patent pending aluminum casing concept to facilitate the installation of long cased laterals, and assist with landing casing at the total depth. Due to its low density and low modulus of elasticity, the aluminum casing is about half the buoyed weight and twice as flexible as comparable steel casing. These physical properties help the aluminum casing lighten the toe of the casing string and navigate through micro doglegs and tortuous wellbores.
The aluminum casing was designed with a focus on torque and drag reduction, to be used in limited quantities to maximize the benefits and ensure that casing reaches total depth. Analysis showed that 4,000 pounds of hook load could be added, without casing rotation, with as little as 160 feet of aluminum casing installed, in some cases. To ensure proper threaded connections with the low modulus aluminum, ALTISS designed its own 5 ½" premium threaded connection, which exceeded 56,000 ft.-lbs. yield torque in testing. Multiple aluminum tubular specimens were collapsed in a laboratory setting to validate equations which are not covered by API calculations, nor conventional closed form solutions (e.g. Timoshenko, Tamano). An experimental nano-coating is currently being evaluated that will protect the aluminum from potential forms of corrosion, including galvanic reactions and acid programs.
The advantages of installing aluminum casing may allow for eliminating expensive premium threaded connections needed for rotating casing, or alternatives such as floating casing. Ensuring the lateral is 100% cased improves initial production, allowable booked reserves, and ultimate hydrocarbon recovery of the well.
Volume and salt concentrations in Marcellus flowback water depend on geology, drilling and completions, stimulation and flowback operations. Recent studies include evaluations of geochemical origins based on the compostition concentrations, flowback sampling analysis and numerical studies. However, an in-depth understanding of chemical compositions as well as the changes of compositions is still needed.
In this paper, we will first review the literature related to flowback water in Marcellus shale gas wells to fully understand the chemistry, geochemistry, and physics governing a fracture treatment, shut-in, and flowback. We will then gather all public and in-house flowback data, named as 3-week or 3-month flowback in this work, to build a data set of flowback water compositions. After data screening, we will then analyze this composition database using four different methods: geographical, changes over time, linear regression, clustering and multi-variable analysis. New understandings such as the magnitude and prevailing trends of concentrations for target constituents as well as the correlations among flowback compositions, the differentiation between early and late time flowback water were obtained and explained on the basis of geochemistry and physics. Guidelines for a comprehensive sampling protocol will be provided based on our analysis.