Case studies can be instructive in the evaluation of other coalbed methane (CBM) development opportunities. The San Juan basin, located in New Mexico and Colorado in the southwestern U.S. (Figure 1), is the most prolific CBM basin in the world. It produces more than 2.5 Bscf/D from coals of the Cretaceous Fruitland formation, which is estimated to contain 43 to 49 Tscf of CBM in place. For a long time, the Fruitland formation coals were recognized only as a source of gas for adjacent sandstones. In the 1970s, after years of encountering gas kicks in these coals, operators recognized that the coal seams themselves were capable of commercial gas rates. CBM development benefited greatly from drilling and log data compiled from previous wells targeting the deeper sandstones and an extensive pipeline infrastructure that was built to transport conventional gas. These components, along with a U.S. federal tax credit and the development of new technologies such as openhole-cavity completions, fueled a drilling boom that resulted in more than 3,000 producing CBM wells by the end of 1992. The thickest Fruitland coals occur in a northwest/southeast trending belt located in the northeastern third of the basin. Total coal thickness in this belt locally exceeds 100 ft and individual coal seams can be more than 30 ft thick. The coals originated in peat swamps located landward (southwest) of northwest/southeast trending shoreline sandstones of the underlying Pictured Cliffs formation. The location of the thickest coals (Figure 1) coincides with the occurrence of overpressuring, high gas content, high coal rank, and high permeabilities in the San Juan fairway ("fairway"). The overpressuring is artesian in origin and is caused by water recharge of the coals through outcrops along the northern margin of the basin. This generates high vertical pressure gradients, ranging from 0.44 to 0.63 psi/ft, which allow a large amount of gas to be sorbed to the coal. Coal gas in the San Juan basin can contain up to 9.4% CO2 and 13.5% C2 . Chemical analyses suggest that thermogenic gases have been augmented by migrated thermogenic and secondary biogenic gas sources, resulting in gas contents ranging up to 700 ft 3 /ton. Coal rank in the fairway ranges from medium- to low-volatile bituminous and roughly coincides with those portions of the basin that were most deeply buried. Coals in the fairway typically have low ash and high vitrinite contents, resulting in large gas storage capacities and excellent permeabilities of 10 md from well-developed cleat systems.
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.
Shoemaker, Michael (Callon Petroleum Company) | Hawkins, James (Callon Petroleum Company) | Becher, John (Callon Petroleum Company) | Gonzales, Veronica (Callon Petroleum Company) | Mukherjee, Sandeep (Callon Petroleum Company) | Garmeh, Reza (Callon Petroleum Company) | Kuntz, David (Callon Petroleum Company)
E&P companies in the Permian Basin typically implement basin-wide development strategies that involve cookie-cutter type methods that use multi-well pads with identical geometric stage and cluster spacing. Such development strategies however fail to recognize and account for subsurface stress heterogeneity, and thus assume similar geomechanical properties that are homogeneous and isotropic which may cause well-to-well interference or “frac hits”, particularly near “parent” wells as fields continue to mature.
Minimum horizontal stress (Sh) is the leading parameter that controls hydraulic fracture stimulation, but is next to impossible to measure quantitatively, especially far field and in 3D space. In-situ stress differences from fluid depletion, combined with stratigraphy and subsequent mineralogy contrasts, control fracture containment vertically and laterally which define fracture propagation and complexity. Far field preference of virgin rock towards brittle vs ductile deformation is governed by mineralogy which defines the elastic moduli or geomechanical behavior of the rock. When integrated with pore pressure and overburden stress, the elastic rock properties are characterized by the Mechanical Earth Model (or MEM) which defines key inputs for calculating Sh using the uniaxial Ben Eaton stress equation. However, implementing this model historically produces incorrect calculated stress, when compared to field measured stress, due to an assumed homogeneous and isotropic subsurface.
Parameterization of fracture geometry models for well spacing, frac hit mitigation, and engineered treatment design in shale (or mudrock) requires an anisotropic in-situ stress measurement that accurately captures subsurface stress states. A method herein is proposed that achieves this using a modified version of the anisotropic Ben Eaton stress equation. The method calculates minimum horizontal stress by substitution of AVO seismic inversion volumes directly into the stress equation, replacing the bound Poisson's ratio term with an equivalent anisotropic corrected Closure Stress Scalar (CSS) defined in terms Lamé elastic parameters, specifically lambda (λ) or incompressibility and mu (μ) for shear rigidity. The CSS volume is corrected for anisotropy using static triaxial core, and is calibrated to multi domain data types including petrophysics, rock physics, completion engineering, and reservoir engineering (DFIT) measurements.
Successful application of said method in the Delaware and Midland sub-basins (of the greater Permian Basin) is shown. Anisotropic minimum horizontal stress (Sh) volumes from 3D seismic defined at 1 ft. vertical log resolution were interpreted quantitatively regionally, particularly as a prevention tool near parent wells prone to frac-hits. Moreover, the method provides an anisotropic measurement of in-situ stress variability (or stress differential) to qualitatively model 3D fracture geometries for engineered treatment optimization. Current stress modeling methods rely on the propagation of geomechanical properties from well control, which do not necessarily represent rock properties and stress states at the area of interest.
Jones, Drew (Deep Imaging) | Pieprzica, Chester (Apache Corporation) | Vasquez, Oscar (Deep Imaging) | Oberle, Justin (Deep Imaging) | Morton, Peter (Deep Imaging) | Trevino, Santiago (Deep Imaging) | Hickey, Mark (Deep Imaging)
We used a new, large-scale, surface-based, controlled-source electromagnetics (CSEM) approach to map the locations of frac fluid during flowback following a three-well hydraulic fracture stimulation in the Permian Basin. CSEM records and analyzes electric field signals induced in the electrically conductive frac fluids by a surface-based transmitter. For this study, we placed a grounded dipole transmitter directly above the central horizontal well of three parallel neighboring wells. The transmitted signal was a broadband pseudo-random binary sequence. To record the frac fluid response signal, we placed an array of 161 receivers on the surface covering the three horizontal wells. We recorded the induced, response signals of the flowback fluids in three-hour intervals (three on, three off) for 228 hours. The CSEM recording started eleven days after flowback began on the central well and four days after flowback began in the two outer wells. From this time-lapse recording we captured the spatial and temporal change in electrical conductivity within the fractured reservoir, allowing us to infer the location of flowback fluid and its movement. During the stimulations chemical tracers had been included in the frac fluid. Analysis of the tracers captured during flowback agreed well with the mapped fluid locations and movement found in the CSEM data.
Flowback monitoring and its interpretation offer another valuable tool for frac and reservoir engineers. This understanding is especially critical in developing and managing unconventional reservoirs. Here, the stimulation responses are not simple, more and more evidence show complex fracturing and complex fracture networks (e.g., Rassenfoss, 2018). Characterizing a fracture network or networks in shale (i.e., an unconventional reservoir) is a challenging task. It is complicated by multiphase and complex flow regimes, non-static permeability and porosity, natural fracture and flow systems, heterogeneities and complex stress, changing stress with production, liquid loading, and a host of operational concerns (Zolfaghari et al., 2016). In the past, to determine hydraulic fracture properties, operators used production data in a variety of models to manage wells and reservoirs. Garnering production data can take months or even years delaying, for example, upgrades to well and stimulation designs and designing infill drilling (Williams-Kovacs, Clarkson, & Zanganeh, 2015). In contrast, a flowback occurs during the transition between stimulation and bringing the well online. Understanding the flowback provides significant improvements in determining early production rates enabling estimates of the effective size of stimulations, distinguishing key reservoir properties, and predicting long-term production rates (Jacobs, 2016). In addition, there can be direct savings if, for example, flowback interpretation identifies an underproducing play in time to redirect funds into a more lucrative play before infill drilling (Williams-Kovacs et al., 2015).
Accurate and frequent mud checking is critical to optimum well construction. Proper assessment and management of drilling fluid properties such as density and rheology maintain the primary well control barrier and optimize fluid hydraulics and hole cleaning ability. However, a full mud check while drilling is typically done only once or twice a day. Moreover, the measurements are performed using antiquated equipment, with data quality and reliability that are highly dependent on the practicing mud engineer. Automated, continuous and practical drilling fluid monitoring is therefore needed.
In this paper, we introduce an automated mud skid unit (MSU) which performs continuous drilling fluid sampling and measurements at variable temperatures. The unit is able to provide the non-Newtonian rheological constants characterizing a Yield-Power Law (YPL) fluid as well as the real-time friction factor and critical Reynolds number using a pipe-viscometer measurement approach. Other important fluid properties such as pressurized-density, oil/water ratio and temperature are provided using high-quality in-line sensors. The unit is controlled by a programmable logic controller (PLC) coupled with a Linux operating system for data analysis. The system is able to send real-time data to WITSML data servers and provide detailed mud reports to engineers working either on-site or remotely.
The MSU was deployed in the Permian basin by an independent operator for automated mud monitoring during unconventional shale drilling operations. Rheology, density and phase content measurements were compared with conventional mud reports provided by the on-site mud engineer. Excellent accuracy was observed in mud rheology tests. The pressurized mud-density measurements provided by the MSU proved to be more accurate than non-pressurized mud balance measurements which were affected by mud aeration. Moreover, the MSU provided mud check data 25 times more frequent than those generated by the mud engineer at temperatures of 50°C and 65.5°C. Drilling fluid related issues such as chemical over-treatment as well as sudden changes in mud density, rheology and oil/water ratio were reported immediately to the drilling crew. This paper provides details about the measurement technology as well as the results from the field deployment of the MSU.
Bessa, Fadila (Occidental Petroleum Corporation) | Sahni, Vinay (Occidental Petroleum Corporation) | Liu, Shunhua (Occidental Petroleum Corporation) | Tan, Jiasen (Occidental Petroleum Corporation) | Frass, Manfred (Occidental Petroleum Corporation) | Kessler, James (Occidental Petroleum Corporation)
Understanding and modeling the interaction between hydraulic fractures and natural fractures is important to predict shale production performance. This paper presents a workflow that incorporates natural fractures, rock properties, and stress regimes to understand fracture behavior during stimulation treatment. The methodology also integrates the predefined discrete fracture network (DFN) and 3D reservoir properties to build a comprehensive hydraulic fracturing model. Heat maps are also generated to help evaluate completion design and well spacing strategies.
Applying the integrated fracture characterization workflow to the study area revealed that the vertical and lateral fracture growth is a function of structural context, stress conditions, and rock mechanical properties. Stimulation parameters, including proppant volume and injection pressures, for one horizontal and six vertical wells were utilized to build a comprehensive fracture network for the study area. The resulting model shows: (a) the stimulation of predefined natural fractures, and (b) the generation of induced fractures in the maximum stress direction associated with re-activation of pre-existing faults and fractures. The modeling results were validated by interwell interference data.
Fractures play an important role in hydrocarbon production from organic-rich shale reservoirs (Gale, et al., 2014). This is evident from the higher than expected production rates typically observed from low-porosity and ultra-low permeability shale rocks. Moreover, many shale outcrops, cores, and image logs show an abundance of natural fractures or fracture traces. This study integrates natural fracture characteristics, directional stresses, and hydraulic fractures to characterize and better comprehend Permian Wolfcamp production performance.
Several factors influence the stimulated rock volume (SRV) geometry during a hydraulic fracturing stimulation treatment. These factors include: structural context, natural fracture networks, rock mechanical properties, lithology, and stress changes associated with tectonic events (Gale et al., 2014; Maity, 2018). Furthermore, natural fracture systems in shales are heterogeneous; they can enhance or reduce formation productivity, augment or diminish rock strength, and may have a tendency to influence hydraulic fracture stimulation (Doe et al., 2013). The flow of stimulation fluid through natural fractures and the generation of hydraulic fractures were modeled in this study.
Dommisse, Robin (University of Texas) | Janson, Xavier (University of Texas) | Male, Frank (University of Texas) | Price, Buddy (The University of Texas at Austin) | Payne, Simon (Ikon Science) | Lewis, Andrew (Fairfield Geotechnologies)
Modern reservoir characterization approaches can be greatly aided by incorporating all available data and interpretations in a three dimensional geomodel. Our goal is to offer a regional perspective to augment the interpretations from local, field-scale 3D models developed by the industry. In this work we highlight the benefits of continuous development of the geomodel for the characterization of the facies architecture of an unconventional play.We generated a three dimensional, faulted Delaware Basin geomodel, containing over 1 billion cells, including stratigraphic, petrophysical, core description, and production data for the Bone Spring and Wolfcamp intervals. The model is based on over 7,000 correlated wells, 650 wells with facies interpretations and approximately 9,000 horizontal production wells with analyzed decline curves and completion data. Additionally, a high-quality 3D seismic volume in the northeastern part of the Delaware Basin reveals the complex stratigraphic architecture of key producing intervals in the Permian Basin. The 3D volume, combined with regional 2D seismic lines, enabled refining the interpretation of the stratigraphic architecture of the Wolfcampian to Guadalupian shelf margin. This allows us to relate the slope to basin strata imaged in the 3D seismic to the well-established stratigraphic architecture of the surrounding platforms. The 3D seismic volume reveals the seismic geomorphology of several key intervals. There are two areas of focus: 1) Testing of the facies model derived from log and core analyses using different deterministic and stochastic attribute distribution techniques; and 2) Exploring the influence of geological trends on productivity. This work demonstrates the value of a multiscale, regional perspective to the practice of 3D reservoir characterization in the Delaware Basin.
Hammon, Helen (Premier Oilfield Group) | Prather, Timothy (Premier Oilfield Group) | Rowe, Harry (Premier Oilfield Group) | Mainali, Pukar (Premier Oilfield Group) | Matheny, Mei (Premier Oilfield Group) | Krumm, Robert (Premier Oilfield Group)
The Latest Pennsylvanian and Early Permian (Wolfcamp, Dean, and Spraberry) interval of the Midland Basin, West Texas, represents a thick (often >1000 ft), mixed succession of shale, carbonate, and siltstone/sandstone lithologies that accumulated in a deep-water marine environment under variable hydrographic restriction. Because the succession is highly heterolithic, it is critical to understand and predict the stratigraphic and lateral variability in lithologic change and assess its impacts on reservoir properties. A highly-resolved (2-inch vertical) x-ray fluorescence-based chemostratigraphic study was undertaken on the Sun Oil D.E. Richards #1 drill core, recovered from Martin Co., TX. The core, while not continuous, contains “windows” of continuous sections of the upper Wolfcamp shale/siltstone through the lowermost Clearfork equivalent strata (Upper Leonard). XRF analysis for major and trace elements was conducted on the slabbed core face for 2567 sample intervals which were calibrated using a set of reference materials from a broad range of mudrock lithologies. In conjunction with XRF sampling, a subset of depth-matched sample powders (n = 229) was collected from the back of the core for mineralogical (XRD) and organic carbon analysis (LECO). A data refinement approach that incorporates elemental results from XRF and mineralogical results from XRD powders is developed to highlight element-mineral linkages and to establish a stoichiometry-derived mineralogy model from the 2-inch XRF data. The XRF-modeled mineralogy can be utilized to resolve sub-log-scale lithological variability and its impacts on rock strength, which are important characteristics to consider for completion optimization and overall drilling strategies in unconventional reservoirs.
Integration of XRD data with the 2-inch XRF data reveals that large-scale changes in elemental concentrations (%Al, Si/Al, %Ca, %Mg) can be interpreted as changes in mineralogical abundances of clays, quartz/clay, calcite, and dolomite, respectively. Furthermore, TOC values can be used to understand the organic variability present in each chemofacies found in this study. A discussion of the chemostratigraphy in the context of mineralogical changes, rock strength changes, and the selection of more detailed analyses (e.g., NMR, rock mechanics) will be undertaken.
Bryndzia, L. Taras (Shell International Exploration and Production) | Hows, Amie M. (Shell International Exploration and Production) | Day-Stirrat, Ruarri J. (Shell International Exploration and Production) | Nikitin, Anton (Shell International Exploration and Production) | Huvaz, Ozkan (Shell International Exploration and Production)
The Permian Delaware Basin (DB) is one of the most desirable regions for production of unconventional oil in the United States. While extended horizontal wells, stimulated with hydraulic fracturing, can recover economic volumes of oil in the DB, this production is often associated with large volumes of water. Relatively high water-oil ratios (WORs) can erode the value of producing wells. This of course begs the questions: where is the water coming from and why is so much being produced?
This study shows that the produced waters (PWs) are primarily in-situ Wolfcamp shale formation water and not water associated with hydraulic fracturing or well completions. This conclusion is based on the observation that the Wolfcamp shale formation water has an oxygen isotopic composition of ~6.5 ± 0.5 ‰ (SMOW) and a salinity of ~23 kppm. These oxygen isotopic data and salinities are consistent with illite-water equilibrium at peak burial conditions.
However, in some areas of the DB, PWs have much higher salinities (~50-125 kppm). The PWs also have a characteristic geochemical fingerprint of highly radiogenic 87/86Sr ratios of ~0.7085-0.7095. The source of this highly radiogenic strontium is believed to be the Salado salt in the overlying shallow Ochoan evaporites, with 87/86Sr of ~0.7090-0.7095. Dissolution of the Ochoan evaporites and salt is the likely source of high salinity brines in Guadalupian and Leonardian age sands and silts within the DB. These high salinity PWs are mixtures of Wolfcamp formation water and dissolved Ochoan evaporites and salt that infiltrated deep into the DB during uplift of the western edge of the DB. Uplift was closely related to the formation of the “Alvarado Ridge”, beginning at ~20 Ma, with peak uplift at ~7 to 4 Ma, creating conditions hydrologically favorable for ingress of the high salinity brines deep into the DB.
Due to the high illite content in the Wolfcamp shale, the shale-silt interface likely behaved as a clay membrane. Differences in salinity (up to ~100 kppm) between shales and sands/silts created gradients in ion and water activity (aw) across the interface. These gradients resulted in the diffusion of ions from high salinity sands/silt (low aw) into adjacent shales with high aw and low salinity. Where shales have not equilibrated with high salinity sands/silts, the water saturation (Sw) in the Wolfcamp shale would remain high and the resultant WOR would also be high. The ion diffusion model predicts co-current flow of oil and water out of the shale. This may explain why oil production in the DB produces so much water.
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%.