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Over the past twenty-five years, more than 3,500 wells have been drilled in the giant Pinedale Field in the northern Green River Basin of Wyoming, at spacing intervals as tight as 5-acres and completed in the 6,000 ft. reservoir column of stacked, tight-gas, fluvial sandstones. Even with this high density of well control, geologic uncertainties remain regarding the geometry and architecture of the highly heterogeneous fluviatile basin-fill. The goal of this project was to predict the distribution and size of the reservoir facies using geocellular-modeling techniques.
A process-based depositional framework formed the starting point for our characterization study. Examples from modern analogs and the rock record were used to condition the model inputs as related to channel size, scaling relationships (including net/gross), and overall reservoir architecture; the fluvial depositional sequences comprise a distributary fluvial system. At a range of scales, a seismic inversion facies volume, supplemented with a dense population of well logs, and core data helped constrain the size, geometry and distribution of reservoir facies at multiple, geologically distinct intervals. The resulting geocellular model honors all input data. Vertical upscaling is primarily constrained by well logs and core. Lateral facies distributions are primarily constrained by the seismic inversion column paired with well data.
By combining sedimentologic interpretations from seismic and well logs, this integrated study was able to differentiate fluvial reservoir sandstones from overbank siltstones and mudstones. This technology-driven reservoir characterization study was undertaken to improve our understanding of resource-in-place and to optimize wellbore placement and construction, for ongoing field development.
Pinedale Field is defined largely by the Pinedale Anticline in the northern part of the Green River Basin in Sublette County, Wyoming and is approximately 35 miles long with a NNW trend (
Production underperformance of a historical infill (child) lateral well was confirmed by observation and modeling to be due to offset vertical well interference. These results led to utilizing a seismic-driven earth model, three-dimensional hydraulic fracture, and reservoir models for a planned horizontal well. The goal was to apply past learnings to maximize completion potential and understand the economic viability of infill horizontal well development in the Greater Green River Basin. The results of this study provided insight to determine future horizontal development strategy.
In-situ model input parameters along with field-scale structure were informed by 3D seismic and vertical log data. Parameters were further calibrated to core and offset well DFIT’s with subsequent treatment history matching validation. Modeled fracture geometries were incorporated into a reservoir simulator to history match parent well production. This exercise provided an accurate representation of pressure depletion and stress profiles around the planned horizontal child well. Additionally, this provided a platform to investigate potential completion strategies, landing zones, and a subsequent production assessment based on uncertainty analysis to determine economic potential.
Targeting a deeper landing location compared to the previously drilled horizontal well resulted in reduced expected interaction with offset wells. Hydraulic fracture design sensitivities indicated child well frac hits and asymmetrical fracture growth can be mitigated or lessened with increased intra-stage cluster count and efficiency to prevent "super frac" generation.
An assessment based on fracture model sensitivity results were coupled with reservoir uncertainties to forecast production. Simulation indicated that the most significant impact on production was a result of porosity, saturation, and permeability assumptions. Two separate models were developed, one based on log derived properties and the other being inferred from core properties and assigned to facies from Gamma Ray. The objective of the stimulation was to maximize hydraulic fracture flowing area with fluvial sand bodies while minimizing cost. Increased sand loading was thought to be the primary driver. The simulation showed that increasing sand loading from 1000 lb/ft to 1500 lb/ft only generated an incremental 0.2 Bcf indicating the lower amount of sand is the economical choice. Capital savings were generated by increasing the stage length while maintaining cluster efficiency reducing stage count by 5. However, even with the capital savings, forecasted production scenarios averaged around 7.15 Bcf missing their economic breakeven. As a result of this work, the decision was made not to drill the well and instead explore alternative prospects for horizontal development.
Gaddipati, M. (NITEC LLC) | Firincioglu, T. (NITEC LLC) | LaBarre, E. (ULTRA Petroleum) | Yang, Y. (ULTRA Petroleum) | Wahl, D. (ULTRA Petroleum) | Clarke, P. (ULTRA Petroleum) | Long, A. (ULTRA Petroleum) | Ozgen, C. (NITEC LLC)
In recent years multi-stage fractured horizontal wells have become a norm in the development of unconventional oil and gas reservoirs. This paper focuses on reservoir modeling of the tight-gas sandstones in Pinedale Field, Green River Basin, Wyoming. This paper represents the first published literature to focus specifically on horizontal well performance in Pinedale. The objective of this study was to evaluate horizontal well productivity of the hydraulically fractured Lance Pool formation. Due to the fluvial nature of the formation and the complexity introduced by the hydraulic fracturing, an integrated workflow was developed utilizing a 3D simulation model combining seismic reflection, inversion, petrophysical and geological data.
A 3D facies model based on object-oriented geostatistical modeling was constructed using a combination of vertical lithology proportion curves (from vertical pilot wells) and reservoir net-to-gross (NTG) maps extracted from a deterministic seismic inversion volume. The NTG maps were honored during the geostatistical population of the fluvial sand bodies (sand generation model). The resultant facies model was then populated with petrophysical and geomechanical properties using the interpreted well logs. The final integrated model honors published characteristics for the Lance Formation. A dual-porosity reservoir simulation model was then utilized. The reservoir simulator integrated the hydraulic fracturing process, multi-phase flow and geomechanics in order to assess SRV generation during hydraulic fracturing and SRV geometry changes during production. The change in mean stress for each grid cell was implicitly solved with pressure and the other flow variables using poro-elastic information. The simulation model was calibrated to history match flow back and depletion periods including historical gas, oil (condensate) and water production rates together with the bottom hole pressure values.
A physics-based history matched simulation model was generated, including flow behavior for two wells in the study area. The hydraulic fractures created/propagated for sandstone and siltstone were tuned as history matching parameters. The calibrated model showed that major pressure depletion is limited to the sand channels due to ductility contrasts with the finer-grained facies. Predictive cases were modeled for 30- year EUR. The study refined our understanding of well performance drivers as related to advanced reservoir characterization, affording a robust prediction tool for undrilled locations.
The integrated reservoir modeling technology presented in this study is impactful as it solves for geomechanics and flow in a single process. The multi-well calibration of the model provides physics-based assessments of gas production from a complex reservoir, leveraging horizontal well technology. Predictive cases illustrate a quantitative performance characterization tool for decision making, including field optimization and development.
To include the all the complexities associated with the reservoir coupled with hydraulic fracturing of horizontal wells, this study required a thorough integration of different disciplines from geology, petrophysics, geophysics, geomechanics and engineering in building a 3D reservoir simulation model. All the available data from different disciplines was analyzed and integrated to a create a consistent physics-based model.
Proppant diagenesis occurs when minerals form on the proppant surface and/or around the embedment crater at high-temperature and/or high-stress conditions (Weaver et al. 2005). It has been used recently to explain low fracture conductivity in the field as well as the long-term downward trend of laboratory-measured American Petroleum Institute conductivity data (Liang et al. 2015). However, researchers disagree about the source of such overgrowth minerals and the involvement of proppant in the process. In addition, the diagenesis process has not been investigated in the case of carbonate-rich shale formations. Therefore, the objectives of this paper are to experimentally investigate the proppant diagenesis process during hydraulic fracturing of the Eagle Ford Shale Formation and to determine the role of the proppant in the process.
Diagenesis was studied after aging a mixture of proppant and formation samples in deionized water for 3 weeks at 325°F and 300 psia. Outcrop cores of the Eagle Ford Shale Formation were crushed and sieved to 50/100 US-mesh size. The ceramic, sand, and resin-coated-sand (RCS) proppants of 20/40 US-mesh size were tested. The proppant surface was studied for mineral overgrowth and/or dissolution before and after aging using scanning electron microscope (SEM) with energy-dispersive X-ray spectroscopy (EDS). The concentration of the cations leached into the solution was measured by analyzing the supernatant samples using inductively coupled plasma (ICP)/optical-emission spectroscopy, while the sulfate-ion concentration was measured using a spectrophotometer. The proppants and the Eagle Ford Shale Formation samples were analyzed after aging separately at the same conditions to explain the sources of the leached ions and the observed overgrowth and/or precipitated minerals.
The Eagle Ford Shale was found to be the source of calcium sulfate and calcium zeolite precipitates because of dissolution/precipitation reactions with water. Only the ceramic proppant was found to induce an additional mineral overgrowth of iron calcium zeolite on its surface. Conversely, the sand and RCS proppants did not encounter any precipitates/overgrowth minerals. These proppants only changed the elemental composition of the precipitated zeolite from the formation/fluid interaction, showing increased silicon and decreased calcium and aluminum concentrations. The proppant dissolution was observed with all types of proppants, as indicated by the presence of silicon ions in the solution after aging. A thermodynamic modeling study was conducted and confirmed the possibility of formation of the observed precipitate and overgrowth minerals at the equilibrium state of the rock and proppant mixture in water. Finally, the breaking and peeling of the phenol formaldehyde resin from the RCS proppant particles at static conditions was observed for the first time (to the best of the authors’ knowledge) using the SEM technique.
The study contributes to the understanding of the scale formation and the mechanisms that damage fracture conductivity in the Eagle Ford Shale. Results impact the choice of fluid and proppant for fracturing optimization and long-term production sustainability in the Eagle Ford Shale reservoirs.
When analyzing gas production from Green River Basin vertical wells in western Wyoming, geomechanical log curves have proven to be superior at predicting production performance than gamma ray alone. Production logs showed many “clean” sandstones that were thought to be of high quality by their gamma ray response were underperforming. Conversely, higher gamma ray sections of the reservoir were contributing or outperforming expectations. The discrepancy is associated with the basin's fluvial geologic environment. An alternative method was, therefore, required to grade reservoir quality independent of gamma ray response.
Acquiring advanced logs on every well to determine porosity and reservoir quality is time intensive and uneconomical in many mature dry gas fields. A new technique was developed using geomechanical properties derived from drill bit vibrations to create a supervised mechanical facies model specific to the Lower Lance Pool (LLP).
Continuous, high-resolution measurements of drilling-induced vibrations were obtained in several dozen vertical wells in the region. Data collected were used to provide stiffness coefficients and determine geomechanical properties including Young's modulus and Poisson's ratio.
The geomechanical curves were compared to offset data to create a supervised mechanical facies model related to porosity, permeability and Vclay. The calibrated model was applied to all legacy vertical wells with drill bit vibration data and LLP completions. The model was applied to several new vertical wells to assist in the completion strategy. Production was logged to validate the mechanical facies model's ability to predict production.
The mechanical facies defined several potential horizontal landing zones in a pilot well drilled through the LLP. The model was then applied to the lateral section and used to stage the well by grouping similar facies together within a stage, thus minimizing heterogeneity and optimizing perforation efficiency.
Production logs showed the mechanical facies identified producible and non-producible reservoir independent of gamma ray measurement. Vertical wells where geomechanical data were used to target mechanically favorable rock outproduced offset wells by ~20% in the LLP. The mechanical facies model determined the landing zone for the operator's first horizontal well in the LLP. The model was also applied to the lateral section to more intelligently implement a geomechanically informed completions strategy.
Differentiating high- and low-delivery reservoir without the deployment of advanced logging suites is operationally and economically more efficient. A supervised mechanical facies model can be calibrated with supporting data and then applied to future wells by solely recording and analyzing drill bit vibration data. Wells can be completed in a geomechanically-informed fashion leading to better production and more economic completions.
Plunger lifted, and free-flowing gas wells experience a wide range of issues and operational inefficiencies such as liquid-loading, downhole and surface restrictions, stuck or leaking motor control valves, and metering issues. These issues can lead to extended downtime, equipment failures, and other production inefficiencies. Using data science and machine-learning algorithms, a self-adjusting anomaly detection model considers all sensor data, including the associated statistical behavior and correlations, to parse any underlying issues and anomalies and classifies the potential cause(s). This paper presents the result of a Proof of Concept (PoC) study conducted for a South Texas operator encompassing 50 wells over a three-month period. The results indicate an improvement compared to the operators' visual inspection and surveillance anomaly detection system. The model allows operators to focus their time on solving problems instead of discovering them. This novel approach to anomaly detection improves workflow efficiencies, decreases lease operating expenses (LOE), and increases production by reducing downtime.
Proppant diagenesis has been introduced recently as a damaging mechanism to the fracture conductivity in shale formations. The mechanism was used to explain the low values of the field-measured fracture conductivity as well as the long-term decline of the lab-measured API conductivity data. Previous studies revealed the presence of a diagenetic overgrowth on the proppant surface and around the embedment crater after being exposed to high-temperature and/or high-stress conditions. The objective of this paper is to experimentally investigate the diagenesis of bauxite proppant in calcite rich Eagle Ford shale fractures.
The interaction between the proppant and the formation was studied by aging its mixture in a deionized water for prolonged period of time at elevated temperature of 325°F to accelerate the involved reactions. Aluminum-based bauxite proppant of 20/40 mesh-size was mixed with a crushed Eagle Ford shale sample of 50/100 mesh-size. The mixture was aged at 325°F and 300 psia for three weeks. The surfaces of the proppant and the formation were examined for mineral overgrowth and dissolution using scanning electron microscope (SEM) with energy dispersive X-ray spectroscopy (EDS). The supernatant fluid was analyzed for cations’ concentrations using inductively coupled plasma (ICP) and the sulfate ion concentration was measured using a spectrophotometer. The proppant and Eagle Ford formation were then aged separately at the same conditions to explain the sources of the leached ions and the observed overgrowth materials.
The results show the diagenetic activity that could result from the use of bauxite proppant in Eagle Ford shale fracturing. The ICP results indicated the potential dissolution of the proppant at high temperature. The observed overgrowth materials were identified as calcium sulfate, calcium zeolite, and iron-calcium zeolite. The calcium sulfate was found to be explicitly sourced from the Eagle Ford dissolution-precipitation mechanism. The SEM/EDS results indicated the presence of calcium zeolite after aging both cells: the proppant/formation mixture and the formation alone. The iron-calcium zeolite was found on the proppant surface as a result of the fluid/proppant/shale interactions.
The study contributes to the understanding of the damaging mechanisms to the fracture conductivity in the Eagle Ford shale formation. Results impact the choice of proppant and fluid for fracturing optimization and long-term production sustainability in the Eagle Ford shale reservoirs.
Ledgerwood III, Leroy William (Baker Hughes Incorporated) | Spencer, Reed W. (Baker Hughes Incorporated) | Matthews, Oliver (Baker Hughes) | Bomidi, John A.R. (Baker Hughes Incorporated) | Mendoza, Jorge (Baker Hughes) | Hanson, Jonathan M (Consultant)
The oil-and-gas drilling industry has developed a large body of knowledge about methods for drilling directional wells with steerable motors. Experience indicates that more-aggressive drill bits are harder to steer. This is commonly attributed to the fact that bits with higher aggressivity produce larger torque changes for a given change in bit weight. The actual mechanics, however, of tool-face disorientation during slide events is poorly understood. This paper reports on tests conducted on a full-size drill rig aimed at understanding the mechanics of tool-face control. Tool-face orientation and other data were measured downhole at 100 Hz. Nine different bits ranging from polycrystalline diamond compact (PDC) to hybrid to roller-cone bits were tested on an adjustable kick- off (AKO) motor bottomhole assembly (BHA) in slide mode. These tests confirm the common industry notions about the effect of aggressivity on tool-face control. They also show that angular motion of the BHA while sliding is overdamped. Toolface orientation consequently follows the average of the torque signal generated by the bit. Furthermore, the tool-face orientation is more easily disoriented by a torque signal at a frequency near to or less than the torsional natural frequency of the drillstring. PDC bits excite this more readily than bits with rolling cones. We also identify a tool-face disorientation anomaly that we call a fast torque anomaly (FTA). FTAs occur because the bent motor/AKO has a preferred angular orientation in the borehole. FTAs have not been previously recognized, probably because they are not identifiable in mud-pulse signals. A BHA suffering FTAs would simply appear as a chaotic and profound loss of tool-face control in mudpulse data. Hybrid and roller-cone bits caused fewer FTAs than PDC bits.
The Raageshwari Deep Gas Field (RDG), Barmer Basin, India, is a thick ( 700m gross), low permeability (0.01-1md) gas condensate field comprised of clastic and volcanic reservoirs at 3,000m depth. The volcanic reservoirs consist of a stacked succession of thick, heterogeneous, low net-to-gross lava flow cycles of Basalt and Felsic units. RDG was initially developed as the fuel source for oilfield developments in the Barmer Basin RJ-ON-90/1 block; however, with improved technology and accelerating worldwide development of tighter reservoirs, it is now feasible to commercially exploit such fields. Early RDG production performance encouraged us to revisit the field development for the possible commercial exploitation of gas and condensate. One key challenge in the development planning of any reservoir is the creation of useful production forecasting models. An updated 3D geocellular model was developed using all available geophysical, geological and petrophysical information to capture the heterogeneity in the sandstone and volcanic reservoirs. A dynamic simulation model was then calibrated to more than four years of production data, pressure transient and interference tests, and time-lapsed production logs. This model was used to determine a range of feasible scenarios to consider for field development. Based on the early RDG production performance, additional data acquired over the last four years and the static and dynamic modeling results, a revised field development plan for RDG commercial gas sales was recently approved by the Government of India.
We shall discuss the following objectives: the use of Multivariant Analysis (MVA) to identify and classify important performance variables implemented in the hydraulic fracture treatment strategies. We shall discuss field optimization workflows initially performed in the Pinedale asset in Wyoming. Data were collated from multiple fluvial sand layers that aggregate across the anticline structure under study. Initial exploratory data analysis and bivariate analyses fell short of a comprehensive appreciation of the multivariate, stochastic and multivariant nature of this complex heterogeneous system. The MVA approach addressed the complexity "inherent in the data's coincident variation in multiple parameters. Data clustering was used to create different models and assess different parameters. Models were able to identify the relative impact of the most significant variables affecting stage production performance, and develop probability distributions for potential outcomes at different categories of production. A neural network was chosen to evaluate both reservoir parameters as well as variables that are controlled by the operator such as proppant volume and flowback methods."
"Evaluation was conducted on 195 stages of which 49 were identified as candidates for increase in proppant volume. Through this process the authors identified a need to update the model to include the impact of pressure depletion from down spacing. Even in the absence of accounting for pressure depletion the team experienced excellent results."
The goal is to design as efficient a completions strategy as possible across the anticline as more wellbores are drilled. Capturing the knowledge garnered from the geological parameters to maximize reservoir contact and the proppant volumes deemed appropriate across each stage of the wellbore, it is feasible to implement a function that identifies the values of operational parameters to maximize production. We can also identify which stages are most productive and shut down those stages that are under performers to reduce operational expenditure.