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Geological effects can impact the design and successful completion of oil, gas, and geothermal wells. Understanding the stresses and pore pressures within the subsurface are important to development of a geomechanical model that can guide well design as part of an integrated process to minimize cost and maximize safety. Forces in the Earth are quantified by means of a stress tensor, in which the individual components are tractions (with dimensions of force per unit area) acting perpendicular or parallel to three planes that are in turn orthogonal to each other. The normals to the three orthogonal planes define a Cartesian coordinate system (x1, x2, and x3). The stress tensor has nine components, each of which has an orientation and a magnitude (see Figure 1.a).
This one-day training event introduces completion, production, surveillance and reservoir engineers to the design of fiber-optic DTS (distributed temperature sensing) and DAS (distributed acoustic sensing) well installations. A basic understanding of the principles and benefits of DTS, DAS and surveillance monitoring technology, in general, is assumed. This course provides both an overview of water management and an in-depth look at critical issues related to sourcing (acquiring), reusing, recycling, and disposing of water in hydraulic fracturing operations. The course starts with a background of hydraulic fracturing operations and the different plays around North America. Options being used for transport, storage, reuse, and disposal are described for each of the different regions.
This paper showing that using rock-density measurement from well-logs affect the calculation of overburden stress because "environmental effects" caused by borehole conditions, overpressures, gas content, high mud filtrates, formation fluid saturation and rock mineralogy. Those effects influence the rock-density measurements and consequently both the overburden stress and geopressures computations; furthermore, the lack of rock-density well-logs in the first drilling stages also affect the overburden stress determinations. However, we consider that the most important bias-effect in the overburden stress calculation is that the overburden must be determined exclusively using the rock-density due to normal compaction of sediments. Hence, we are proposing a new method and model to compute the overburden stress that utilize a power law approach to reproduce rock density values instead to use log-density measurements. The new method is based on the theory of consolidation of clays described by Terzagui and Peck in 1948 which considers that rock-porosity reduction because of compaction when sediments burial increases. This rock-porosity reduction or rock-density increment can be modeled by a power law approach and use its results to calculate overburden instead rock-density measurements from well-logs. Here, we describe how establish the normal compaction trend for rock-density and its integration into overburden equation. This modified overburden model is showed and some examples are presented to permit readers to use the method with their own data. The examples compare the overburden stress calculated with new method against those using rock-density measurements from well-logs. The results show better overburden estimations using the power law model and how the use of rock-density readings from well-logs impact in the geopressures results because mislead of the overburden stress. The results allow to conclude that the overburden stress must be calculated using rock-density due to normal compaction of sediments and avoid the use of density-log readings that are influenced by "borehole environmental effects".
Pei, Yanli (The University of Texas at Austin) | Yu, Wei (The University of Texas at Austin / Sim Tech LLC) | Sepehrnoori, Kamy (The University of Texas at Austin) | Gong, Yiwen (Sim Tech LLC / The Ohio State University) | Xie, Hongbin (Sim Tech LLC) | Wu, Kan (Texas A&M University)
The extensive depletion of the development target has triggered the demand for infill drilling in the upside target of multilayer unconventional reservoirs. To optimize the hydraulic fracturing design of newly drilled wells, we need to investigate the stress changes in the upside target induced by parent-well production. In this work, an integrated parent-child workflow is presented to model the spatial-temporal stress evolution and propose the optimal development strategy for the upside target using a data set from the Permian Basin. The stress dependence of matrix permeability and fracture conductivity is determined based on available experimental data and incorporated in our reservoir simulation with the aid of an embedded discrete fracture model (EDFM). With calibrated reservoir properties from history matching of an actual well in the development target (i.e., 3rd BS Sand), we run the finite element method (FEM) based geomechanics simulator to predict the 3D spatial-temporal evolution of the local principal stresses. A displacement discontinuity method (DDM) hydraulic fracture model is then applied to simulate the multi-cluster fracture propagation in the upside target (i.e., L2BSSh) with the updated heterogeneous stress field. Numerical results indicate that stress field redistribution associated with parent-well production not only occurs within the development target but also vertically propagates to the upside target. A smaller parent-child horizontal offset induces a severer deviation of child-fractures towards the parent wellbore, resulting in more substantial well interference and less desirable oil and gas production. The parent-child fracture overlapping ratio in our study is in 0.6 ~ 0.8 for the 400 ft horizontal offset and 0.2 ~ 0.5 for the 600 ft horizontal offset. Varying the parent-child vertical offset gives the same trend as we change the horizontal offset. But with a delayed infill time, placing child-well in different layers causes more significant variation in the ultimate recovery. Moreover, infill operations at an earlier time are less affected by parent-well depletion because of the more homogeneous stress state. The candidate locations to implement infill-wells are suggested in the end for different infill timing by co-simulation of the parent-child production. With the reservoir-geomechanics-fracture model, this work provides a general workflow to optimize the child-well completion in multilayer unconventional reservoirs. The conclusions drawn from this study are of guiding significance to the subsequent development in the Permian Basin.
Unconventional reservoirs, such as Permian Basin, have fundamentally different production behaviors than that of the conventional reservoirs because of the low permeability of formations away from the stimulated volume. Thus, it is difficult to run full-field reservoir simulation to generate a full-field development plan. Even though satisfactory history matching for completion and production data can be achieved for wells at one location, it is difficult to directly apply the results to other areas in the same region. This is especially true in complex thick pay zone reservoirs, such as Permian Basin, where the complex geology, geomechanical properties, and resource properties all make the solution of frac hit (optimal well spacing) very challenging. To our best knowledge, this study is the first to integrate the detailed physics-based simulation, including fracturing simulation, coupled reservoir and geomechanics simulation, with machine learning (ML) to generate a sound workflow for well spacing optimization. In this workflow, a large field is first divided into several representative regions according to geology, geomechanical properties, and reservoir properties; and a typical well is selected for each region. High-quality physics simulation (including fracturing simulation, coupled reservoir simulation and geomechanics simulation) and history matching are then performed for a pair of parent and child wells. Additional well completion scenarios are built upon the base case, which serve as input to the following ML study. Various ensemble regression methods are applied to generate production predictions for unexplored reservoir locations in this field.
In recent years, many fracture simulation models have been developed to represent the complex geomechanical processes involved in hydraulic fracturing (F. Ajisafe, Shan, Alimahomed, Lati, & Ejofodomi, 2017; Morales et al., 2016; Pankaj, 2018b). Among them, well interference or well spacing optimization is a critical issue to solve in energy sector, especially during the current industrial downturn (F. O. Ajisafe, Solovyeva, Morales, Ejofodomi, & Porcu, 2017; Pankaj, 2018a; L. Wang & Yu, 2019; M. Wang, Wang, Zhou, & Yu, 2019). Detailed mechanistic study of integrated fracturing simulation and reservoir simulation have made significant progress during the recent years, which greatly helps to unlock unconventional resources and assist the industry to achieve economic goals (Alimahomed et al., 2017; Lashgari, Sun, Zhang, Pope, & Lake, 2019; Min, Sen, Ji, & Sullivan, 2018; Rodriguez, 2019). Nevertheless, when applying these technologies in unconventional field development and production, major uncertainties remain, including geology aspects such as stress orientation, stress anisotropy and natural fracture distribution, and completion aspects such as discrepancy between different completion strategies (Pankaj, Shukla, Kavousi, & Carr, 2018; Xiong, Liu, Feng, Liu, & Yue, 2019). A common concern is that even though current physics-based modeling and simulation could match the completion and historical production of a single well or multiple wells, it is still difficult to successfully transfer or scale up one small-area’s knowledge and experience to another area, because of the complexity and uncertainty of unconventional reservoirs (Xiong, Ramanathan, & Nguyen, 2019; Yeh et al., 2018).
With the recent development of unconventional reservoirs, attention has been geared towards the integration of the geomechanical models with traditional flow simulation. A case in point is quantifying rock-fluid interactions in hydraulic fracturing operations. Although much effort has gone into the creation and advancement of commercial simulation software for coupled flow and geomechanics, it is still in its infancy. The models are considerably oversimplified and poorly representative of the problem’s complex nature. Throughout history, several contributions have been made into the development of efficient model-order reduction (MOR) techniques for "flow only" simulations. Yet – to date – contributions to the mechanical models in coupled simulations have been minimal.
This study tackles this challenging aspect, by proposing a novel model reduction adaptive workflow, especially for the mechanics simulators, that (1) can be coupled with any simulator that can export mass, stiffness, and load matrices; (2) can achieve 2 orders of magnitude in computational time reduction; and (3) do not add more complexity to the solution.
In the first part of this paper, several – widely used – reduction techniques for structural mechanics were implemented based on the construction of the dynamic condensation matrix. Single-step reduction methods were first executed; in particular, Guyan DOFs based reduction techniques. Following that, two-step methods were implemented; where corrections were made to the results obtained from the former. Finally, iterative (three-step) reduction methods were applied; handling the problem of master DOFs selection through consistent updates of the dynamic condensation matrix until convergence is achieved. To that end, two schemes are presented; based on the convergence of the dynamic condensation matrix, as well as, the eigenvalues of the reduced-order model.
In the second part of this paper, we provide a rigorous framework for testing the completeness, efficiency, and convergence for all the presented reduction techniques. Regarding the completeness of the reduced models, two main criteria were investigated; namely, modal assurance criterion (MAC) and singular value decomposition (SVD). For efficiency testing, percent error (PE) of natural frequencies and the correlation coefficient for modal vector (CCFMV) values were considered. Finally, the efficiency of the convergent criterion was demonstrated through the errors associated with the column vectors of the condensation matrix. Several numerical examples are presented to show the efficiency of the presented framework, particularly for coupled simulations.
Based on the adopted framework, we managed to reduce the scale of the finite element models to less than 9% of the full model with error as low as 1%. In terms of computational speed and runtime, we achieved substantial speedups; up to 20X. Given the proposed workflow, large-scale complex simulations – similar to those associated with hydraulic fracturing – could be more feasible and less costly. This, ultimately, would give allowance for incorporating the complex physics pertinent to unconventional reservoirs and motivate the advent of their development at no additional cost.
Eltaleb, I. (University of Houston) | Rezaei, A. (University of Houston) | Siddiqui, F. (University of Houston) | Awad, M. M. (University of Houston) | Mansi, M. (University of Houston) | Dindoruk, B. (University of Houston) | Soliman, M. Y. (University of Houston)
The fracture injection fall-off test is a common technique for determining rock properties and fracture closure pressure. Conventional methods for analyzing DFIT are formulated based on the assumption of a vertical well and have shortcomings in horizontal wells drilled in ultra-low permeability reservoirs with potential multiple closures. In this study, an alternate technique using the signal processing approach is proposed. In the proposed method, we analyze the energy of the noise in the signal using a wavelet transform to identify the closure moment and pressure. We hypothesize that after the complete fracture closure moment, the noise in the recorded pressure will begin to vanish. To determine this closure moment, we decompose the pressure fall-off (signal) into multiple levels with different frequencies using the wavelet transform. Multiresolution wavelet decomposition breaks the (pressure) signal into high pass (noise) and low pass (approximation) components at various levels. The energy distribution plot is then constructed by plotting the energy of the high pass (noise) component versus the corresponding decomposition level.
Our results show that the noise energy reduces by several orders of magnitude at a specific time, which may identify the moment of fracture closure. Four field cases are analyzed using the proposed approach for demonstration. Also, we show an example where identifying the closure pressure using G-function is challenging, and our method still works reasonably well. Plots of the noise energy distribution versus time indicated multiple decreasing levels of energy. We also observed that the energy of the recorded noise in the signal could stay constant, or it can decrease gradually until the closure moment. In both cases, we observed that the signal energy drops to a minimum level at closure, and stays at that lowest level, thereby confirming our hypothesis. We also noted that the closure points that are found using this approach could happen before or after the closure from the conventional G-function method.
The main advantage of our proposed approach is that, unlike other physics-based techniques, it does not have any pre-assumption about the geometry of fracture or type of the well. It solely relies on the pressure signal that is recorded during the fall-off period. This advantage makes our approach unique since it is not limited to any specific formation, rock, or well type.
This paper was prepared for presentation at the Unconventional Resources Technology Conference held in Austin, Texas, USA, 20-22 July 2020. The URTeC Technical Program Committee accepted this presentation on the basis of information contained in an abstract submitted by the author(s). The contents of this paper have not been reviewed by URTeC and URTeC does not warrant the accuracy, reliability, or timeliness of any information herein. All information is the responsibility of, and, is subject to corrections by the author(s). Any person or entity that relies on any information obtained from this paper does so at their own risk. The information herein does not necessarily reflect any position of URTeC. Any reproduction, distribution, or storage of any part of this paper by anyone other than the author without the written consent of URTeC is prohibited. Abstract The publicly available multi-terabyte dataset of the Marcellus Shale Energy and Environmental Lab (MSEEL) consortium provides a unique opportunity to develop fracture models and analyze the effectiveness of the stimulation of a reservoir on a consistent base. Sonic, microresistivity image and production logs, microseismic data, and raw fiber optic measurements are examples of such data. Abundant core samples supplied demonstrate reservoir complexity and high density of natural fractures. The planar fracture model allows us to compare and contrast multiple stimulation strategies and propose engineered completions that cannot be done solely by data-driven approaches. Conclusions about stage spacing, stimulation design, wellbore placement, and stage isolation are shared. The workflow will be detailed to allow others to use, verify, and critique our findings using the same initial data.
For most US unconventional resources development, operators usually first drill the parent wells to hold their leases. After several years, infill wells will be drilled. The Meramec stack play in Anadarko Basin, Oklahoma is a multi-layered tight oil reservoir and its development just followed this practice. The parent well was drilled in layer 3 and shut down after 2-year production for infill well completion in layers 3 and 4 (layer 4 is below layer 3). After the infill well completion, field observations reveal a sharp increase in water production of the parent well, a decline in the oil production rate from the parent well, and a significant difference in production performance emerged between newly drilled infill wells. Two infill wells that are closest to the parent well but landed in layer 4 yield much lower oil and gas production compared to other infill wells completed in the same layer. In this paper, field data were analyzed to investigate the root causes of production loss from the parent well and lower-than-expected production rate from these two infill wells for this staggered well layout. Landing depth, well trajectories, operation conditions, and completion designs were compared for all infill wells and we found out that none of these can cause the significant production difference among the infill wells. Hence, the most accepted hypothesis is that the stress change induced by parent well depletion negatively affects the effectiveness of infill well completion.
A reservoir geomechanical simulation was developed to evaluate the pressure and stress change induced by the parent well depletion of two years. The reservoir model was prepared with available geological and well logging data. History matching for the parent well production was performed to determine the region of pressure sink. Based on geomechanical well logging test data, a 3D real field scale geomechanical model was built to calculate the stress redistribution induced by pressure sink. Results show that non-uniform fracture length with extreme long fractures in the parent well can generate non-uniform depletion area and pressure sink. Fractures generated in infill wells tend to propagate toward to depletion region and hit the existing long fractures in the parent well. Therefore, frac-hits still can be induced even with 1000 ft large well spacing. Stress change was also investigated vertically in different layers, especially layer 4. We found that stresses in the upper section of layer 4 have been decreased by parent well depletion and stresses in the lower section of layer 4 have been increased, which will favor fracture growing to the upper section and layer 3 due to lower stresses. Therefore, the staggered well layout may not necessarily be an effective strategy to mitigate interwell interference.
This study helps understand the poor performance of infill wells and provides some suggestions for future well development, such as applying extreme limit entry or diverter to generate more uniform fracture growth to avoid irregular depletion region, placing the parent well in the lower layer to mitigate well interference between staggered parent and infill wells for development of multiple pay layers.