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Suarez-Rivera, Roberto (W. D. Von Gonten Laboratories) | Panse, Rohit (W. D. Von Gonten Laboratories) | Sovizi, Javad (Baker Hughes) | Dontsov, Egor (ResFrac Corporation) | LaReau, Heather (BP America Production Company, BPx Energy Inc.) | Suter, Kirke (BP America Production Company, BPx Energy Inc.) | Blose, Matthew (BP America Production Company, BPx Energy Inc.) | Hailu, Thomas (BP America Production Company, BPx Energy Inc.) | Koontz, Kyle (BP America Production Company, BPx Energy Inc.)
Abstract Predicting fracture behavior is important for well placement design and for optimizing multi-well development production. This requires the use of fracturing models that are calibrated to represent field measurements. However, because hydraulic fracture models include complex physics and uncertainties and have many variables defining these, the problem of calibrating modeling results with field responses is ill-posed. There are more model variables than can be changed than field observations to constrain these. It is always possible to find a calibrated model that reproduces the field data. However, the model is not unique and multiple matching solutions exist. The objective and scope of this work is to define a workflow for constraining these solutions and obtaining a more representative model for forecasting and optimization. We used field data from a multi-pad project in the Delaware play, with actual pump schedules, frac sequence, and time delays as used in the field, for all stages and all wells. We constructed a hydraulic fracturing model using high-confidence rock properties data and calibrated the model to field stimulation treatment data varying the two model variables with highest uncertainty: tectonic strain and average leak-off coefficient, while keeping all other model variables fixed. By reducing the number of adjusting model variables for calibration, we significantly lower the potential for over-fitting. Using an ultra-fast hydraulic fracturing simulator, we solved a global optimization problem to minimize the mismatch between the ISIPs and treatment pressures measured in the field and simulated by the model, for all the stages and all wells. This workflow helps us match the dominant ISIP trends in the field data and delivers higher confidence predictions in the regional stress. However, the uncertainty in the fracture geometry is still large. We also compared these results with traditional workflows that rely on selecting representative stages for calibration to field data. Results show that our workflow defines a better global optimum that best represents the behavior of all stages on all wells, and allows us to provide higher-confidence predictions of fracturing results for subsequent pads. We then used this higher confidence model to conduct sensitivity analysis for improving the well placement in subsequent pads and compared the results of the model predictions with the actual pad results.
Abstract Fracture treatments and stage designs for new wells have evolved considerably over the past decade contributingto significant production growth. For example, in the acreage discussed hererecently used higher intensity fracturing methods provided an ~80% increase in recovery rates compared with legacy wells. Older wells completed originally with less efficient techniques can also benefit from these more up-to-date designs and treatments using re-fracturing methods. These offer the prospect of economically boosting production in appropriately selected wells. While adding in-fill wells has often been favored by Operators as a lowerrisk option the number of wells being re-fractured has grown every year for the last decade. In this case study two adjacent Eagle Ford wells, comprising a newly completed and a re-fractured well, allow both methods to be considered and compared. Completion design and fracture treatment effectiveness are evaluated using the uniformity of proppant distribution at cluster and stage level as the primary measure. Perforation erosion measurements from downhole video footage is used as the main diagnostic. Novel data acquisition methods combined with successful well preparation provided comprehensive and high-quality datasets. The subsequent proppant distribution analysis for the two wells provides the highest confidence results presented to date. Clear, repeatable trends in distribution are observed and these are compared across multiple stage designs for both the newly completed and re-fractured well. Variations in design parameters and how these effects distribution and ultimately recovery are discussed. These include changes to perforation count per cluster, cluster spacing, cluster count per stage, stage length, perforation charge size and treatment rates and volumes. As a final consideration production records for the evaluated wells are also discussed. Historical industry data shows that the number of wells being re-fractured increases relative to the number of newly drilled wells being completed during periods of low oil and gas prices. With the industry again facing harsh economic realities an increasing number of decisions will be made on whether new or refractured wells, or a combination of both, provide the best solution to replace otherwise inevitable production decline. This paper attempts to provide a detailed understanding of how proppant distribution, as a significant factor in production for hydraulically fractured wells, can be evaluated and considered in these decisions.
Thiessen, Scott (Hunting Energy Services - Titan Division) | Han, Oliver (Hunting Energy Services - Titan Division) | Ahmed, Ramadan (University of Oklahoma) | Elgaddafi, Rida (University of Oklahoma)
ABSTRACT In hydraulic fracturing, determining the perforation pressure loss is a critical step in the design strategy, on-site troubleshooting diagnostics and post-fracture analysis. Historically, the most widely assumed and thus unknown components in the perforation friction equationare the coefficient of discharge and the holistic perforation diameter. The perforation coefficient of discharge has long been assumed as a dynamic variable dependent on the amount of fluid and proppant pumped through the perforations. This variable becomes increasingly important when clusters are spaced closer together and fewer perforations are shot such as in a limited entry design. Limited entry is a perforating technique used to generate uniform fractures along the wellbore by creating appropriate pressure differentials from cluster to cluster. With the adoption of consistent hole perforating shaped charges, the perforating diameters are more consistent and predictable. While not all consistent hole shaped charges have low diameter variability, the perforating diameters downhole are no longer an unknown, particularly after the introduction of downhole cameras. Therefore, the coefficient of discharge is the only unknown variable remaining. This paper presents an experimental methodology to accurately define the true coefficient of discharge in common completions perforated by a known consistent hole shaped charge. The test setup is illustrated, detailed test steps are discussed, and experimental data with correlations of rate per perforation and discharge coefficient is presented. Completions tested included 4-1/2", 5", and 5-1/2" casings in common weights and grades. Various perforating strategies were examined such as single shot and angled shot. Critical parameters such as entry hole diameters were made by the actual shaped charges and measured before and after the test. Freshwater and slickwater were used as hydraulic fluid and circulated at real-world pump rates through each perforation to simulate the actual field flow conditions. Based on the study, several correlations for the coefficient of discharge of flow through a perforation are created considering casing thickness, entry hole diameter and rate per perforation for the given consistent hole shaped charges. These correlations can improve perforation and fracturing designs where perforation friction are important variables.
Abstract Most waterfloods in California target sandstone formations that are unconsolidated in nature with high porosities and high permeabilities. These formations are also characterized by high Poisson ratios and low values of Young's Moduli. There has been a concern if, during the waterfloods of these types of formations, fracturing takes place at high-injection gradients. The influence of various factors on leak-off is studied in detail, indicating that with an increase in rock permeability, the leak-off velocity increases. This study included a comprehensive analysis of the characteristics of such soft formations and their responses to high injection gradients. We show that if the leak-off factors are adjusted to reflect high permeability and proper geomechanical properties, the probability of fracture formation is nil at injection gradients up to 0.9 psi/ft, for unconsolidated rooks. We computed estimated fracture width, fracture height, fracture length and noted for all three calculations, it takes gradients approaching 1psi/ft to note a non-trivial estimated value for these characteristics. This study shows that for unconsolidated formations like those in California targeted for waterfloods, the probability of fracture formation under pressure gradients of 0.9 psi/ft. is nil, and high injectivities can be exercised without the fear of fracture formation.
Abstract The rate of penetration (ROP) was optimized using a particle swarm optimization algorithm for real-time field data to reduce drilling time and increase efficiency. ROP is directly related to drilling costs and is a major factor in determining mechanical specific energy, which is often used to quantify drilling efficiency. Optimization of ROP can therefore help cut down costs associated with drilling. ROP values were chosen from real-time field data, accounting for weight on bit, bit rotation, flow rate variation along with bit wear. A random forest regressor was used to find correlations between the dependent parameters. The parameters were then optimized for the given constraints to find the optimal solution space. The boundary constraints for the ROP function were determined from the real-time data. The function parameters were optimized using a particle swarm optimization algorithm. This is a meta-heuristic model used to optimize an objective function for its maximum or minimum within given constraints. The optimization method makes use of a population of solution particles which act as the particle swarm. These particles move collectively in the given solution space controlled by a mathematical model based on their position and velocity. This model makes use of the best-known solution for each particle and the global best position of the system to guide the swarm towards the optimal solution. The function was optimized for each well, providing optimal ROP values during real-time drilling. A fast drilling optimizer is crucial to automate and streamline the drilling process. This simultaneous optimization of ROP based on real-time data can be implemented during the process thereby increasing the efficiency of drilling as well as reducing the required drilling time.
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.
The most basic vibration analysis is a system with a single degree of freedom (SDOF), such as the classical linear oscillator (CLO), as shown in Figure 1. It consists of a point mass, spring, and damper. This example will be used to calculate the effects of vibration under free and forced vibration, with and without damping. Where needed, refer to this refresher on differential calculus. The first analysis is free vibration without damping.
Aljaberi, Jaber (King Fahd University of Petroleum & Minerals) | Alafnan, Saad (King Fahd University of Petroleum & Minerals (Corresponding author)) | Glatz, Guenther (King Fahd University of Petroleum & Minerals) | Sultan, Abdullah S. (King Fahd University of Petroleum & Minerals) | Afagwu, Clement (King Fahd University of Petroleum & Minerals)
Summary Shale-matrix-associated transport phenomena exhibit multiple mechanisms including advective-, diffusive-, and adsorptive-driven transport modes, depending on the pore type. Diffusive processes are governed by the shale organic constituents known as kerogens. Kerogens, composed of fine-scale organic microstructures, vary with respect to their petrophysical properties, depending on their origin and maturity level. The extent to which kerogens contribute to the overall transport is governed by their ability to diffuse hydrocarbons contained within. The diffusion coefficient is a crucial parameter used to quantify diffusivity based on the interactions between the host material and the diffusing molecules. Kerogen as a hosting medium allows for diffusion of natural gas at various rates based on several factors. One of these factors, kerogen porosity, is conjectured to significantly influence diffusive transport phenomena. In this paper, taking advantage of the predictive power of molecular dynamics (MD) simulation, we investigate the impact of kerogen porosity on the diffusivity coefficient of natural gas. Starting from a single type II kerogen macromolecule, several kerogen structures for a realistic range of porosity values were created and, subsequently, used for diffusivity calculations of methane molecules. Simulation results suggest a direct link between diffusion and kerogen porosity, allowing for delineation of the diffusion tortuosity factor. Furthermore, the microscale tortuosity–diffusivity relationship in kerogens was investigated at the reservoir scale by means of a shale permeability model. The results substantiate the critical impact of the diffusion process on the shale permeability.
Summary The effects of temperature on the permeability coefficients of carbonaceous shales and the underlying mechanisms have been investigated experimentally. Pressure-pulse-decay gas-permeability tests were performed on seven shale plugs with different lithological compositions, organic-matter contents ranging from 0.8 to 11.7% total organic carbon (TOC) and thermal maturity between 0.53 and 1.45% random vitrinite reflectance (VRr). During the tests, the measuring temperatures were changed stepwise from 30 to 120°C and back to 30°C while axial load and confining pressure were kept constant. Sister plugs were used for mechanical tests to investigate the creep response upon thermal loading under the same temperature conditions. The samples showed varying degrees of permeability reduction by up to 71% with increasing temperature. This reduced permeability persisted during the cooling phase. The observed permeability changes reflect the elastoplastic deformation upon the thermal compaction of the rocks. Permeability reduction and creep response with increasing temperature are evidently controlled by organic matter, although clay minerals also played an important role. Organic-matter- and clay-rich shales exhibit the strongest response to temperature, while temperature effects were slightly smaller for overmature samples. Rock mechanical analysis showed that permeability reduction correlates with temperature-related creep/deformation of the shales. Given the strong temperature dependence of the mechanical stiffness of solid organic matter and of the viscosity of bituminous solids/liquids, more attention should be paid to temperature effects in the assessment of shale permeability. Our experimental results document that thermal stimulation has negative effects on shale-transport properties and that measurements conducted at laboratory temperatures can lead to substantial overestimation of in-situ shale permeability.
Summary Linear network models are promisingly simple progressive cavity pump design tools. Current linear network models are difficult to use in the design process because they require calibration against experimental data or computationally intensive simulation. In this paper we present new approaches for implementing linear network progressive cavity pump models and provide new methods to accurately and quickly estimate the values of each resistor in the model from pump geometry for both laminar and turbulent flows. This paper also argues that sealing-line flow transitions from laminar to turbulent at orders of magnitude smaller Reynolds numbers than described in the literature thus far. We propose a new hypothesis for the point of transition to turbulent performance.