Carbonate reservoirs usually consist of multiple units each with different degrees of layer-bound fracture density, height, length, and angular scatter. Some units may have finite fracture networks (FFNs), and some others may contain only isolated fractures. FFNs are islands of interconnected fractures within a sea of isolated fractures. The fracture volume can be estimated from the initial surge in

Water blocking can be a serious problem, causing a low gas production rate after hydraulic fracturing, a result of the strong capillarity in the tight sandstone reservoir aggravating the spontaneous imbibition. Fortunately, chemicals added to the fracturing fluids can alter the surface properties and thus prevent or reduce the water-blocking issue. We designed a spontaneous imbibition experiment to

Quantifying wettability of organic-rich mudrocks is important for reliable formation evaluation, optimizing production, predicting water/hydrocarbon production, and selection of appropriate fracture fluids. Recent publications suggest that kerogen wettability can vary as a function of thermal maturity, ranging from water- to hydrocarbon-wet at low to high thermal maturities, respectively. However,

Core-scale measurements are considered the ground truth that oil and gas or electric utility companies use to predict the migration of fluids such as oil, natural gas, carbon dioxide, or brine deep underground during their extraction or injection operations. To provide a greater understanding of petrophysical properties of low-permeability geologic formations such as shales and tight gas sandstones

This study continues the work of presenting a novel approach for making petrophysical assessments of tight core samples. This method, the full-immersion pressure-pulse decay (Hannon 2019), involves applying a rapid increase in pressure in a chamber surrounding the entire outer surface area of a cylindrical sample, shutting the system in, and monitoring the pressure decay in the chamber as it reaches

Foam stability primarily determines the efficiency of foam-induced conformance control, especially when fractures exist in formations. In this work, a well-defined nanocellulose fibril (NCF)-strengthened carbon dioxide foam (NCF-st-CO2 foam) was proposed, aiming to improve the conformance of tight formations with fractures. The bulk characteristics of NCF-st-CO2 foam including foamability, foam stability

Complex flow mechanisms, such as Knudsen diffusion, are encountered in the shale matrix because of the presence of nanopores. Numerous apparent-permeability models have been proposed to capture the ensuing non-Darcy flow behavior. However, these models are not readily available in most commercial reservoir simulators, and ignoring these mechanisms can potentially underestimate the overall matrix conductivity

Hydraulic fracturing is critical for extracting shale gas in the subsurface. The treatment technique of multistage hydraulic fracturing is widely used to maximize production. In multistage hydraulic fracturing, not all pumping stages make the same contribution for production, although the designed stimulation process is almost same in every pumping stage. In this study, we characterize the microseismic

Closed-loop reservoir management (CLRM) consists of continuous application of history matching and optimization of model-predictive control to maximize production or reservoir net present value (NPV) in any given period. Traditional field-scale implementation of CLRM by using a large number of reservoir models, in particular when uncertainty is accounted for, is computationally impractical. This presented

Decision analysis related to petroleum field development and management phases with complex models can be time-consuming, especially in highly heterogeneous fields. Probabilistic approaches require a large number of simulation runs to cover all possible solutions, and this can be slow. In this study, we present a methodology to include high-dimensional spatial attributes (geostatistical realizations)

Relative permeabilities are well understood for light oils involving stable displacement. However, conflicting arguments have been presented in the literature regarding relative permeabilities for viscous oils. Most nonthermal viscous oil displacements are unstable. Depending on the magnitude of mobility ratio, displacement is influenced by varying degrees of viscous instability, often referred to

To overcome the problems of slow mixing in the vapor-extraction (VAPEX) process and regaining high oil viscosity in the cyclic solvent process (CSP), we introduce a new process for thin heavy-oil reservoirs known as the enhanced cyclic solvent process (ECSP). In ECSP, two types of hydrocarbon solvents are cyclically injected in two separate slugs: one slug is more volatile (methane) and the other is

Numerous studies on electrical potential of particles have proven its wide range of applications in areas such as electrochemistry, geophysics, and hydrology. Because most researchers have only focused on single-type mineral particles, our knowledge about zeta potential is extremely limited, despite the fact that most natural rocks are mixtures of different pure minerals. In this research, we investigated

Capturing the correct reservoir heterogeneity in a geological model is critical for designing and accurately forecasting expected production benefits from improved/enhanced oil recovery processes. In simple terms, reservoir heterogeneity is often considered as a measure of statistical variation of static properties, such as porosity and permeability. The Lorenz coefficient and Dykstra-Parsons coefficient

Identification of vuggy intervals and understanding their connectivity are critical for predicting carbonate reservoir performance. Although core samples and conventional well logs have been traditionally used to classify vuggy facies, this process is labor intensive and often suffers from data inadequacies. Recently, convolutional neural network (CNN) algorithms have approached human-level performance

Machine learning provides powerful methods for inferential and predictive modeling of complicated multivariate relationships to support decision-making for spatial problems such as optimization of unconventional reservoir development. Current machine-learning methods have been widely used in exhaustive spatial data sets like satellite images. However, geological subsurface characterization is significantly

Hydrocarbon fields that are located offshore Abu Dhabi, United Arab Emirates (UAE), are known to be associated with undulating thick sedimentary sequences. These undulations are mostly influenced by variations in the depth of Infracambrian Hormuz salts that generate negative gravity anomalies. Nonetheless, a few known oil fields are uncorrelated with the airborne gravity observations. This is attributed

The oil and gas industry has come a long way by shifting from the deterministic methods of economic evaluations to probabilistic/stochastic methods. The time is right as the uncertainties keep on increasing and more sophisticated methods/calculations are required for decision-making. The industry is under pressure to maintain its key performance indicator of reserves-to-annual production ratio. New

Storage of large amounts of carbon dioxide (CO2) within deep underground aquifers has great potential for long-term mitigation of climate change. The U.S. Gulf Coast is an attractive target for CO2 storage because of the favorable formation properties for injection and containment of CO2. Deltaic formations are one of the primary targeted depositional environments in the Gulf Coast. In this paper,

In this study, we demonstrate the application of an interpretable (or explainable) machine-learning workflow using surface drilling data to identify fracturable, brittle, and productive rock intervals along horizontal laterals in the Marcellus Shale. The results are supported by a thorough model-agnostic interpretation of the input/output relationships to make the model explainable to users. The methodology

Offshore reservoirs are subjected to pressure loading from the ocean tide. The resulting pressure fluctuation, notably its amplitude and phase, provides valuable information regarding the formation compressibility and heterogeneity. The purpose of the present study is twofold: First, to propose a method for calculating tidal efficiency from harmonic analysis of regional tide stations and detrended

Optimal spacing between fracture clusters has eluded reservoir and completions engineers since the inception of multistage hydraulic fracturing. Very small fracture spacing could result in fracture to fracture (intrawell) interference and a higher completion cost, whereas very large fracture spacing could lead to inefficient hydrocarbon recovery, which is detrimental to the well economics. Meramec

The expanding solvent-steam-assisted gravity drainage (ES-SAGD) is a newly proposed thermal recovery technique showing promising efficiency in terms of a smaller steam-to-oil ratio and greater production rate to recover heavy oils and bitumen from oil-bearing formations, where a solvent is coinjected with the steam in the SAGD process. Numerical simulation of the ES-SAGD process requires reliable relative

Hydrocarbon (re-)development projects need to be evaluated under uncertainty. Forecasting oil and gas production needs to capture the ranges of the multitude of uncertain parameters and their impact on the forecast to maximize the value of the project for the company. Several authors showed, however, that the oil and gas industry has challenges in adequately assessing the distributions of hydrocarbon

In this paper, we present methodology to quantify biases in reserves estimates using technical revisions (TRs) listed in reserves-reconciliation reports filed with regulators in the US and Canada. Using this methodology, we assessed the reliability of reserves estimates for 34 companies filing in Canada and 32 companies filing in the US from 2007 to 2017. Filers in both Canada and the US overestimated

The oil and gas industry uses production forecasts to make decisions, which can be as mundane as whether to change the choke setting on a well, or as significant as whether to develop a field. These forecasts yield cash flow predictions and value-and-decision metrics such as net present value and internal rate of return. In this paper, probabilistic production forecasts made at the time of the development

A core-based fracture prediction method is used to illustrate a value-of-information (VOI) decision-analysis protocol to inform completion decisions in tight gas sandstones. The ratio of late host-rock cement to available pore volume (PV), or degradation index, uses petrographic observations of cement distributions in core (including sidewall cores) to predict whether nearby but unsampled fractures

The coexisting free gas, solution gas, and oil in a tight oil reservoir, constrained by the capillary force of the micrometer/nanometer pore/pore-throat system, are of crucial importance to the sweet spot of a tight oil reservoir. Equations of modified total capillary force for the liquid phase are proposed to indicate the tight oil mobility in situ, and are derived from the Kelvin capillary force

Flow zonation and permeability estimation is a common task in reservoir characterization. Typically, integration of openhole log data with a conventional and special core analysis solves this problem. We present a Bayesian-based method for identifying hydraulic flow units in uncored wells using the theory of hydraulic flow units (HFUs) and subsequently compute permeability using wireline log data.

Building a representative static model for predicting and monitoring the performance of coal-seam gas (CSG) fields presents several complex and unique challenges. The individual reservoirs possess different coal architectures, often with highly complex seam splitting, amalgamating, and structural deformation. Our objective was to develop an alternative approach that honored log and core data capturing

Reliable formation evaluation in organic-rich mudrocks requires integrated interpretation of well logs and core measurements. More than 80% of the Permian Basin wells have incomplete data sets, lacking photoelectric factor (PEF) or other logs required for reliable formation evaluation in the presence of complex mineralogy. Hence, we develop a novel workflow to reliably estimate rock properties in wells

Numerous technical papers have been published on the reservoir evaluation of tight sand gas in recent decades. It is believed that tight sand gas is characterized by low permeability, complex pore structure, abnormal pressure, and low gas saturation. Researchers have characterized tight gas in terms of, for example, statistics; and some of them are increasingly interested in the effect of fluid pressure

Nuclear magnetic resonance (NMR) measurements have been attractive options for wettability characterization of reservoir rocks as they are sensitive to the type of fluid in contact with the grain surface. Several NMR-based wettability indices are documented in previous publications. Most of these methods require extensive calibration or involve complex inversion algorithms, which makes them computationally

Diagenetic effects in carbonate rocks can enhance or occlude depositional pore space. Reliable identification of porosity-enhancing diagenetic features (e.g., vugs and fractures) is essential for petrophysical characterization of reservoir properties (e.g., porosity and permeability), construction of geological and reservoir models, reserve estimation, and production forecasting. Challenges remain

Cold heavy oil production with sand (CHOPS) technique has successfully improved oil recovery from heavy oil reservoirs due to high permeability channels resulted from sand failure and foamy oil flow enhancing heavy oil movability. However, impacts of the sand failure and the foamy oil flow on multiphase fluid flow features are still not properly understood. In this paper, an effective and systematic

Advances in horizontal drilling and multistage hydraulic fracturing have unlocked tight-oil resources, such as the Montney Formation in the Western Canadian Sedimentary Basin. However, the average oil-recovery factor after primary production is 5 to 10% of the original oil in place. The aims of this study are to investigate phase behavior and to estimate the minimum miscibility pressure (MMP) of the

A technique to quickly determine the asphaltene onset pressure (AOP) of a crude oil from low-volume, nonequilibrium measurements is presented. The pressure at which the optical signature indicative of asphaltene aggregation is first detected in recombined crude oils is found to decrease strongly with the rate of depressurization and can be well-described with a modified power law. This technique exploits

The enhanced oil recovery (EOR) technology can be instrumental in achieving the maximum rate of return from a hydrocarbon reservoir. One of the widely implemented EOR methodologies is the cyclic steam injection (CSI) which is a thermal recovery process aiming to reduce the oil viscosity and increase the production in naturally fractured heavy-oil reservoirs. However, commercial software used for CSI

Recent experience in applying recurrent neural networks (RNNs) to interpreting permanent downhole gauge records has highlighted the potential utility of machine learning algorithms to learn reservoir behavior from data. The power of the RNN resides in its ability to retain information in a form of memory of previous patterns and information contained in the previous behavior of phenomena being modeled

A series of earthquakes was recorded along a mapped fault system near Azle, Texas, in 2013. To identify the mechanism of seismicity, geologic, production/injection, and seismicity data are gathered to build a detailed simulation model with coupled fluid flow and geomechanics to model fluid injection/production and the potential onset of seismicity. Sensitivity studies for a broad range of reservoir

An incomplete data set of flow rate and pressure is detrimental to reservoir management and operation. It has the potential to increase uncertainty and has the potential to unfavorably affect operational and managerial decisions. Such a data set might transpire because of failure in the flowmeters, pressure gauges, and/or unrecorded shut-in periods. This study proposes and evaluates unified physics

Producer-flowline temperatures (FLTs) can be measured automatically with a thermistor on an emergency-shutdown system (ESD), or manually on a specified spot on flowline with a handheld unit. Measured FLTs can usually be mapped to represent the formationtemperature distribution for steamflood reservoir management purposes (Hong 1994; Nath et al. 2007). In addition to FLT, wellhead temperature (WHT)

Waterfloods in California operate under the US Environmental Protection Agency’s Class II underground injection control regulations, which are tasked with the protection of underground sources of drinking water (USDW) within the state. A key aspect of this regulatory framework is the operation of water injection wells under a maximum allowable surface pressure (MASP) to ensure that injected water does

Only 3 to 10% of gas from tight shale is recovered economically through natural depletion, demonstrating a significant potential for enhanced shale-gas recovery (ESGR). Experimental studies have demonstrated that shale kerogen/organic matter has higher affinity for carbon dioxide (CO2) than methane (CH4), which opens possibilities for carbon storage and new production strategies. This paper presents

Foamy oil flow is a commonly encountered drive mechanism in the primary production (depletion of naturally methane-saturated heavy oil) and secondary stage (cyclic gas—mostly methane—injection after primary production). In the former, among other important parameters, pressure depletion rate has been reported to be the most crucial parameter to control the process. In the latter, type and amount of

Mixtures of anionic/cationic surfactants have never been used in enhanced oil recovery (EOR) for negatively charged sandstone reservoirs because of high adsorption. Recently, novel mixtures of anionic/cationic surfactants that produced low critical micelle concentrations (CMCs) of 3.50×10–4 wt%, ultralow interfacial tension (IFT) of 10–4 mN/m, high oil solubilization of 23, and low adsorption of 0

Unconventional reservoirs such as Wolfcamp and Eagle Ford formations have played an important role in boosting the oil and gas production in the United States, but unfortunately, primary recovery from these reservoirs seldom exceeds 10%. Thus, operators are exploring enhanced oil recovery (EOR) techniques such as miscible gas injection (huff ‘n’ puff) and surfactants to increase the production from

In this study, we summarize and discuss the data reported from a series of multiscale experiments to explore the interactions of salinity and aqueous ions at fluid/fluid and rock/fluid interfaces and to understand the pore-scale oil-recovery mechanisms in controlled-ionic-composition waterflooding (CICW). Experimental data on various crude-oil/brine/carbonate and crude oil/brine physicochemical changes/effects

Phase change plays an essential role in wettability during steam injection, and oil becomes the wetting phase in the steam zone. This study investigates this unfavorable phenomenon using visual data obtained from micromodel experiments and how the wettability can be reversed using chemicals. All measurements were conducted at temperatures up to 200°C on glass-bead micromodels. The models were initially

Sieve analysis, sedimentation, and laser diffraction (LD) have been the methods of choice in determining particle-size distribution (PSD) for sand control design. However, these methods do not provide any information regarding the particle shape. In this study, we introduce the application of dynamic image analysis (DIA) to characterize particle sizes and shape descriptors of sand-bearing formations

Rock typing into flow units (FUs) plays a pivotal role in constructing static and dynamic models of petroleum reservoirs. Decisions made by asset teams mostly depend on predictions of how fluids will percolate through the subsurface during the reservoir life cycle. In carbonate settings, dealing with rock typing is complex and can generate a large quantity of units because of diagenetic processes such

Predicting oilfield performance is extremely challenging because of the large number of variables that can influence and control it. Traditional methods such as decline-curve analysis have been commonly used but have been shown to have significant shortcomings. In recent years, advances in machine learning (ML) have provided a new suite of tools to tackle complex multivariant problems such as understanding

The authors of SPE-191327-PA [ SPE Res Eval & Eng (in press; posted online 29 November 2018) https://doi.org/10.2118/191327-PA] have submitted corrections to the preprint paper. Full paragraphs are provided for context as applicable; all text corrections are marked in red. While these changes have been incorporated into the preprint paper, this errata will be included as supporting information to the

This erratum is being issued to correct the captions of Figs. 2 and 3 on pages 395 and 396 of SPE-175907-PA [ SPE Res Eval & Eng 21 (2): 392–404. https://doi.org/10.2118/175907-PA]. This change affects the captions only, and supersedes those contained in the paper.

Correction to Eq. 14 on page 278 of SPE-183640-PA; this equation supersedes the equation in the original published paper.