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Advanced machine-learning methods combined with aspects of game theory are helping operators understand the drivers of water production and improve forecasting and economics in unconventional basins. What Damage Is Wrought by the Rush to Shut In Wells? The Permian Basin is now influencing the upstream water market on the way down, while many questions swirl around the implications of unprecedented shut-ins. Autonomous Inflow Control Valve technology demonstrates significant benefits within first year. As operators feel the pinch of low oil prices, so, too, do their service providers.
Rezaei, Ali (University of Houston) | Siddiqui, Fahd (University of Houston) | Dindoruk, Birol (University of Houston / Shell International Exploration and Production Inc.) | Soliman, M. Y. (University of Houston)
In order to maximize the profitability of a well and minimize the cost, three key questions must be answered before drilling a well: Where to drill the well? What completion design is to be used? Which fluid type will be produced from the reservoir? These questions must be answered under the premise of maximizing profitability. In this study, we combine the recently developed artificial neural network (ANN) model with a global sensitivity analysis method to present a reduced-order model for addressing these questions.
We developed ANN models to predict the oil and gas production of the first year. The input of the model are parameters such as longitude, latitude, true vertical depth, lateral length, fracturing fluid volume, proppant volume, and fracture stages. Next, we use the Sobol global sensitivity analysis to identify the dominant input variables and their interactions on the variation of the oil and gas production. Finally, we develop reduced-order models that can be represented as a simple algebraic expression consisting of simple mathematical functions. These equations can then be used to predict the production in the Eagle Ford shale rapidly by engineers on the field.
The ANN model used in this study predicted the oil and gas production of the first year with reasonable accuracy. Our model suggests increasing the number of fracture stages and proppant volume in the oil-bearing region. The suggestions for the gas bearing cases were opposite to the oil case. The Sobol global sensitivity approach used in this study captures the variation of the output parameters of the ANN model with respect to the changes in the input parameters. Also, it identifies the combined output variation due to the changes of multiple input parameters. After ranking the dominant contributing input parameters, the model was used to present a simple function to predict the oil and gas production of the first year (combined oil and gas). The function has the advantage to be used in a simple excel sheet and can rapidly predict the results. We compared the accuracy of the proposed reduced order model against the developed ANN model, and results showed less than 5% error in predictions.
For the first time, we have combined the data science methods with analysis of variance (ANOVA) based methods. This has resulted in a simple mathematical function to rapidly and directly predict the oil and gas from Eagle Ford shale, based on the input parameters that can be selected before drilling the well. Using the presented methodology, other such functions can be created for other shale plays and will aid engineers and decision-makers for field development to make reliable and quick decisions.
One of the missing pieces for the Delaware Basin development in the Wolfcamp Formation is optimal spacing for horizontal wells. The spacing varies with formation characteristics (rock and fluid) across the Delaware Basin. A single method of determining optimal spacing has yet to be found as many pieces of information are still missing. Among the various parameters affecting development, well patterns and completion methodologies. Both parameters show a significant impact on the drainage area of wells and may in turn affect optimal spacing between the wells. The model outcomes are expected to improve recovery efficiency and minimize environmental effects of unconventional resource development. Several spacing tests were implemented in various areas of the Delaware Basin with multiple completion strategies. Private production and spacing data were analyzed in conjunction with data analytics. This step led to a newly developed model to optimize spacing. Various reservoir parameters such as permeability, fracture width and height, drainage area, reserves, and recovery factors were estimated according to patterns discovered by transient flow rate analysis.
These parameters may lead to an optimal spacing for the stacked Delaware Basin, and contribute to a better understanding of future neighboring wells development. Our findings and correlation within the Wolfcamp will be applied to various sections and formations across the Permian Basin. Current workflows and spacing advisors require use of numerical reservoir simulation and fracture simulation. Drainage area, reserves, recovery factors, and fracture height and width are the main unknowns in unconventional plays. Application of data analytics with production, spacing, life of the well on production, and completion data is anticipated to resolve some of these issues.
The paper is to develop a thorough understanding of well spacing and to propose a strategy for optimization in shale and tight rocks. Well interference due to fracture driven interaction (FDIs) (frac hits) may occur between neighboring wells especially if the distance between the wells are narrow. This interference must be avoided to reduce negative impact on productivity and estimated ultimate recovery (EUR) of the producing wells. The impact of these interactions is intricate and requires advanced numerical modeling to account for fracture propagation and depletion effects due to varied spacing sets (Kan et al. 2019).
Efficient and cost-effective unconventional oil and gas (UOG) recovery depends critically on the knowledge of primary factors controlling the reservoir producing behaviors, as well as on well completion strategies. Currently the completion design of UOG wells is often dominated by geometry-based approaches, neglecting the impact of spatial heterogeneity of reservoir properties. The primary goal of this work is to identify geological factors and well completion strategies important to production using systematic Design of Experiment (DoE) methodologies, and then train a data-driven, machine-learning (ML) proxy model to expedite optimization of well completion. The results are demonstrated for applications in Permian Basin.
A set of Permian Basin wells are selected to provide a wide spectrum of geological, geomechanical and completion features existing in the basin. For each well, process-level modeling is performed in commercial hydraulic fracturing (HF) and reservoir simulators. For each well, the HF model is calibrated against historical well production data, by adjusting hydraulic fracture structure and reservoir properties. Using DoE methodologies, we evaluate a large number of completion strategies, in conjunction to different geological and geomechanical conditions. The effect of different decision variables on HF completion efficiency and production are examined, including the type of proppant carrier fluid (slick water and crosslinker), and proppant types (e.g., ceramic, curved resin, sizes, concentration, size, etc.). The results are used to develop an ML-based proxy model, which can be used to make rapid design of well completion strategies for future development, without requiring running time-consuming, full-scale reservoir simulations.
Simulation results of this work show the well completion implementation for many of the selected wells is far from optimal. History matching helps to establish the input-production relationships for each well, which provides a base model for sensitivity runs. The well set is divided into two parts. One part is used to develop an ML proxy model, and the rest is used for testing. Proxy modeling results suggest that the machine learning model can learn the complex reservoir input-output relations well, providing a data-driven tool for rapid well completion design and field production evaluation.
The complex geology, coupled with dynamic fracture stimulation and reservoir production processes are often not well investigated and represented in current practice, due to the lack of tools and representative data. As a result, sub-optimal production prevails, which erodes the HF economics. Previous works either mainly focus on mechanism simulation study or over-emphasize the original raw data but neglect the complex geology and physics underlying fracturing and reservoir production processes. The contribution of this study is we provide an integrated solution for well completion design based on real production data, fracturing simulation and reservoir simulation from different representative locations in Permian Basin. The physics-based proxy model can be used for future well designs by taking account into the effects of a large number of geological, geomechanical, and production factors.
Summary We report here a study of lithology-controlled stress variations observed in the Woodford shale (WDFD) in north-central Oklahoma. In a previous study, we showed that the magnitude of the minimum horizontal stress S hmin systematically varied with the abundance of clay plus kerogen in three distinct WDFD lithofacies. We believe that the application of the workflow described here in the context of viscoplastic stress relaxation can facilitate the understanding of layer-to-layer stress variations with lithology and thus contribute to improved HF effectiveness. Introduction Development of extremely low permeability unconventional oil and gas reservoirs requires multistage HF in horizontal wells. It is wellestablished that the magnitude of the three principal stresses and their relative differences significantly influence the initiation, propagation, and containment of hydraulic fractures (cf., Economides and Nolte 2000; Fisher and Warpinski 2012; Desroches et al. 2014; Xu et al. 2017; Zoback and Kohli 2019). More specifically, layer-to-layer stress variations influence optimal landing zone selection, vertical hydraulic fracture growth, and proppant placement (cf., Fu et al. 2019; Singh et al. 2019). Thus, to effectively stimulate the formations being produced from, one has to understand the physical properties of the formations being stimulated as well as the state of stress within, above, and below the producing units. Ma and Zoback (2017) reported variations of stress magnitudes obtained from HF stages in two horizontal wells that encountered three distinct lithofacies of the WDFD in central Oklahoma. They hypothesized that the abundance of compliant components (principally clay and organic matter, or kerogen) brought about the observed stress variations between the three WDFD lithofacies.
Hydraulic fracturing techniques use a variety of chemicals which alter the formation properties in the optimization of fracture initiation and growth. Acids are primarily used to clean perforations to provide an easy flow path into the formation for the fracturing fluid. Additionally, clay stabilizers may be pumped to prevent clay swelling and/or fines migration. These chemicals interact with shale to change its mechanical properties; however, mechanical testing of shale source rocks, especially fissile shale, is extremely difficult because of the limited availability of suitably sized samples and their inherent anisotropy. Nanoindentation provides an alternative technique to measure Young’s modulus and hardness of these rocks and to examine their dependency on chemical exposure. Acids weaken the shale frame and Young’s modulus was found to decrease by 13 to 80% after exposure. The results from acid exposure are evaluated with respect to mineralogy, porosity, microstructure, and other petrophysical properties. Microstructural changes caused by the exposure to acids were observed using a scanning electron microscope (SEM). The significant alterations in Young’s modulus from commonly used additives in fracturing fluids have a potentially large impact on formation damage and fracture performance. Lower values of Young’s modulus could lead to significant reduction in fracture conductivity due to enhanced proppant embedment or damage leading to rock failure. Nanoindentation hardness values decreased by as much as 82% after acid exposure. Knowing the potential formation damage induced by treatment fluids allows an optimal selection of treatment fluids. Better proppant performance can be predicted from the composition of formation, acid exposure, Young’s modulus and hardness responses.
McClure, Mark (ResFrac Corporation) | Picone, Matteo (ResFrac Corporation) | Fowler, Garrett (ResFrac Corporation) | Ratcliff, Dave (ResFrac Corporation) | Kang, Charles (ResFrac Corporation) | Medam, Soma (ResFrac Corporation) | Frantz, Joe (ResFrac Corporation)
Hydraulic fracturing and reservoir simulation are used by operators in shale to optimize design parameters such as well spacing, cluster spacing, and injection schedule. In this paper, we address'freqently asked questions' that we encounter when working on hydraulic fracture modeling projects with operators. First, we discuss three high-level topics: (1) data-driven and physics-based models, (2) the modeling workflow, and (3) planar-fracture modeling versus'complex fracture network' modeling. Next, we address specific technical topics related to modeling and the overall physics of hydraulic fracturing: (1) interrelationships between cluster spacing and other design parameters, (2) processes affecting fracture size, (3) fracture symmetry/asymmetry, (4) proppant settling versus trapping, (5) applications of Rate-Transient Analysis (RTA), (6) net pressure matching, (7) Initial Shut-In Pressure (ISIP) trends along the wellbore, and (8) the effect of understressed/underpressured layers. We discuss practical modeling decisions in the context of field observations.
Abivin, Patrice (Schlumberger) | Vidma, Konstantin (Schlumberger) | Xu, Tao (Schlumberger) | Boumessouer, Wissam (Schlumberger) | Bailhy, Jason (Schlumberger) | Ejofodomi, Efe (Schlumberger) | Sharma, Amit (Schlumberger) | Menasria, Samir (Schlumberger) | Makarychev-Mikhailov, Sergey (Schlumberger)
Infill drilling consists of adding horizontal wells between existing wells to optimize drainage in high-value acreage. New wells are sometimes drilled as close as 250 ft to producing or depleted wells. Fracturing the new wells creates a high risk of fracture-driven interactions (FDI). This paper describes a methodology to characterize well interference on production in unconventional basins and the impact of mitigation technologies.
Data mining, correlations, and statistical tools were developed to extract and analyze a large commercial production database covering major plays in the US. First, cloud-based algorithms were developed to identify and characterize infill wells based on coordinates, well deviations, production dates, and an adjustable radius of interference. Second, monitoring algorithms automatically captured and analyzed abrupt changes in normalized production of infill wells and neighboring wells at the time of infill well stimulation. Finally, the effect on production of both parent and child is immediately displayed on a user-friendly user interface for further visualization and interpretation.
The method was successfully applied to areas experiencing high infill drilling in major basins such as the Williston basin. Results show that production data correlate with historical changes in infill drilling density and fracturing job volumes (proppant and fluid). The production of child wells is then compared to that of their closest parent, which shows some decline as a function of the distance between wells. The systematic workflow also identifies if the basin is prone to positive fracture hits or if there is a significant decrease in the production of existing (parent) wells. The use and impact of diversion technologies as a well interference mitigation method is also studied.
These results give important insights into the effect of field development strategies on well interference and enable recommendations related to well spacing, fracturing designs, and use of fracture geometry control technologies to optimize future well and field development. Production data analysis clearly shows a beneficial impact of both near-wellbore and far-field diversion technologies on production.
The combination of extended-length horizontal drilling and high volume hydraulic fracturing has led to previously unimaginable production increases, yet the recovery potential of unconventional oil and gas resources remains largely unrealized. Recovery factors for unconventional oil and gas wells are typically reported at < 20% in gas shale reservoirs and < 10% in the oil plays.
Neutrally buoyant ultra-lightweight proppants have been demonstrated to effectively provide production from fracture area that is otherwise unpropped and thus, non-contributive with conventional sand/slickwater hydraulic fracturing processes. Production simulations illustrate that treatment designs incorporating neutrally buoyant ULW proppant treatment designs tailored for contemporary unconventional well stimulations deliver cumulative production increases of 30% to over 50% compared to the typical large volume sand/slickwater treatments. Unfortunately, production simulation results may not sufficiently lessen risk uncertainties for operators planning high-cost multi-stage horizontal stimulations. Therefore, several field trial projects using the neutrally buoyant ULW proppant in extended-length horizontal unconventional wells are currently in progress to validate the production simulations.
Since the initial 4-stage fracturing stimulation incorporating neutrally buoyant ultra-lightweight proppant in 2007, deployment has occurred in fracture stimulating hundreds of oil and gas wells spanning multiple basins and reservoirs. Most of the wells are vertical or relatively short lateral wells common to asset development practices predating the unconventional shale completions mania, but many were targeted at the same unconventional reservoirs as the current multi-stage horizontal completions. Several published case histories have documented the production enhancement benefits afforded by the legacy ULW proppant wells, but questions remained as to how those lessons might be correlated to provide engineers confidence in the current production simulations.
Well completion and production information was mined from the various accessible databases for the neutrally buoyant ULW proppant wells. The scope of the legacy data compiled for analysis was limited to the reservoirs common to the current field trials and production simulations, ie. unconventional oil and gas shale reservoirs. Production performance contributions of neutrally buoyant ULW proppant in past applications were compared with the production uplift observed in applications and/or simulated application of neutrally buoyant ultra-lightweight proppant fracturing treatments in current multi-stage horizontal reservoirs.
The lessons learned from this investigation provide the practicing engineer the means to confidently assess production simulation data for multi-stage horizontal unconventional completions incorporating neutrally buoyant ulw proppant in the treatment designs.
Tight gas and oil storage is different from conventional where a majority of oil and gas are stored in nanometer sized pores (nanopores). Therefore the nanofludics, i.e. nanometer scale capillary sealing and opening in nanopores of tight rocks, plays a key role in overpressure conservation and storage of oil and gas, and also the fracking process involves the opening of the nano pore capillary seals through rock-fluid interactions. Through models presented here, cuttings/cores’ headspace Stable Isotope Analysis (CHSIA) provides an effective way to calculate the pore throat size and distributions much like BET experiment, and it could also provide information about the original pore pressure or gas in place. The rock-fluid nanofluidics interactions during fracking could also be studied through CHSIA and the results could help the optimization of fracking designs.
Unconventional oil and gas production have altered world oil and gas supply map, particularly from North America where the light oil and gas from tight rocks that undergo extensive fracking in the long laterals. During the past decade, tens of thousands of laterals have been drilled and completed with latest fracking technologies. Yet, there are still unresolved puzzles. In this work, we discuss the three puzzles that are not obviously correlated, but are rooted back to the first success of hydraulic fracturing in Barnet in 1997, and have been perplexing unconventional tight oil and gas productions, storage and preservations. We reveal through stable isotope headspace analysis of core chips and cuttings that these puzzles are associated with the nanofluidic natures of shale oil and gas reservoirs.
The success of hydraulic fracking in the Barnett is a result of two factors, i.e. the abundance of shale gas in place that is much larger than adsorption or conventional porosity pressure product model and measurement had predicted (Bowker 2003); and the still mysterious breakthroughs (Zuckerman 2013, Gold 2014) by Nicolas Steinsberger and Ray Walker (Meyhofer 1997, Walker 1998) that large amount of fracking water, instead of ruining the formation as conventional wisdom still predicting, actually helps shale gas production more than other fracturing technologies available then and now. The shale gas in place and the detailed mechanism of how water actually promote oil and gas production from shale and tight rocks are both still hot topics right now (Jacobs 2015, Bostrom 2014, Bertoncello 2014) as the detailed production results have shown below.