Temizel, Cenk (Aera Energy) | Balaji, Karthik (University of North Dakota) | Canbaz, Celal Hakan (Ege University) | Palabiyik, Yildiray (Istanbul Technical University) | Moreno, Raul (Smart Recovery) | Rabiei, Minou (University of North Dakota) | Zhou, Zifu (University of North Dakota) | Ranjith, Rahul (Far Technologies)
Due to complex characteristics of shale reservoirs, data-driven techniques offer fast and practical solutions in optimization and better management of shale assets. Developments in data-driven techniques enable robust analysis of not only the primary depletion mechanisms, but also the enhanced oil recovery in unconventionals such as natural gas injection. This study provides a comprehensive background on application of data-driven methods in oil and gas industry, the process, methodology and learnings along with examples of data-driven analysis of natural gas injection in shale oil reservoirs through the use of publicly-available data.
Data is obtained and organized. Patterns in production data are analyzed using data-driven methods to understand key parameters in the recovery process as well as the optimum operational strategies to improve recovery. The complete process is illustrated step-by-step for clarity and to serve as a practical guide for readers. This study also provides information on what other alternative physics-based evaluation methods will be able to offer in the current conditions of data availability and the understanding of physics of recovery in shale oil assets together with the comparison of outcomes of those methods with respect to the data-driven methods. Thereby, a thorough comparison of physics-based and data-driven methods, their advantages, drawbacks and challenges are provided.
It has been observed that data organization and filtering takes significant time before application of the actual data-driven method, yet data-driven methods serve as a practical solution in fields that are mature enough to bear data for analysis as long as the methodology is carefully applied. The advantages, challenges and associated risks of using data-driven methods are also included. The results of comparison between physics-based methods and data-driven methods illustrate the advantages and disadvantages of each method while providing the differences in evaluation and outcome along with a guideline for when to use what kind of strategy and evaluation in an asset.
A comprehensive understanding of the interactions between key components of the formation and the way various elements of an EOR process impact these interactions, is of paramount importance. Among the few existing studies on natural gas injection in shale oil with the use of data-driven methods in oil and gas industry include a comparative approach including the physics-based methods but lack the interrelationship between physics-based and data-driven methods as a complementary and a competitor within the era of rise of unconventionals. This study closes the gap and serves as an up-to-date reference for industry professionals.
Production from highly paraffinic crude oil wells poses unique technical challenges such as poor flowability and paraffin deposition on the production tubing. Paraffin deposition increases the lift load on the pump, reduces pump efficiency, and eventually plugs the pump. To restore the productivity of these wells a common solution is to inject hot oil or hot water at 160°F–200°F to clean the deposits. This process imposes higher operating cost and lost production due to well downtime.
Paraffin inhibitor (PI) and pour point depressant (PPD) have been used to treat paraffinic fluids but are not effective for wells with high water cuts. These wells when treated with PI/PPD still require high cost maintenance such as the hot oil/water jobs and/or well workover. This paper presents a more effective treatment using tailored chemical mixtures to form a water dispersion with the paraffinic oil, thus to increase oil flowability and reduce deposition. A novel test method has been developed to evaluate effectiveness of treatment chemicals on various paraffinic oils based on flowability and cleanliness. The test method has been validated with field trial data from three different wells in the Uinta Basin, Utah and Julesburg Basin, Colorado.
The results of the field trials showed a significant increase in pumping efficiency and crude oil production. Need for hot water application was also reduced or eliminated for the treated wells. Improved oil and produced water quality were also observed. These results demonstrated that the water dispersion-based treatment is a more effective treatment for high paraffin wells with high water cuts.
A major shale producer in North America with established oil and gas production was facing challenges with severe paraffin deposition in downhole tubing and flowlines. Since chemical recommendations based on traditional screenings failed to deliver adequate inhibition, the operator turned to a costly remediation program to maintain production. We aimed to revisit the case, do a root cause analysis, and look for a potential chemical solution for cost savings. The field deposit obtained from the producer proved to be quite complex and introduced limitations with our current internal HTGC method for carbon chain analysis. Upon analysis, components present in the sample were found to exceed the solidity limits of the carrier system, carbon disulfide (CS2) and would precipitate out of the solution and form a two-phased system. These components were believed to be higher molecular weight carbon chains (HMWC) above C70+ at a high enough concentration to exceed the solvents solubility limit. This was the first time encountering such a sample in our experience. A systematic approach was applied to isolate the insoluble HMWC and further outsourced analysis. A MALDI-TOF and High-Resolution Carbon-13 NMR was utilized to confirm the presence of C90+ chains within the deposit at a high enough concentration to have a trimodal paraffin distribution system. To our knowledge, this is the first time a trimodal system has been documented.
Reliable estimation of organic matter characteristics is essential in drilling decisions, source rock evaluation, and unconventional reservoir production. Their measurement is based on experiments after core sampling, which is time-consuming and economically challenging. In this study, we present a new approach to evaluate the characteristics of organic matter in source and reservoir rocks by in-situ electrical heating and temperature transient analysis under in-situ conditions.
The new approach is based on inverse modeling, which monitors in-situ heater temperature during electrical heating and machine learning technologies. Thermal method of electrical heating is applied for the in-situ pyrolysis, to figure out the characteristics of organic matter—kerogen volume fraction and activation energy of decomposition reaction. The heater temperature acts as an indicator of type and maturity of kerogen, since it is affected by the bulk thermal conductivity of formation, which is a function of dynamically changing rock-and-pore composition by kerogen decomposition. A full-physics simulation model of in-situ kerogen pyrolysis is used to generate output data of electrical heater temperature, which is the input data of learning-based models. Minimal simplification of physical and chemical phenomena in the full-physics simulation model, which describes the multicomponent-multiphase-nonisothermal systems involving kinetic reactions, gives the confidence of synthetic output data of heater temperature.
Full-physics simulation model computes system responses under unknown and uncertain input parameters, which determine the reactivity of kerogen pyrolysis. The full-physics simulation model generates the sets of heater temperature transient data while heating with constant heat flux, in the 300 different simulated source rocks containing Types 1, 2, and 3 kerogens with various organic matter content and activation energies. Based on the set of heater temperature transient data as input parameters, Artificial Neural Network (ANN) is employed to generate a black box model to estimate the unknown organic matter content and activation energy. Developed ANN data-driven model shows better performance in estimating unknown parameters, in Types 2 and 3 kerogens with wide ranges of activation energies than Type 1 kerogen with a narrow range of activation energy. Support Vector Machines (SVM) method, which categorizes data into multiple classes by using hyperplanes, is applied to classify the heater temperature transient data into different types of kerogens and shows good performance in classification.
The new characterization technology of in-situ organic matter in source rocks presented in this study provides reliable information of types and maturity of organic matter, without experiments after core sampling. It is expected to enable the realistic evaluation of source rocks under subsurface conditions, by resolving technical and economic challenges.
The development of unconventional resources is capital intensive and challenging where operators spend a large amount of resources to maximize value. This is a direct result of completing thousands of wells with multistage fracturing. The optimization of well completion to enhance hydrocarbon recovery will help to reduce development costs and enhance project economics under the uncertainty parameters: geological, engineering, and economic.
The paper demonstrates a novel workflow as an effective way to optimize completion design by integrating advanced multi-stage fracture modeling with reservoir simulation in an unconventional resource play. This work shows an integrated workflow using a compositional dynamic simulation study for gas condensate well. The complexity of gas flow physics in both nano-darcy reservoir as well as hydraulically fractured Stimulated Rock Volume (SRV) are considered. The physics include gas desorption, pressure dependent permeability, non-Darcy flow and gas condensate fluid behavior.
The workflow includes QA/QC of the geologic model with a fine model resolution to map the hydraulic fractures. Long-term flow back data is used to calibrate the simulation model using history matching regions following the analytical trilinear model. After achieving a reasonable history matching, a detailed uncertainty assessment was performed to estimate P10, P50 and P90 of the well's EUR (Estimated Ultimate Recovery) using Proxy modeling workflow. Uncertainty parameters include hydraulic fracture half-length, SRV permeability, dew point pressure, under-saturated desorption pressure, rock compaction trend, etc.
Finally, what-if scenarios were performed to assess the impact of cluster spacing, fracture height, horizontal well length and minimum well head pressure (WHP) on the well's EUR.
The results of this work illustrates the workflow used to optimize well completion design including the number of stages along the lateral, length of the lateral, treatment sizes and how it impacts well performance as well to support management decision making.
The US Energy Information Administration (EIA) has added new play production data to its shale gas and tight oil reports. Last December, US shale and tight plays produced approximately 65 Bcf/D of natural gas and 7 million B/D of crude oil, accounting for 70% and 60% of US production in those areas, respectively. These totals represent a significant jump in the last 10 years: shale gas and tight oil accounted for 16% of total US gas production and approximately 12% of US total crude oil production, according to EIA statistics. EIA updated its production volume estimates to include seven additional shale gas and tight oil plays, increasing the share of shale gas by 9% and tight oil by 8% compared with previously estimated shale production volumes. The change captures increasing production from new, emerging plays as well as from older plays that had previously been in decline, but are now rebounding because of advancements in horizontal drilling and hydraulic fracturing.
Nath, Fatick (University of Louisiana at Lafayette) | Salvati, Peter E. (University of Louisiana at Lafayette) | Mokhtari, Mehdi (University of Louisiana at Lafayette) | Seibi, Abdennour (University of Louisiana at Lafayette) | Hayatdavoudi, Asadollah (University of Louisiana at Lafayette)
Understanding the mechanical behavior (compression, shear, or tension) of rocks plays an important role in wellbore-stability design and hydraulic-fracturing optimization. Among rock mechanical properties, strain is a critical parameter describing rock deformation under stress with respect to its original condition, yet conventional methods for strain measurement have several deficiencies. In this paper, we analyze the application of the optical method digital-image correlation (DIC) to provide detailed information regarding fracture patterns and dynamic strain development under Brazilian testing conditions. The effects of porosity, rock type, lamination, and saturation (freshwater and brine) on indirect tensile strength are also discussed.
To examine the effect of rock type, 60 samples of sandstone (Parker, Nugget, and Berea) and carbonate rocks (Winterset Limestone, Silurian Dolomite, Edwards Brown Carbonate, and Austin Chalk) were tested under dry and saturated conditions with regard to lamination angle in laminated samples. A photogrammetry system was used to monitor the samples in a noncontact manner while conducting the indirect tensile experiment. DIC depends on the photogrammetry system, which helps to visualize and examine rock-fracture patterns from the recorded images of the rock before and after deformation by assessing the strain development in samples.
The experimental results show the following.
We introduce a novel well-logging method for determining more-accurate total porosities, fluid volumes, and kerogen volumes in shale-gas and shale-tight-oil wells. Improved accuracy is achieved by self-consistently accounting for the effects of light hydrocarbons and kerogen on the log responses. The logging measurements needed to practice this method are bulk densities, nuclear-magnetic-resonance (NMR) total porosities, and total-organic-carbon (TOC) weight fractions. The TOC weight fractions and the matrix densities, which are used to interpret the bulk density measurements, are both derived from geochemical-tool measurements.
Most unconventional shale-gas and shale-tight-oil reservoirs contain some nonproducible immobile hydrocarbons. When immobile hydrocarbons are present, our method requires prior knowledge of in-situ total water volumes. The water volumes can be estimated from dielectric-tool measurements. In special cases (e.g., in some mature shale-gas reservoirs) where no immobile hydrocarbons are present, a dielectric tool is not needed. In such cases total water volumes are outputs of the method.
We discuss the response functions in shale reservoirs for measurements of bulk densities, NMR porosities, and TOC weight fractions and derive exact self-consistent solutions to the response equations. The algebraic solutions are used to compute shale total porosities, fluid volumes, and kerogen volumes. The predicted shale total porosities and fluid volumes are corrected for light-hydrocarbon effects on the measured bulk densities and NMR porosities and for kerogen effects on the bulk densities. It is shown that significant errors can be made in log-derived shale total porosities if NMR porosities or density-log porosities are assumed to represent true-shale porosities without applying proper corrections.
We discuss the application of the method to the analysis of logging data acquired in a mature shale-gas well drilled in the Marcellus Shale in the northeastern United States and to data acquired in a shale-tight-oil well drilled in the Permian Basin in west Texas. A multifrequency dielectric tool is used to determine in-situ total water volumes in the tight oil well. The mature shale-gas reservoir does not contain immobile hydrocarbons, and, therefore, dielectric-logging measurements were not needed in this well. The results in both wells are shown to compare favorably with core data.
We report experimental research on frictional strength and stability properties of shale fractures during slip. Longmaxi shale, Green River shale and Marcellus shale are selected for constant-velocity and velocity-stepping fracture shear experiments. Combing with theoretical analysis, micro controlling mechanism of mineralogy on frictional strength and stability properties of shale fractures is discussed. Results indicate that the fracture friction-stability relationship is largely affected by shale mineralogy. Frictional strength of shale fractures increases when tectosilicate content increases and phyllosilicate content decreases; during velocity-stepping experiments, three kinds of shale show velocity-strengthening behavior, which means an aseismic creep tends to occur; with the increase content of tectosilicate, shale fractures tend to have seismic slip while with the increase of phyllosilicate content, stable aseismic creep happens.
With the advances in horizontal drilling and multi-stage fracturing technologies, shale gas production has a substantial growth not only in North America, but also in other areas around the world (Jia et al., 2018; Wu et al., 2017). However, as the basic stimulation method to enhance shale gas recovery, hydraulic fracturing is implemented for almost every shale gas wells. After hydraulic fracturing operations, large-scale waste water re-injection has been linked to seismic activities (Bao and Eaton, 2016; Ellsworth, 2013; Elsworth et al., 2016), which has raised public concerns and makes hydraulic fracturing prohibited in many areas across the world.
The large-scale injection of waste water generates overpressures and decreases effective normal stresses which leads to reactivation of pre-existing faults and fractures in formations (Ellsworth, 2013), which is shown in Fig 1. In addition, the fracturing operations induced fractures may also be the source for seismic activities. Hence, the stability of pre-existing and induced fractures will decide whether seismic activities happen.
Fig. 1. Mechanism of induced seismicity by large-scale water re-injection. Natural fractures and hydraulic fracturing induced fractures may be re-activated by overpressure caused by fluid injection.
The objective of this work was to develop a supercritical CO2 foam with a liquid phase composed of a polyelectrolyte complex nanoparticle system interacting with a viscoelastic surfactant solution. This is intended to be used as a fracturing fluid to reduce fluid loss and increase post-fracture clean-up efficiency for improved productivity in unconventional reservoirs. In a previous study, we optimized the polycation/polyanion ratio and polyelectrolyte pH using zeta potential and phase-angle light scattering. Rheological and foam stability tests were used to further optimize surfactant/polyelectrolyte ratio. In this work, dynamic fluid loss tests were performed on supercritical CO2 foam generated using the optimized ratio of surfactant/PECNP to investigate the effect of PECNP addition to the surfactant solution on the fluid loss. The same foam systems were used to investigate post fracture clean up using sand pack tests. Interfacial tension was measured on both air-(surfactant/PECNP) and supercritical CO2-(surfactant/PECNP) systems to understand the effect of PECNP on IFT. Fluid loss to the formation during hydraulic fracturing causes water blockage, formation damage and capillary pressure shift, lowering the conductivity of the reservoir, and impeding the flow of oil and gas. Supercritical CO2 foam generated by surfactant solution exhibited low fluid loss, thus lower values of fluid loss coefficient compared to unfoamed surfactant systems. However, addition of polyelectrolyte complex nanoparticles further reduced the total fluid loss and fluid loss coefficient. Foam fracturing fluids break in the presence of crude oil because the oil penetrates the foam lamellae causing drainage and lamellar rupture; this results in effective post fracture clean up using supercritical CO2 foam as fracturing fluid. Foam systems generated by surfactant showed promising clean up results, and the addition of PECNP further increased clean up efficiency. From IFT test results we concluded that the addition of PECNP decreased interfacial tension of both air-(surfactant/PECNP) and supercritical CO2-(surfactant/PECNP) systems. The addition of optimized polyelectrolyte complex nanoparticles to surfactant in a supercritical CO2 foam fracturing fluid can reduce interfacial tension and fluid loss, which will reduce formation damage, resulting in better hydrocarbon flow. PECNP stabilized surfactant-supercritical CO2 foam drains rapidly in the presence of crude oil, leading to good clean-up, which will result in better flow back and higher productivity.