How to get the most out of your multi stage unconventional fracture design

Transcription

1 WHITE PAPER How to get the most out of your multi stage unconventional fracture design Author: Robert F. (Bob) Shelley

2 HOW TO GET THE MOST OUT OF YOUR MULTI STAGE UNCONVENTIONAL FRACTURE DESIGN A number of often intertwined issues can complicate the effective design of a hydraulic fracture program, and in the process, restrict maximum reservoir drainage and returns from multi fractured horizontal shale and equally low permeability formations. However, as we demonstrated in an in depth engineering evaluation of a three well pad in the Utica/Point Pleasant unconventional play, largely underutilized analytical methodologies, such as production history and frac pressure matching, open the door for alternative completion designs that deliver more uniform fracture coverage with corresponding increases in production and economic returns. The detailed evaluation included calibration of a 3 D frac model by frac pressure matching; use of a numeric reservoir simulator for multi phase production history matching; and estimated fracture conditions over time as the wells are produced. The evaluations concluded that completion, frac design, operational and production issues individually or collectively meaningfully influence the production and economics of multi stage horizontal assets. The bottom line: Well recovery can be improved considerably with more effective frac designs that generate a larger effective frac area. 1 THE FIELD LAB Classified as dry gas producers, the three wells were drilled and completed from a single pad in the frequently stacked Utica Shale/Point Pleasant formation. The underlying Point Pleasant formation, described generally as a calcareous organic rich limestone shale conglomerate, 2 was the horizontal target for each of the direct offsets (designated Wells A, B and C) at depths of ±10,000 ft. The trio was drilled in an identical Azimuth direction, with Well B landed between the other two, and, for the most part, stimulated with a similar hybrid frac fluid design. Tables 1 summarize the respective frac/completion designs and treatment/pressure rates. All frac stages in Well A were completed as designed, while adverse stimulation pressure response forced those along the slightly longer laterals of Wells B and C to deviate from plan. 1. Robert Shelley PE, Koras Shah, Nijat Guliyev, Stan Sheludko, Amir Mohammadnejad; StrataGen, Is Pumping Larger Volume Sand Treatments Sustainable?, SPE 17463, Wickstrom, L.H., Gray, J.D. and Stieglitz, R.D., Stratigraphy, structure, and production history of the Trenton Limestone (Ordovician) and adjacent strata in northwestern Ohio: Ohio Division of Geological Survey Report of Investigations, 1992 No. 143, 7 p.

3 The average treatment rate of the wells varied, with Well C exhibiting a significantly lower rate, which was attributed to the higher injection pressures during treatment. The average pressure/average rate was calculated for each well, with a higher value corresponding to increased treatment difficulties. Well A B Prop Description Resin Coated Sand (RCS) Sand Ceramic (LDC) Sand Prop Wt. Fluid Volume (MM gal.) Lateral Length (ft.) Frac Stages Average Rate (BPM) Pressure/Rate (psi/bpm) , , C Ceramic (LDC) , Table 1: Frac and Completion Summary Myriad data were used in evaluating the performance of the studied wells, including: Daily Production Data Daily Operation Report Logs Completions Procedure Reports Post Frac Reports Mechanical Properties Log Geosteering Charts Digital Fracture Treatment Data Stimulation Invoices From this and other data, we were able to identify the treatment difficulties and begin to look at the overall completion effectiveness of the three wells. TREATMENT EFFECTIVENESS The individual frac stages in each well were evaluated to ascertain the treatment difficulties encountered, based on four categories, ranging from completed per plan with no resulting issues, to "not completed" with minimal proppant placed. Increasing pressure in some stages required design alterations, while others were completed as designed. Figure 1 is a color coded plot of the treatment difficulties encountered in each frac stage of the three wells. As mentioned, higher pressure/rate average values correlate to more treatment difficulties, which is clearly evident in Wells B and C where only a cumulative 20 stages were completed with no issues.

4 Fig. 1: Treatment pressure response summary PROPPANT TYPE, DISTRIBUTION As pointed out in Table 1, the individual wells were completed with different proppant types, but as detailed in Table 2, the total volumes, likewise, differed significantly. Well B, for example, used the most proppant, split nearly evenly between white sand and low density ceramic proppant (LDC). The sieve distributions and median particle diameters for the proppant used were also considered. Though the median diameter of the ceramic proppant are larger than those of white sand or resin coated sand (RCS) for the same mesh size classification, the size differences did not immediately explain the aborted frac treatments on wells B and C where high treatment pressure issues were experienced before any of the proppant reached the formation. It is reasonable to lay blame on near wellbore tortuosity associated with fracture initiation and propagation. Thus, in retrospect, we believe well C would have benefited if the initial stages used a combination of smaller proppant to condition the fracture, a more viscous frac fluid to mitigate the apparent tortuosity issues and/or increasing the treatment rate per perforation cluster. Well 100 mesh 30/50 White 30/50 RCS 20/40 RCS 30/50 LDC 20/40 LDC Designed Prop Placed A % B % C % Table 2: Breakdown of proppants placed in zone for each well

5 PUTTING THE DATA TO WORK All of the gathered well and treatment data were encapsulated in frac models and other state of the art evaluation methodologies, with the ultimate objective of providing insight into designing an effective hydraulic fracturing design that would deliver higher long term production and economic returns. 3 D FRACTURE MODELING Using an analysis of a mechanical properties log, all of the treatments were modeled using a 3 D fracture model generated through FRACPRO fracture design modeling software package. The same model and parameters were used consistently on all three wells. Fracture propagation from each cluster in every stage was evaluated and modeled. Once a pressure match was achieved the fracture geometries were estimated for each cluster, as shown in Fig. 2. Fig. 2: The 3 D fracture wellbore diagram showing the frac geometry along the lateral of the three wells From the model, it is clear that the treatments in Well A delivered extremely uniform geometry, when wells are treated with no operational/completion issues and each frac stage has normal and similar treating pressures and injection rates. Conversely, Well C and, to a lesser degree, Well B, exhibited varying geometries with numerous sections along the respective lateral having zero propped fractures. From this data, we estimated the number of propped fractures for each well, based on frac pressure response, which was also taken into account for the subsequent production history matching. Notably, a number of parameters in fracture and reservoir modeling, including reservoir anisotropy and fracture interference (stress shadowing), adds layers of complexity and uncertainty with few constraints. Therefore, if the proppant volume was less than 10,000 lb/ cluster with a very small fracture size, that particular frac stage was not considered to be a significant contributor to production. Moreover, for all the treatments that screened out early, the cluster efficiency was reasonably estimated at 60%, effectively reducing the number of fractures propagated. As for all important average conductivity (proppant permeability and propped width), Well B, owing to its mixture of ceramic and sand proppant, volume and concentration (Table 1), was shown to deliver the highest values. Well A exhibited the lowest average conductivity, while Well C fell slightly below Well B.

6 FRACTURE DEGRADATION OVER TIME We also looked at fracture integrity as the well is produced. Basic rock mechanics hold that the stress the formation places on the proppant is a function of the formation closure stress and the bottomhole flowing pressure. In practice, and depending on how the well is produced, increasing drawdown, in turn, increases the stress on the proppant over time, as illustrated by the flowing pressure stress relationship of Well B (Fig. 3) Actual Flowing Pressure (psi) Stress on Proppant (psi) Producing Time (Days) Fig. 3: Well B production time compared to well flowing pressure and calculated stress on the proppant Here, we see early time stress on proppant of roughly 2,000 psi; however, as production approaches 200 days, reduced flowing pressures caused by production drawdown allows the stress on proppant to exceed 7,000 psi. Conductivity measurements have verified that stress swings of this amplitude have a profoundly adverse impact on proppant permeability (fracture conductivity), which subsequently reduces the effective fracture length, area and overall effectiveness. PRODUCTION HISTORY MATCHING Using a numerical production simulator, we conducted a production history match (PHM) of the three offset wells, using reservoir, completion, drilling and regional data collected as part of the detailed evaluations. The aim was to calibrate the reservoir model to actual well production by basically matching all phases of the reservoir and completion simultaneously over the entire production history of the well. Daily bottomhole flowing pressures were calculated for 200+ days of production history, using surface flowing pressures, production tubular internal diameter (I.D.), well bore architecture, reservoir temperature and assumed pressure volume temperature (PVT) data. The estimated pressures were used as a constraint for the PHM process, while an initial estimate of pore pressure and permeability of the producing zone were obtained from area experience and measurements made during the horizontal well construction process. Formation thicknesses were estimated from

7 geo steering interpretation and nearby well log analysis. Meanwhile, connate water saturation and porosity of all zones were determined from geologic data. Relative permeability of all phases were calculated using the exponent value 2, while a PVT model for reservoir fluids were determined using correlations in the absence of actual PVT data. As an effective PHM required, we use multiple flow periods with reduced fracture dimensions, three flow periods were used for Wells A and B while two flow periods were used for Well C. An effective fracture area (EFA) was calculated for each flow period, defined as the product of the PHM total fracture length, height and the number of fractures. Well A exhibited an EFA reduction of 65% and a calculated 0% reduction in effective fracture conductivity. The EFA and effective fracture conductivity of Well B was reduced to 60% and 72% respectively. Well C had a 44% EFA and 46% effective fracture conductivity reductions. The rate and cumulative gas production matches for all three wells are shown in Fig. 4 6, with the calculated daily and cumulative gas production rates depicted on the left and right corners, respectively. The red dots represent actual data, while the black dots represent our modeled data. Fig. 4 Well A PHM gas rates, cumulative and flowing pressures

8 Fig. 5 Well B PHM gas rates, cumulative and flowing pressures Fig.6 Well C PHM gas rates, cumulative and flowing pressures FRACTURE EFFICIENCY EVALUATION As emphasized, the amount of fracture area that contributes to well production which can be calculated from the fracture characteristics determined from the PHM, is critical to the overall success of a hydraulic fracturing program. A fracture efficiency can be determined by dividing the effective area determined from the PHM by the 3 D fracture model propped area. From these calculations, we determined that based on the eight cumulative flow periods from the three wells, fracture efficiencies ranged from a high of around 13% to a low of 4%. A comparison of the effective fracture conductivity to fracture efficiencies are shown in Fig. 7. As can be seen, the data from these wells support the proposition that fracture conductivity has a direct bearing on fracture efficiency which is the portion of the propped fracture area that contributes to well production. By definition fracture conductivity can be increased either through higher proppant permeability (proppant selection) or increasing

9 propped width or both. So in effect, fracture effectiveness can be improved not only though better fracture conductivity and efficiency, but also by increasing the propped area with larger treatment volumes. Furthermore, as detailed in Fig. 7, over time fracture degradation due to increased stress which is caused by production drawdown can have a significant impact on fracture efficiency, effectiveness and well recovery. This effect can be reduced through selection of stronger proppant and/or with proper production management practices. Fig. 7: The relationship of effective fracture conductivity to fracture efficiency. Note that all of the data fall on the same trend line with the early production data plotting on the upper right and later data on the lower left. THE CASE FOR ALTERNATE FRAC DESIGNS So, how can all this be used to forecast the production achievable by altering your hydraulic fracturing design? First, we considered information obtained from the performance evaluation of the three offset wells: The RCS white sand tandem; the LDC sand combination; and the small volume ceramic (LDC) treatment. Frac modeling was then performed to estimate the propped area, length, height and conductivity for four alternative hypothetical frac designs. For consistency, the reservoir and completion characteristics from Well A was used to forecast production for the frac design scenarios. For each of the hypothetical frac designs, the correlation in Fig. 7 and a conductivity scaling factor determined from production history and frac pressure matching were used to estimate effective fracture characteristics from the frac model geometry. This calculation was performed as part of the production forecasting for each of the hypothetical frac designs. From this, we generated production forecasts for each of the four frac designs, using a baseline well with a 5,00 ft lateral completed with 24 frac stages and five perforation clusters/stage. As shown in Fig., the ceramic white sand frac design would produce 7.3 BCF of gas after five years of production, followed closely by the large volume sand

10 treatment at 6. BCF. The smaller volume Sand treatment would produce the least volume of gas (5.6 BCF) over five years. Fig. Forecasted well production for the four hypothetical frac designs As these results clearly bear out, well recovery can be significantly improved with more effective frac designs that result in greater effective frac area. As reflected in the LDC Sand design, frac effectiveness and efficiency is improved though greater proppant permeability. On the other hand, a Large Sand treatment could improve frac effectiveness through the increased propped frac width and area, thereby improving stimulation effectiveness. Hand in hand with forecasted production, we also conducted an economic analysis of the four hypothetical frac jobs. While the LDC Sand and Large Sand designs are by far the most effective, they likewise come at higher costs. The ceramic sand design, in today's frac costs, would cost $130,000 more/well, but would produce an incremental 0.5 BCF of gas, generating $1.27 million more value after five years of production than a Large Sand design. What's more, the smaller treatment volume significantly reduces the environmental footprint with 34% less water and 43% less proppant. LESSONS LEARNED The detailed engineering evaluation confirmed many long held assumptions on the many factors that come into play with key roles in designing more effective frac treatments. As demonstrated, treatment volume, proppant selection, fracture spacing, perforation cluster efficiency, and treatment rate all contribute to maximum recoveries in multi stage hydraulic fracturing programs. Thus, as the three well performance evaluations suggest, ample opportunities exist to improve well production and economic returns in the deep Utica/Point Pleasant and similarly tight formations through more effective frac designs.

11 ABOUT THE AUTHOR ROBERT F (BOB) SHELLEY has 39 years of experience with hydraulic fracture design, execution and evaluation. Currently he currently is the Director of Well Performance Evaluation for STRATAGEN based in Houston. In this position Bob leads a team of hydraulic fracturing, reservoir and data modeling experts. He has authored 30+ SPE papers, patents and served as an SPE Distinguished Lecturer. Bob holds a BS degree in Civil Engineering from Colorado State University and is a Registered Petroleum Engineer in Texas and Colorado. Prior to joining STRATAGEN in 2010, Bob worked for Halliburton, RTA LLC and Landmark.

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