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.
Shahri, Mojtaba (Apache Corp.) | James, Moisan (Apache Corp.) | Vasicek, Alan (Apache Corp.) | De Napoli, Roy (Apache Corp.) | White, Matthew (Apache Corp.) | Behounek, Michael (Apache Corp.) | D'Angelo, John (University of Texas at Austin) | Ashok, Pradeep (University of Texas at Austin) | van Oort, Eric (University of Texas at Austin)
Given the intensity of drilling operations in the North American unconventional reservoirs and the quality and amount of data gathered during a drilling operation, leveraging those data along with advanced modeling techniques for optimization purposes is becoming more feasible. In this study, historical data and advanced physical modeling are utilized to better understand and optimize the bottom-hole assembly (BHA) performance in drilling operations. A comprehensive data set is gathered for more than 300 BHA runs in the span of three years. This extensive data set enables thorough examination of the variation in the operational parameters and its effect on the drilling performance.
Different indices are used to determine and evaluate drilling performance, such as rate of penetration (ROP). Excessive tortuosity in a well can have many detrimental effects while drilling such as excessive and erratic torque and drag, poor hole cleaning (cuttings removal), low ROP, along with problematic casing and/or liner runs and associated cementing procedures. In this paper, a tortuosity index (TI) is used to quantify the drilled well quality and correlate it to ultimate drilling performance. In the next step, patterns are extracted and used along with physical modeling for optimizing drilling performance before the well is drilled.
The corresponding tortuosity index can be used as a proxy for the well path smoothness and may be used for quantifying parameters affecting drilling performance. According to historical drilling performance data, there appears to be a strong relationship between wellbore tortuosity and ROP. If drilling operating parameters (e.g., BHA configuration, directional company's performance, target formations, bit specification, mud types, etc.) can be related to the TI based on historical data, such parameters can be modified for optimizing the performance before the well is drilled.
By investigating the historical data, different trends have been extracted. In addition, different models can be built to predict drilling performance (e.g., TI) prior to drilling and according to new well design specifications. Based on data from more than 300 BHA runs and using advanced physical modeling, the most strongly correlated parameters to drilling performance have been determined and shown using different case studies. Such a historical database along with modeling techniques are used to predict well quality and drilling performance during the design phase. Using this method, well design specifications can then be optimized to enhance drilling performance and reduce the cost.
Observations from field applications along with laboratory experiments have revealed the significant potential of the surfactant-assisted spontaneous imbibition (SASI) as an encouraging EOR method in unconventional liquid reservoirs (ULR). This study focuses on unveiling the target pore size range for SASI EOR through a combination of experimental results, computed tomography (CT), Scanning Electron Microscope (SEM) and Nuclear magnetic resonance (NMR) technologies. In addition, laboratory results were upscaled to the field-scale to evaluate the effectiveness of the SASI EOR in production enhancement in the Wolfcamp formation.
Eight SASI experiments were performed at reservoir temperature using different surfactants on quartz- and carbonate-rich side-wall core samples obtained from the Wolfcamp formation. Contact angle (CA), interfacial tension (IFT), and zeta potential were measured for the saturated core samples. CT-Scan technology is used to visualize the process of oil expulsion from the core plugs and generate core-scale simulation model to history-match laboratory results. SEM is used to match the NMR Pore Size Distribution (PSD) and obtain the Surface Relaxivity for each core sample. The target pore size range for SASI EOR in ULR is determined from NMR results. In addition, the laboratory results were upscaled to estimate the production enhancement through SASI EOR using the field scale model.
The primary production mechanism of SASI EOR is highly influenced by wettability alteration and IFT reduction. SASI experiments showed optimistic oil recovery results in both quartz-rich and carbonate-rich core samples with up to 36% and 17.5% of the Original Oil in Place (OOIP), respectively. The NMR technique is used to determine the pore size range from which the oil is produced during the SASI experiment. NMR results revealed that the pore size distribution plays a significant role in SASI EOR with the majority of the imbibed fluid is observed in smaller pores. The consideration of the pore size distribution has a significant impact on successful surfactant selection and a proper EOR process design in ULR. CT-scan technology is utilized to demonstrate the movement of the fluids inside the cores throughout the experiments. CT-scan technology is also used to validate the NMR results, which revealed a direct relation between CT imaging and NMR results. A CT-generated core-scale model was utilized to history-match laboratory results. The capillary pressure and relative permeability curves for the field-scale model were estimated from scaling group analysis and core-scale simulation. The simulation results indicate that SASI EOR has significant potential of enhancing oil production in ULR.
The novelty comes from the insight of the essential role of the pore size distribution in SASI EOR through CT and NMR technologies. Besides, a new workflow for surfactant selection is proposed to unveil the real potential of SASI in ULR.
Expert-guided machine learning has been used to classify depositional facies from core photographs of the Wolfcamp, Bone Spring and Spraberry formations in the Permian Basin. Training sets of core facies were selected by a sedimentologist. A model was built using a convolutional neural network and then tested against core outside of the training set with a 98% accuracy. The system can yield a quit-look of core facies much faster than that of traditional methods.
Artificial Intelligence (AI) is a branch of computer science that creates intelligent machines that work and react like humans. Machine learning is a key part of AI and requires an ability to identify patterns in streams of inputs. Learning with adequate supervision involves classification, which determines the category an object belongs to. Today it is being extensively used in image and speech recognition. At present the application of machine learning is in its infancy in the area of geosciences for the oil and gas industry.
The objective of our research is to determine if machine learning can be used to fast-track identification of depositional facies from images of conventional core photographs. Normally, this work requires a sedimentologist to painstakingly describe a core that may take many weeks to incorporate with logs and other formation evaluation data. With over 200 cored wells having 50,000 feet of core in our Permian Basin projects, the task of core description is overwhelming.
Theory and/or Methods
In order to meet the objective the software needs to be trained to recognize the various depositional facies. This is done by employing a sedimentologist (expert) to guide the training with the AI specialist. The sedimentologist builds a training set from several cores through a particular formation (e.g. Wolfcamp). The training set is a set of images selected by the sedimentologist to cover the range of depositional facies and the variations seen in each facies (Figure 1). The training sets typically employ 20 to 40 images of each facies.
Objectives/Scope: The continuous drive by the E&P industry to deliver additional value and performance improvements in unconventional reservoirs has created the need for innovative advances in technology to meet evolving challenges. Jweda et al. (2017) and Liu et al. (2017) developed a novel time-lapse geochemistry technology calibrated to core extracted oils to cost effectively ascertain vertical drainage, which is among the most critical parameters used in determining optimal field development strategies. Aqueous geochemistry, well-established in academic and environmental investigations, is another technology that can be used in conjunction with time-lapse hydrocarbon geochemistry to evaluate drainage behavior, vertical connectivity between stacked wells and to ascertain the efficacy of different stimulation designs. Methods/Procedures/Process: More than 300 produced water samples from approximately 60 different Eagle Ford wells have been collected across ConocoPhillips’ Eagle Ford acreage. Sampling campaigns have included collecting several long-term time-series and baseline samples from individual wells across the field. The analytical program consists of a suite of total ion chemistry (cations and anions), salinity, alkalinity, and isotopic geochemistry (δ18O, δD, 87Sr/86Sr, δ11B). Results/Observations/Conclusions: Produced waters, contain a robust arsenal of geochemical signals that can be analyzed to understand the provenance(s) and change(s) in composition with time of these produced waters. A combination of interpretative and multivariate statistical tools were used to gain a deeper understanding of water-rock interactions and mixing/diffusion processes in the subsurface. Stimulation water was differentiated from in-situ formation water, and the evolution of that process was tracked over time. Time-series water analyses were also used to evaluate differences between completion designs, determine the vertical drainage and/or communication between wells, and ultimately understand the drained rock volume through time. Applications/Significance/Novelty: We clearly demonstrate that produced waters are mixtures of stimulation and formation water and that long-term geochemical signals from different layers within the Eagle Ford can be differentiated using aqueous geochemistry. Furthermore, we show that the formation waters vary vertically, coincident with hydrocarbon indicators (oil biomarkers and gas isotopes). To our knowledge, this is among the first published studies of aqueous geochemical behavior of produced waters in the Eagle Ford and the first to establish that intra-formational waters can be discerned, which is particularly novel and important for evaluating completion designs and strategies within a stacked development.
Jin, Xiaochun (Jacob) (ULTRecovery Corporation) | Pavia, Michael (ULTRecovery Corporation) | Samuel, Michael (ULTRecovery Corporation) | Shah, Subhash (University of Oklahoma, Norman) | Zhang, Rixing (ULTRecovery Corporation) | Thompson, James (ULTRecovery Corporation)
Historical production data of unconventional oil wells shows rapid decline rate and low estimated ultimate recovery (EUR), although the records of “lateral length” and “number of stages” have been broken frequently in Permian Basin. The industry has been striving to develop a novel technically feasible and economic enhanced oil recovery (EOR) technology to arrest the production decline curve; however, limited successes have been achieved.
According to the dialectical analysis of the four-dimensional dynamic interactions between unconventional rock-slickwater system-subsurface water-indigenous beneficial bacteria, it is concluded that the rapid decline rate and low EUR might be attributed to the potential formation damage caused by (1) the adsorption of high-weight big organic molecules (gellants and HPAM) on nanopores, (2) plugging of natural fractures, (3) plugging of propped fractures, and (4) pressure and energy loss while liquid flowing through the polluted zones. An advanced biotechnology is developed to unblock the contaminated zones by injecting microbial nutrients to the stimulated reservoir volume (SRV) to grow the indigenous beneficial microbes to degrade the residual fracturing fluid chemicals. The otherwise blocked flow paths are re-opened, and the trapped fluids (oil, gas, and water) can be mobilized, the residual oil can flow from the reservoir to the borehole with less pressure loss. Therefore, the objective of the field pilots of unconventional EOR is to create a more permeable SRV.
A ULTRSHALE™ process for unconventional EOR is developed and has been proven to be effective based on the laboratory study and field tests. One depleted fractured vertical well (used crosslinked guar-based fracturing fluid, at about 9,000 ft) and one depleting fractured horizontal well (used slickwater system, at about 9,900 ft) were selected as the field pilots of unconventional EOR in the Permian Basin. The laboratory data indicated that the indigenous beneficial microbes residing in the deep reservoir could be stimulated to degrade the fracturing fluid additives in the high-salinity produced water at an elevated temperature. The field implementation was carried by a Huff-N-Puff process. The post-treatment liquid production was uplifted by 40%-127% within 180 days, which means the otherwise polluted SRV was unblocked by the stimulated beneficial microbes. Furthermore, the eight-months incremental oil of the vertical well was about 1,500 bbls, the six-months incremental oil of the fractured horizontal well was about 12,000 bbls. The incremental of EUR of the fractured vertical and horizontal wells were 2,100 bbls and 25,000 bbls, respectively. And the EUR after the treatment is increased by 9-12%. The payouts for both treatments were from 2-4 months. The Rate of Return (ROR) for both pilots is more than 100%.
Frac-driven interactions (FDIs), more commonly known as frac hits, are becoming increasingly common as operators develop acreage near existing wells. These FDIs are commonly observed in an area of infill drilling in eastern Reagan County, Texas. To better understand their effects, a study was undertaken to document all FDIs observed during five years of field development in a fifteen-square-mile area. FDI frequency and intensity was found to be a function of (a) the parent well’s wellbore geometry, (b) offset direction between the parent and child well, (c) the presence or absence of a horizontal “buffer” well, and (d) distance between the parent and child wells. Horizontal parent wells received FDIs with greater frequency and intensity than vertical parent wells. Similarly, vertically stacked or directly offset parent wells received FDIs with greater frequency and intensity than indirectly offset or horizontally in-line parent wells. Horizontal parent wells commonly attenuate (or “buffer”) FDI frequency and intensity for other parent wells behind them (relative to the frac job). Distance between the parent and child well was found to have a strong negative correlation with FDI frequency and intensity but is more pronounced for vertical parent wells than horizontal parent wells. The majority of parent wells were found to receive either small FDIs or no FDI at all; thus, FDIs do not appear to pose a major risk to reserves within the study area contrary to many other unconventional plays. Although simple, the methodology was found to be a useful tool for understanding complex relationships between parent and child wells and may be applied to other development areas.
Meek, Robert (Pioneer Natural Resources) | Hull, Robert (Pioneer Natural Resources) | Woller, Kevin (Pioneer Natural Resources) | Wright, Brian (Pioneer Natural Resources) | Martin, Mike (Pioneer Natural Resources) | Bello, Hector (Pioneer Natural Resources) | Bailey, James (VSProwess)
Fluid and proppant are injected into a shale reservoir during a hydraulic stimulation, causing changes in rock properties. Over time fluid and pressure bleed off into the reservoir causing further changes. We measured these changes as well as the height of the hydraulic fracture at 1.5-hour intervals using single source point seismic recordings.
A distributed acoustic sensor (DAS) and pressure gauges were installed in a vertical well to monitor the hydraulic stimulation of several horizontal wells. In the vertical well we conducted microseismic recordings using geophones, tiltmeter measurements, strain measurements from DAS, distributed temperature sensor (DTS) readings, and several monitor walk-away time-lapse VSPs (vertical seismic profiles) along with repeated single offset source VSPs. The single source VSP was acquired every 1.5 hours over three days and was oriented so that the direct arrival passed through a single stage in one of the horizontal wells. We estimated the height of the p-wave velocity change due to the hydraulic fracture by measuring travel time changes in the direct arrival. The changes in height and velocity due to the deflation of the pressure over time was also measured. The fracture height was comparable with estimates from microseismic, DAS, and tiltmeters.
In this paper we describe a method to better highlight the geometry of altered rock from a hydraulic stimulation within the Spraberry Formation of the Midland Basin in West Texas. Pioneer Natural Resources is currently developing significant unconventional resources within the basin and methods like those noted here enable an understanding of fracture geometry and well interaction during hydraulic stimulation that are important in developing unconventional resources. By acquiring several different types of data, a more accurate picture of the fracturing process can be observed and field development and geomechanical models can be adjusted accordingly. The use of DAS/DTS fiber allows for a very cost-effective and rapid acquisition of vertical seismic profiles. Pioneer has used time-lapse, fiber-based VSPs in the past with good results (Meek, 2017). Meadows (1994) observed changes in travel time during a hydraulic fracture using geophones. Recently, Byerley et al (2018) described a time-lapse experiment to monitor a hydraulic fracture during each stage into a horizontal fiber. They observed that the time delay diminished over a few days. It is thought that this time-delay was caused by fractures opening during the completion and decreasing the velocity around the well bore. Fluid and pressure leaking off over time then results in an increase in velocity of the altered rock. Understanding this pressure build up and later diffusion is important to understanding the interaction of offset well fracture stages which may influence well spacing decisions. It is also useful in determining how long adjacent wells that were shut in during completion can be placed back on production. Beyond the use of microseismic, imaging the hydraulic completion from surface geophysical techniques has been challenging. As a result we have begun to utilize subsurface imaging techniques like VSPs to gain further insight into the dynamics of the stimulation. Here we demonstrate the usefulness of the VSP by recording data into the vertical fiber only. Unfortunately, with a horizontal fiber it is difficult to obtain the height and width of the fracture using reflection energy. Experiments are currently being conducted using downward continuation of reflection energy from horizontal fibers to image around the well bore (Fuller, 2019).
Cost-effective exploitation of heterogeneous/anisotropic reservoirs (e.g., carbonate formations) reckons on accurate description of pore structure, dynamic petrophysical properties (e.g., directional permeability, saturation-dependent capillary pressure), and fluid distribution. However, techniques for reliable quantification of permeability and hydrocarbon saturation still rely on model calibration using core measurements. Furthermore, assessment of saturation-dependent capillary pressure has been limited to experimental measurements, such as mercury injection capillary pressure (MICP). The objectives of this paper include (a) developing a new multiphysics workflow to simultaneously quantify rock fabric features (e.g., porosity, tortuosity, and effective throat size) and hydrocarbon saturation from integrated interpretation of nuclear magnetic resonance (NMR) and electric measurements, (b) introducing rock physics models that incorporate the quantified rock fabric and partial water/hydrocarbon saturation for assessment of directional permeability and saturation-dependent capillary pressure, and (c) validating the reliability of the new workflow in pore- and core-scale domains.
To achieve these objectives, we introduce a new multiphysics workflow integrating NMR and electric measurements, honoring rock fabric, and minimizing calibration efforts. We estimate water saturation from the interpretation of dielectric measurements. Next, we develop a fluid substitution algorithm to estimate the
The introduced multiphysics workflow provides accurate description of the pore structure and fluid distribution in partially water-saturated formations with complex pore structure. Moreover, this new method enables real-time well-log-based assessment of saturation-dependent capillary pressure and directional permeability (in presence of directional electrical measurements) in reservoir conditions, which was not possible before. Quantification of capillary pressure has been limited to measurements in laboratory conditions, where the differences in stress field reduce the accuracy of the estimates. We verified that the estimates of permeability, saturation-dependent capillary pressure, and throat-size distribution obtained from the application of the new workflow agreed with those experimentally determined from core samples. Finally, since the new workflow relies on fundamental rock physics principles, hydrocarbon saturation, permeability, and saturation-dependent capillary pressure can be estimated from well-logs with minimum calibration efforts, which is another unique contribution of this work.
A challenge in oil-reservoir studies is evaluating the ability of geomechanical, statistical, and geophysical methods to predict discrete geological features. This problem arises frequently with fracture corridors, which are discrete, tabular subvertical fracture clusters. Fracture corridors can be inferred from well data such as horizontal-borehole-image logs. Unfortunately, well data, and especially borehole image logs, are sparse, and predictive methods are needed to fill in the gap between wells. One way to evaluate such methods is to compare predicted and inferred fracture corridors statistically, using chi-squared and contingency tables.
In this article, we propose a modified contingency table to validate fracture-corridor-prediction techniques. We introduce two important modifications to capture special aspects of fracture corridors. The first modification is the incorporation of exclusion zones where no fracture corridors can exist, and the second modification is taking into consideration the fuzzy nature of fracture-corridor indicators from wells such as circulation losses. An indicator is fuzzy when it has more than one possible interpretation. The reliability of an indicator is the probability that it correctly suggests a fracture corridor. The indicators with reliability of unity are hard indicators, and “soft” and “fuzzy” indicators are those with reliability that is less than unity.
A structural grid is overlaid on the reservoir top in an oil field. Each cell of the grid is examined for the presence and reliability of inferred fracture corridors and exclusion zones and the confidence level of predicted fracture corridors. The results are summarized in a contingency table and are used to calculate chi-squared and conditional probability of having an actual fracture corridor given a predicted fracture corridor.
Three actual case studies are included to demonstrate how single or joint predictive methods can be statistically evaluated and how conditional probabilities are calculated using the modified contingency tables. The first example tests seismic faults as indicators of fracture corridors. The other examples test fracture corridors predicted by a simple geomechanical method.