bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluating Well Casing Integrity with Non-Invasive Electromagnetic Methods
Authors: MacLennan Kristopher , Nieuwenhuis Greg , Wilt Michael , Um Evan , Pendleton Joseph M. 
Published: October 2018

Abstract
Casing integrity is a major issue for thousands of older oil and water wells. Damage to well casings may occur for multiple reasons, including corrosive wellbore fluids, mechanical failures, or external forces, and can lead to impaired production and environmental risks. We propose a rapid, non-invasive electromagnetic (EM) method for diagnostic testing of casing integrity. The well casing is energized by connecting an electrical current source at low frequency to the wellhead. Current flows down the casing and out into the formation at a rate defined by the length of the casing, the casing conductance, and the formation resistivity. Damaged casing has a reduced conductance, and so the flow of current is altered, with an increased amount leaving the casing above the damaged segment. This affects the electric fields observed at the surface, a difference which can be measured with sufficiently sensitive electric field sensors. By comparing forward modeling results based on wellbore diagrams of intact casing with the observed fields, we can arrive at an estimate of whether or not the casing has been damaged. This paper describes the theory behind this method and validates the methodology through synthetic modeling. We also consider how the effects of various common oilfield scenarios may affect the success of the EM casing integrity evaluation method.
Utilizing Geomechanically Informed Completions to Reduce the Environmental Impact of Hydraulic Fracturing in Unconventional Reservoirs
Authors: Hildick Alice M. , Scott Ellen L. 
Published: October 2018

Abstract
Recently, the United States (US) oil and gas industry has dramatically increased its production, primarily due to technological advances in horizontal drilling and hydraulic fracturing. Current hydraulic fracturing practices require a significant amount of water. Section 9.2.1 of the API Recommended Practice (2015) states that of development activities including drilling and completion activites, hydraulic fracturing, typically results in the most significant water use. For context, hydraulic fracturing operations in 2000 used approximately 177,000 gallons of water per oil and gas well. According to USGS, hydraulic fracturing requirements increased to over four million gallons of water per oil well and 5.1 million gallons of water per gas well in 2014 (USGS, 2015). The Environmental Protection Agency's multiyear study found an increasing trend in water use per well attributed to growing numbers of wells drilled, with longer laterals and more stages completed (Dunn-Norman, et al., 2018).
Many US oil and gas companies’ annual reports and public communications currently feature sustainability and environmentally-responsible development strategies. However, opportunities to minimize negative environmental impact without affecting the value of a large-scale unconventional development is extremely difficult, particularly in the current low oil price market. Operators throughout the industry are developing water management facilities focused on safe, reliable and environmentally friendly water management practices. This paper discusses utilizing in-situ mechanical rock property data to optimize completion strategies, which can help reduce the negative impacts of hydraulic fracturing, while maintaining, and often increasing, production.
Stimulated Oil Reservoir Volume Estimation of Prominent US Tight Oil Formations
Authors: Panja Palash , Velasco Raul , Deo Milind 
Published: October 2018

Abstract
In this work, we estimate the Stimulated Original Oil In Place (SOOIP) of hydraulically fractured horizontal wells in prominent shale plays. This is done by compiling production data from hundreds of wells belonging to the Bakken, Niobrara, Wolfcamp, Eagle Ford, Bone Springs, and Woodford totaling over 2,500 wells. Additionally, we present probabilistic distributions of SOOIP with mean, standard deviation, P10, P50, and P90 estimates for each play.
To circumvent the challenge of data availability for each well, we use the findings of a previous study where all reservoir unknowns are grouped into two major parameters. One of these parameters, alpha, is a function of the stimulated reservoir volume, compressibility, and pressure drawdown, where the last two are unknowns. While alpha is determined with high confidence for each well, we account for the uncertainty of compressibility and drawdown values across wells by assuming a normal distribution for these parameters. Lastly, by incorporating 1 million Monte Carlo samplings and a Mersenne Twister random number generator we estimate SOOIP distributions for each play with varying degrees of confidence.
The final results show that the Niobrara and Bakken have the highest mean SOOIP values per well while the values for the Woodford and Bone Springs are the lowest among all six plays considered. Volumetric calculations using data from the literature qualitatively corroborate these findings. New insight on the stimulated volumes per well for prominent shale plays can be derived from these results as they correlate to horizontal well length, formation thickness, and hydraulic fracture half-lengths in each play.
Field Validation of a New BHA Model and Practical Case Studies in Unconventional Shale Plays, with a Framework for Automated Analysis for Operations Support
Authors: Wilson J. K. 
Published: October 2018

Abstract
A new three-dimensional drillstring model has been developed that determines the static and dynamic behavior of bottom hole assemblies (BHAs) in realistic wellbores. The analysis approach has been validated with field data, and shows a strong agreement between observed and calculated BHA behavior. Several case studies are presented that show the practical use and benefit of the advanced model for, among other applications, unconventional horizontal drilling. A framework is also provided to show how the model can be incorporated into automated engineering processes for operations support.
Validation tests were conducted using high-frequency down-hole data measured within a motor- assisted rotary-steerable BHA. The gathered data was used to verify the calculated mechanical loads, predicted lateral natural frequencies of the BHA, estimated directional performance of the down-hole assembly, as well as torsional resonance resulting from High-Frequency Torsional Oscillations (HFTO). Using the validated model, various analyses have been conducted for operators around the globe, in a multitude of different drilling environments, to aid in identifying drilling dysfunctions and optimizing BHA performance. Several case studies are presented that highlight the benefit of the modeling techniques in US unconventional shale plays as well as in the Canadian heavy-oil sands, with noticeable improvements in drilling efficiencies, tool design, and reduced non-productive time (NPT).
Results from the field tests show a strong correlation between measured and calculated bending moment values, as well as lateral natural frequencies of the BHA with an average of 3% error across all data sets. The primary source of error is thought to be borehole spiraling, which is quantified through analysis of the down-hole bending moment data. In addition, the model is shown to provide close estimates to actual directional performance of both steerable mud motor and Rotary-Steerable BHAs. However, the directional calculation-measurement comparison does reveal a need to incorporate an ROP-dependency within the directional prediction algorithms.
Nevertheless, even with these sources of discrepancy, the modeling approach provides a sensible prediction of the BHA's mechanical and dynamic behavior and, as shown through case studies, can be used as a planning tool for BHA design, an investigative tool for root-cause analysis, or potentially as a real-time optimization tool for avoiding harmful operating conditions.
Hydraulic Fracturing Design in Shale Formations Based on the Impact of Fracturing Additives on the Fluid Loss and Flowback
Authors: Al-Ameri Aymen , Gamadi Talal , Ispas Ion , Watson Marshall 
Published: October 2018

Abstract
Throughout fracturing treatment, millions of gallons of water are injected, but commonly less than 50% is recovered after stimulation. This study was constructed to evaluate the impact of the fracturing additives on the fluid flowback and fluid loss during hydraulic fracturing. Different pad fluids types were considered including; friction reducer fluid, friction reducer with a non-ionic surfactant fluid and 3 wt% HCl acid.
Flooding experiments were conducted for core samples from the Eagle Ford outcrop to measure the brine permeability, time of breakthrough and water relative permeability. The measurements were performed for intact samples and also after flooding the samples with the fracturing fluids. A simulation sector modeling for a hydraulically fractured vertical well in the shale formation was constructed to investigate the effect of the fracturing additives on the fluid flowback and fluid loss during hydraulic fracturing. A sensitivity analysis was considered to study the effect of the formation capillary pressure and reservoir pressure on the fluid flowback and fluid loss due to counter-current capillary imbibition.
The study results showed that the fluid saturation in the near fracture face shale matrix is highly reduced by the effect of the high capillary pressure. Therefore, the fluid had not flow back from the near fracture face matrix. Moreover, adding a non-ionic surfactant to the friction reducer pad fluid or using 3 wt% HCl increased the fluid loss during pumping and the fluid imbibition during shut-in, flowback, and production. Therefore, the dilute HCl acid and small well shut-in times are recommended when no flowback occurs from the near fracture face matrix due to low fluid saturation.
The fluid loss from the near fracture face region due to counter-current capillary imbibition reduced the effect of the fluid saturation on the gas production. However, the high fluid saturation and the polymer adsorption may cause water blocks. Thus, reducing the gas production or leading to a complete gas block.
For shales with moderate capillary pressure, a flowback from the near fracture face matrix has occurred. Hence, the friction reducer with a non-ionic surfactant fluid and 3 wt% HCl enhanced both of the fluid loss due to counter-current capillary imbibition and the fluid flowback. However, a non-ionic surfactant and long shut-in time are recommended for the hydraulic fracturing. Shales with low reservoir pressure had less fluid flowback and more fluid loss. To minimize the fluid loss during pumping and to overcome the water block problem, it is recommended to use a friction reducer fluid in the pad stage while injecting a non-ionic surfactant or dilute acid during the subsequent fracturing steps.
Integrating Propellant and Shaped Charges to Improve Frac Efficiency
Authors: Albert L.. , Nery N.. , Prapoo H.. , Dai P.. , Qu B.. , Jiang G.. , Kwok D.. 
Published: October 2018

AbstractCurrent perforating guns utilize shaped charges with high energy explosives (RDX, HMX, etc.) to shoot high velocity jets of metal in a direction that is perpendicular to the gun body (and casing), thus creating holes in casing and tunnels through cemented annulus and formation. The physics of shaped charge perforating (high velocity jet of metal penetrating casing and formation) results in a crushed zone of rock around the perforation tunnel. Rock crushing increases skin and lowers permeability in the near wellbore region, making formations more difficult to breakdown and increasing treating pressures. There have been many methods developed to overcome the perforation crushed zone and improve flow efficiency. These methods include underbalance, overbalance, propellants, charge orientation and reactive shaped charge liners.Propellants (energetic materials with slower burn rates than explosives shaped charges) have been utilized in a number of methods to create a delayed pressure pulse to break-up the crushed zone around perforation tunnels. Propellants have been added as solid sleeves over guns, solid sticks ignited across open sets of perforations and propellant discs within gun bodies. With each of these techniques, propellant is located within the wellbore when it burns, thus the pressure pulse builds within the casing and then flows into perforation tunnels. As the pressure pulse moves into perforations, it can disrupt the tunnel crushed zone and create fractures. The net effect is lower skin and improved perforation efficiency. Unfortunately, by burning propellant within the casing, the efficiency of the pressure pulse is reduced.To tackle the challenges above, a new method is proposed to place propellant in a molded cap that attaches to the face of individual shaped charges. This new method results in jets produced by shaped charges dragging the propellant material behind the high velocity jet as it penetrates casing, cement annulus and formation. As a result, most of the propellant burns sequentially within the perforation tunnel, thus delivering direct continuum pressure pulse to the perforating event. The propellant provides a secondary stream of energy, enlarging the perforation tunnel diameter, cleaning up the perforation tunnel and giving impetus to the shaped charge jet, resulting in deeper penetration. The result is very effective and efficient in disrupting crushed zones and creating fractures around the perforation tunnel.
Combining Decline Curve Analysis and Geostatistics to Forecast Gas Production in the Marcellus Shale
Authors: Xi Zhenke , Morgan Eugene 
Published: October 2018

Abstract
Traditionally, in order to estimate the production potential at a new, prospective field site via simulation or material balance, one needs to collect various forms of expensive field data and/or make assumptions about the nature of the formation at that site. Decline curve analysis would not be applicable in this scenario, as producing wells need to pre-exist in the target field. The objective of our work is to make first-order forecasts of production rates at prospective, undrilled sites using only production data from existing wells in the entire play. This is accomplished through co-kriging of decline curve parameter values, where the parameter values are obtained at each existing well by fitting an appropriate decline model to the production history. Co-kriging gives the best linear unbiased prediction of parameter values at undrilled locations, and also estimates uncertainty in those predictions. Thus, we can obtain production forecasts at P10, P50, and P90, as well as calculate EUR at those same levels, across the spatial domain of the play.
To demonstrate the proposed methodology, we used monthly gas flow rates and well locations from the Marcellus shale gas play in this research. Looking only at horizontal and directional wells, the gas production rates at each well were carefully filtered and screened. Also, we normalized the rates by perforation interval length. We kept only production histories of 24 months or longer in duration to ensure good decline curve fits. Ultimately, we were left with 5,637 production records. Here, we chose Duong’s decline model to represent production decline in this shale gas play, and fitting of this decline curve was accomplished through ordinary least square regression.
Interpolation was done by universal co-kriging with consideration to correlate the four parameters in Duongs’ model, which also showed a linear trend (the parameters show dependency on the x and y spatial coordinates). Kriging gave us the optimal decline curve coefficients at new locations (P50 curve), as well as the variance in these coefficient estimates (used to establish P10 and P90 curves). We were also able to map EUR across the study area. Finally, the co-kriging model was cross-validated with leave-one-out scheme, which showed significant but not unreasonable error in decline curve coefficient prediction.
We forecasted potential gas production in the study area using co-kriging. Heat maps of decline curve parameters as well as EUR were constructed to give operators a big picture of the production potential in the play. The methods proposed are easy to implement and do not require various expensive data like permeability, bottom hole pressure, etc., giving operators a risk-based analysis of prospective sites. We also made this analysis available to the public in a user-friendly web app.
Modified Arps Equation for Changing B-factor
Authors: Biseda Brent 
Published: October 2018

Abstract
SPEE Monograph 4 establishes recommended best practices for decline curve analysis of unconventional wells through the use of specialized diagnostic plots such as the square-root of time plot. These diagnostic plots are important for flow regime identification and selection of an appropriate b-factor for predicting a well’s EUR. However, in practice, because of familiarity with the Arps decline equation and its ease of use, typically a single b-factor is selected despite multi-fractured horizontal wellbores demonstrating changes in flow regime and consequently the b-factor. This paper introduces the Modified Arps Equation, an iterative formulation of the Arps equation. The Modified Arps Equation maintains use of the form of the original Arps equation with a few modifications to allow for a changing b-factor. These modifications allow a single equation to be used with a vectorized b-factor in order to model a well as it transitions from linear flow to boundary dominated flow and eventually back to pseudo-linear flow. This equation may be applied broadly across unconventionals where wells transition over years from linear flow to boundary dominated flow and later return to pseudo-linear flow as simulation data suggest.
A Novel Workflow for Fracture Reconstruction and Uncertainty Analysis for Unconventional Reservoir Development
Authors: Liang Baosheng , Du Song 
Published: October 2018

Abstract
Fracture networks present a critical influence on to better assess oil recovery and to optimize production of hydraulically fractured reservoirs. We established a novel workflow for fracture uncertainty analysis and prediction, in which multiple fracture pattern realizations are created from the geostatistical analysis. The original fracture networks were created using geomechanics tools. Then the fracture network is reconstrued for uncertainty analysis and history matching. For different realizations of the fracture distributions created in this workflow, we successfully maintain the continuity of the fractures, as well as the connections from the matrix to fractures. The generated grid can be further used for treatment simulation to determine fractures geometry, height growth and respected proppant transport in the induced fracture network.
In this paper, we also apply Embedded Discrete Fracture Model (EDFM) to capture the realistic geometry of fractures. Within the EDFM, each fracture plane is embedded inside the matrix grid and is discretized by the cell boundaries. We study a series of reservoir simulation realizations, in which the complex hydraulic fracture networks are created in the workflow. We investigate different fracture realizations in both planar and complex fracture configurations while maintaining the continuity within the fracture networks. This study also includes the influence of the network geometry and fractures properties on the overall performance of the reservoir.
From the uncertainty analysis results, we find that the overall reservoir performance is controlled by the fracture connectivity and the distribution of conductivity within the network. A good match of production history can be achieved by adjusting the fracture connectivity. Modeling with multiple realizations of fracture networks acknowledge that a reliable production forecast is achievable using geostatistical analysis for fracture connection reconstructions. Applying Embedded Discrete Fracture Model (EDFM) on the fracture-related model simulation provides a robust and effective means of investigating multiple fracture realizations.
Utilizing an Innovative Approach to Create Type Well Areas for Unconventional Gas Shales
Authors: Kreman Drew , Osholake Tunde 
Published: October 2018

Abstract
Three principal factors that influence shale gas productivity are the reservoir quality (geology), the fluid type (which affects drive mechanism), and the completion methodology (which is affected by geomechanics). Out of all the reservoir fluids, dry gas has the highest recovery factor. Within dry gas shale resources, fluid type is not as big a factor compared to other hydrocarbon types. With fluid type out of the equation, where does geology and geomechanics contribute in the assessment of type well (TW) areas? In most occurrences, the geology and geomechanics is unaccounted for and only the factors that influence or quantify productivity (EUR, Cumulative Production, etc.) are utilized to generate TW areas. This paper demonstrates a unique, innovative approach, combining well-known statistical learning methods with detailed geologic and geomechanical maps to derive "like" geologic areas, lending to common well productivity. This new approach, not only reinforces the necessity of geologic mapping work, but more importantly takes out the geologic bias, while statistically exploring the data for geologic similarities.
The approach outlined in this paper takes a slightly different approach from a previous study [1], which grouped wells into different type wells by productivity measures (e.g. flowing pressures, shut in pressures, condensate gas ratio, flow potential, and separator oil and gas gravity). This approach focuses on generating similar geologic areas built around grid-based geologic and geomechanical maps, and relating these common areas back to type well performance. The common approach taken by both studies is the application of statistical learning methods, specifically principal component analysis and hierarchical clustering, to explore and group observations into similar regions.
This study includes various datasets, which range from production data to detailed geologic data for a frontier gas shale play in North America, but is applicable to most unconventional gas shales. This approach utilizes unsupervised statistical learning methods and infers that we are not trying to be predictive, but rather explore what geologically is influencing the type well areas.
The results of this study show that unsupervised learning techniques applied in a meaningful way can be used to delineate type well areas. Actual production data (Gas Rate and EUR) was utilized to verify the type well areas that have been generated using this method. In conclusion, six type well areas were generated and ranked by production results. It is recommended by the authors to utilize this approach in any frontier shale gas basin, in order to better streamline a type well workflow.