Experiences in the Development of Shale Gas

Experiences in the Development of Shale Gas

Presentation Outline General background: Unconventional gas plays in the US SLB’s general evaluation workflow Data Audits and Initial Design Pilot Well Strategy Confirmation and Development Options Optimization and Maintenance Exploitation Conclusions

Influence of Prices and Technology
The next few slides were presented by Steven Holditch in September this year at the UG convention in the USA. This simply gives you a view of the normalized money of the day being spent as COST/Barrel. Take note how both technology and world events take effect. The difference between the two is simple. World events just add cost and are grounded in fear and are typically cyclical where the price of oil reverts back to the norm. Technology on the other hand can add invoice cost but has the offsetting benefit of reducing total cost by bringing improved performance and as such makes a good business case. Unconventional Gas Conference & Exhibition Stephen A. Holditch September 30, 2008

This is an example of this cycle on the Austin Chalk where you can see both technology and world events again having it’s impact. In this case the play is getting a bit tired as you can see the decline is setting in making it more difficult for drilling to maintain production. Clearly this is a case needing another technology breakthrough. Unconventional Gas Conference & Exhibition Stephen A. Holditch September 30, 2008

He is a similar scenario but on a shale gas play this time. The cotton valley is a little younger than the Austin Chalk and is one of the earlier siliceous plays (more sandy than clay). In this case you can see the play has not been exhausted and there is still upside potential. Unconventional Gas Conference & Exhibition Stephen A. Holditch September 30, 2008

Barnett Shale Production (BCFD) & Well Count
Barnett Shale Gas Production Growth Barnett Shale Production (BCFD) & Well Count 5 4 6 3 2 1 Yearly well count Number of wells This is a second shale play in the US called the Barnet. You can see that as of 2006 the ramp up in activity and corresponding increasing recovery. The Barnet is one of the more understood and less complicated shale plays in the US. That said there is still a range of success where some operators still drill 50% or more wells that do not produce while others like Devon, EOR, SEECO enjoy much higher success. The difference is how they gather information and then apply technology to exploit the shale.

SEECOS’ Fayetteville Shale Gas Production Growth
These last two slides are from SEECO and their Fayetteville Asset group. In this case SEECO spent a fair amount of time on the front end to understand their play and the heterogeneity challenges and you can see they have enjoyed reasonably steady success.

Fayetteville Shale Gas Production Growth
In the SEECO case they had two thing in their favor: The market price for gas had been higher which allowed them to ramp up the scope of activity. SEECO also took the time to understand the technology, investigated a number of pilot sites across the play and then optimized their field development accordingly applying many lessons learned. The key to success in any shale play is to accept that although a shale can be massive and there may be commercial TOC volumes, the play will not behave like a normal sand stone or carbonate reservoir. In Fact, approaching these shale plays with a normal geologic/Layers model and populating reservoir attributes along the layer is a mistake. The typical shale although containing hydrocarbon, is constrained by micro and nano increments of porosity and permeability. Further the maturity of the shale and the thermal cycling over time can render the shale un producible. Lastly, the complex stresses, both the natural stress fields and the changes in the stress fields over time, the sensitivity to fluids and identifying the right propant to avoid embedment are each critical such to get any of them wrong can cost you half the recover or more. Finally, and this last point is key, Shale is very heterogeneous both vertically and horizontally. This explains why often offset wells can behave radically different. To assume a single completion approach will work across a shale play is very risky. To think one can take success from the Barnet and deploy the same techniques in the Haynesville, or Bakken, etc is a critical misjudgment. The rest of these slides will give you an overview of how Schlumberger approaches these prolific shale plays and why we have been able to take an operators Estimated Ultimate Recovery and double it.

Presentation Outline General background: Unconventional gas plays in the US SLB’s general evaluation workflow Data Audits and Initial Design Pilot Well Strategy Confirmation and Development Options Optimization and Maintenance Exploitation Conclusions

Tight Shale Work-Flow Data Audit/M&A Support Review
Reservoir Model Migrated into Petrel First Pilot Well to Evaluate Shale and Geol Confirmation Second well-offset to prove commerciality and development strategy Update model and tune Cluster systems from old wells Optimization of well placement and completions Exploitation External data collected and considered for analysis. Must have core or cuttings for TRA and basic Cluster normalization. Identify play as viable Identify critical data gaps to be filled in initial well(s). Bring all data into Petrel and begin reservoir model 1st new well is a data rich well designed around filling gaps in data audit and employing the key technologies to prove commercial viability and completion design Prove repeatability and completion concept and performance OR React and re-design and treat as 1st well. Build up Petrel model and design seismic survey for Ant Tracking correlation for field development strategy. Develop initial stress model and resulting model post 1st stage development for optimum infill drilling and re-frac stage Spot check with side wall cores Test tandem well stimulation approach Monitor with microseismics Spot check resulting stress and anisotropy changes from development and plan re-frac sequence.. The presented workflow begins by taking all the available data and building up a model of the reservoir/shale. However, as Shales pose a significantly different set of challenges you have to take a few extra steps. Normal petrophysics using logs struggle at the nano scale so they need help. Normal geologic models are like layer cake and assume a level of homogeneity. This does not work with shale. The typical shale is typically heterogeneous so you need to take more samples to plug the unknowns across the reservoir's. Most sand stones and many carbonates often behave on a trend across a basin because regards mechanical properties while shales have demonstrated they can have widely varying material properties with unconfined compressive strength (UCS) ranging from 1000 psi to 6000 psi and higher in just a few feet. A methodical approach that honors all the data and is disciplined to fill in the data gaps and that minimizes assumptions across the play is the difference between success and failure. As always many companies and departments see themselves practicing this already at a high level. But the devil is in the detail as some have found out and put into practice.

The art of models is in the application.
We love models… Models allow us to take a solution and apply it everywhere. Or do they? Some of the early slides in the presentation showed the evolution of plays like the Barnet, Fayetteville, Cotton Valley etc. Because we at SLB work for all the clients we get to observe all the practices and the results. And while some companies can find a measure of success taking what works in one shale and applying it to another other companies who are just offset in very similar conditions are enjoying double the success. You have to wonder what the difference is. Barnett The art of models is in the application.

Early Phase – Data Audit+
Gather the available data and conduct actual lab measurements when needed to compliment the petrophysics. Where Core is not available cutting may be of sufficient quality. Reservoir Quality Core to Log Integration Shale Classification and Cluster Analysis Identify missing data and Pilot Strategy Data Audit/M&A Support Review Reservoir Model Migrated into Petrel External data collected and considered for analysis. Must have core or cuttings for TRA and basic Cluster normalization. Identify play as viable Identify critical data gaps to be filled in initial well(s). Bring all data into Petrel and begin reservoir model Along with the seismic, log sets and the geologic models that are likely to exist you need to find or go out and get the rock. Shale presents challenges at the nano scale so you simply have to start there to get the assumptions right to build up your model.

TRA Analysis Rock ≠ Rock ≠ Rock
The goal of tight rock analysis is to evaluate the two most fundamental requirements for successful production of gas from tight shales, reservoir quality and completion quality. Reservoir quality assesses and ranks the gas productivity potential of the various shale units in the play. Completion quality assesses the potential for developing hydraulic fractures on the various shale units, their containment potential, and their potential for developing large surface area via the generation of multiple fractures (i.e., branching). Most prolific gas bearing units are identified based on measurements of gas desorption, adsorption gas isotherms to evaluate adsorbed and interstitial gas content, by measuring fundamental geochemical properties of gas composition, organic content, Kerogen type and maturity, by measuring fundamental reservoir properties of effective porosity, gas filled porosity, permeability, liquids and gas saturations (following the tight rock analysis method), and by evaluating the textural and mineralogical properties of these units via petrologic analysis. Best zones for hydraulic fracturing are identified by evaluating the magnitude and orientation of the minimum horizontal stress and its variability along the various reservoir and non-reservoir rock units, by identifying the presence, orientation, and filling of natural fractures on cores, and by understanding the optimal orientation between the mineralized fractures, the orientation of the horizontal stress, and the orientation of the horizontal wells, for maximizing surface area during hydraulic fracturing. Furthermore, the treatment design is optimized by evaluating the potential for formation/frac-fluid sensitivity, the adequate selection of proppant, and the analysis of near-wellbore stress concentrations, that may result in tortuous paths and abnormally elevated fracturing pressures. Tight shales are heterogeneous and strongly anisotropic. Thus, analysis of material property heterogeneity and core-to-log scaling relationships are a necessary component of the analysis. N-dimensional cluster analysis of logs, and high-resolution, continuous, strength profiles along the core length provide the measurements required for evaluating sample-scale, core-scale and log-scale heterogeneity and for developing scaling relationships. The analysis also optimizes core sampling and sample location for adequate and cost effective representation of material properties. Initial analysis from precise sampling of core with TRA conducted to describe the heterogeneity and precise attributes. Two Goals: 1. Reservoir quality in the various units 2. Completion quality for each productive interval

Texture and mineralogy
Issues like thermal maturity, carbon content, etc are all key. Petrology is no less important. Grain sizing, texture, mineral content and the corresponding fluid compatibilities. Here you can see one view of a Barnet and Haynesville that looks somewhat similar (bottom) where a different view of the same rock looks completely different. Also the Haynesville has been found to be more unpredictable than the Barnet and yet in this case you can see the Haynesville has good perm and TOC. Barnett calcareous mudstone: 3% gas-filled porosity; 150 nd perm Haynesville calcareous mudstone: 6% gas-filled porosity; 406 nd perm Haynesville calcareous mudstone: 6% gas-filled porosity; 406 nd perm

Three Layered Core-Based Shale Classification
argillaceous siliceous calcareous Layer 1: Grains >4 μm TIGHT GAS SANDS AND CONVENTIONAL RESERVOIRS Layer 3: Organics Layer 2: Matrix Composition increasing silt & sand TerraTek has worked on nearly all the productive shales around the world and have developed a classification for each that is used on our workflow. SHALE RESERVOIRS

Reservoirs: Thin Section Examples
Marcellus, Pennsylvania Montney, Alberta Canada Bakken Shale, North Dakota A further illustration of silt content shows the visual difference between disseminated silt (or slightly wispy silt distribution) on the left and more discrete silty layers on the right. Note locally better porosity in the silty layer at the right, whereas the texture at left contains tiny interxln micropores. Note scale is different: higher mag on right. The key point to take away from this slide is that each shale is quite different and carrying a successful practice from one shale to another does not yield the optimum result. Mancos Shale, Uinta Basin Penn Shales, West Texas Sandstone, offshore South Africa

Applications: Multiwell analysis for coring and sampling
Aerial View Once you understand the quality of the reservoir you have to couple this with the materials properties so that your completions designs are matched to the complexity of the rock. To do one without the other risks issues like understanding the stresses in the rock the rock fabric and the containment of the treatment. This can lead to miss reading and confusing similar clusters that are differed only by their material properties at the core scale and this then determines the producibility of the cluster. The two rows of core sections with have a red curve mapped along the axis. This is a measure of UCS from our MP2 Service on our Scratch tester. In these two 3 foot sections the UCS ranges from <10o0 psi to over 6000psi. This detail and other geomechanics measurements are integrated into the cluster groupings as well as used in determining anisotropic or isotropic behavior in the rock. Cluster analysis coupled with materials profiling allows us to evaluate log-scale heterogeneity for reservoir quality and completion optimization. You need both

Heterogeneity is a Key Issue
Argillaceous (NR) Calcareous (NR) Mix. Siliceous Argillaceous (R) Siliceous/Arg-illaceous (R) Nodules Problem: Reservoir quality: Where & how is gas stored? Net Value: What is the effective gas in place? Accessibility: What is the relationship between high gas concentration and containment? Production and Recovery: How discontinuous is the stress profile? How discontinuous is the pressure profile? What are the relevant discontinuities? Is the system stiff (open vs. closed fractures)? What is the variability in rock properties? What is the degree of anisotropy? Is brittleness an indication of anything fundamental? Siliceous (R) When we look at the different unconventional plays across the US we often observe a sequence of success and failure from well to well even on close offsets in the same play. This is because of the heterogeneous nature of the play. Once the geology is laid down several changes take place that have a direct effect on the quality of the shale reservoir. Changes over time from tectonics, thermal cycling, diagenisus, stress and fracturing and healing of the fractures happen non uniformly across the basin have a direct impact on the producibility of the shale. The result is that often two offset wells drilled as twins find completely different properties in the shale. One is productive and one is not. Because the differences are often at the micro and nano scale well logs are not sufficient to answer all the questions. This is where our Cluster Analysis was born. It takes the detail of the measurements of the rock and scales this up and integrates it with the log data to give you the ability to move across the play more efficiently. The biggest issue in tight gas reservoirs is not low permeability….It’s heterogeneity.

First Pilot Well(s) Consider what data is in hand and the quality against the uncertainty and design the Pilot data strategy Hole Core or infill with Side Wall (rotary) Horizontal or Vertical Assumptions Heterogeneity Completion Strategy Do you have containment? Are multi stages feasible? Fluid and proppant selection First Pilot Well to Evaluate Shale and Geol Confirmation 1st new well is a data rich well designed around filling gaps in data audit and employing the key technologies to prove commercial viability and completion design Following the data audit a plan to infill any of the data gaps is next. Where Cluster analysis can be done on existing data we may be able to avoid taking full core and use sidewall core. Basic assumptions of well placement like vertical, or pilot and horizontal lateral, etc can all be planed to test and gather additional data to be able to firm up the optimum development for the field. Where the data Audit has had access to useable rock and the reservoir quality is proven the next key issue is what is the best completion and is there sufficient containment for each of the target zones you want to complete.

Anisotropy and Fracture Containment
Isotropic Blue (v) Anisotropic Red (Eh, EV, nh, nV) These are the basic equations we use to determine the nature of the in-situ stresses and the resulting effects on containment. Tight Shales are often more complex than normal reservoirs and often display anisotropic nature. Understanding this is key to designing the right stimulation job.

Note: You must have core measurements of stress in 3 axis to cover the remaining unknowns
This is an example in the Barnet in a more sandy section were we can see how the core data is integrated with the sonic scanner. Again to accurately estimate the amount of anisotropy the core is critical as the Sonic Scanner measures only 3 of the 5 unknowns. There are alternative methods to guestimate the differences but these have been proven risky and can result in your fracture treatment going very wrong. So they will not be covered here.

Staging the Stimulation
Anisotropic Stress Profile Isotropic Stress Profile Here you can clearly see the difference between an isotropic stress profile and an anisotropic profile. In one case you can design for containment and in one you can not. The impact on your completion strategy is obvious.

Anisotropic Stress Profile Isotropic Stress Profile
Staging the Stimulation Anisotropic Stress Profile Isotropic Stress Profile Here again is the same example deeper in the well

Pilot Update - Development
A second pilot well to optimize or confirm the completion is recommended Horizontal vs. Vertical Completion Optimization Update Model Plan for periodic checks Field Optimization Upscale Clusters into Petrel and Seismic Visage Coupled Stress Model Fine tuning risks of heterogeneity Well Placement Frac geometry Simultaneous frac planning Consider forward stress modeling First Pilot Well to Evaluate Shale and Geol Confirmation Second well-offset to prove commerciality and development strategy Update model and tune Cluster systems from old wells Prove repeatability and completion concept and performance OR React and re-design and treat as 1st well. Build up Petrel model and design seismic survey for Ant Tracking correlation for field development strategy. Develop initial stress model and resulting model post 1st stage development for optimum infill drilling and re-frac stage With the initial Pilot drilled you have one of 2 cases: You can confirmed most of your model assumptions and can move to the second pilot well to optimize on the completions, decide on the well type as vertical or horizontal, etc. You have realized errors in the model and have to go back and correct for them. Assuming you are right we update the model accordingly and can begin the detail planning of this section of he play. Well placement in the reservoir to contact the best zones becomes an issue as you may control on the pilot and offset wells but you may not be able to assume consistency from well to well. An updated 3-D survey with ant tracking processing should be conducted at this time where the design is tuned to the play. This feed directly into petrel. Obviously, if the data was already available this would already be done or in progress. With the right attribute training in the ant tracking we can identify the larger clusters and can place the wells accordingly reducing the failure rate due to lateral heterogeneity. Also the stress fields across the play should be mapped with the view of anticipating significant changes over time from both depletion as well as the induced stress changes from the stimulations. This is done in Visage. Visage is a coupled Geomechanics forward modeling tool that help plan the second stage of drilling or help select which wells to be re fracked. Depending on the size of the play, you can also continue stepping out with your pilot well approach to prove up the other sections in the reservoir. i.e. there are several parallel processes to consider for maximum efficiency and fastest cash flow. Continue to pilot across the play

TRA Real Time Support Core to log integration allows you to tag intervals along the borehole of a non cored well with similar patterns. Log data can be transmitted to town as you identify dissimilar patterns you can quickly take a sample in real time to insure a proper evaluation of the units on the subject well. A rotary sidewall coring tool is used and the sample is returned to the lab for analysis Once you have confirmed the basic model assumptions and have refined the development plan it’s off to the races and move into manufacturing mode. Right? Wrong…………you can not forget the heterogeneous nature of the shale and you have to be ready for discontinuities. You will be drilling along a seismic guided plan but you may find a new sections of varying thickness that n do not match your known clusters. As we discussed Cluster analysis shows heterogeneity at log-scale, and discriminates zones of consistent clay behavior within heterogeneous media. As you continue to step out from your Pilot well(s) you may find new log response or a new sediment layer not seen before. Real Time Cluster analysis can be incorporated into the development plans where we can send the data into the lab for analysis and matching with the existing models. This RT advise can be turned around in <2 hours. Results from this analysis are used for selecting core samples (or rotary SWP locations), to sample heterogeneous formations most efficiently, and subsequently to identify the units with best reservoir quality and the units with best fracture containment potential. Cluster Tagging and the analysis of the compliance index help monitoring changes in thickness and location of previously defined cluster units between wells, and help identifying new facies requiring coring and laboratory characterization. In addition, Cluster Tagging quantifies the applicability of cluster-based models for use on un-cored wells. To our knowledge, there is no equivalent service that provides a quantitative indication of how well a particular tight shale model fits the measured log responses.

Basin-scale 3D Visualization (Petrel Models )
Compílanse Gross Thickness We build the models in Petrel to be easily integrated with your other data. This can then be integrated with surface seismic. With the right 3-D survey design and then processing against the right set of attributes you can then start to identify the productive clusters between your Pilot wells. Obviously you can now see the value of core to log integration as it allows you to scale the knowledge from the core up to seismic. Also as you will see several clusters will be too thinly layers to be identified in the seismic. However, with a proper design of the acquisition and proprietary processing using Anttracking and Extreme techniques we can see with much higher resolution than normal seismic and get down to the meters and even feet. Note also the Compliance term in the upper corner. The algorithms have a self testing aspect that detects for results out of compliance that can be due to borehole conditions and flags these.

Completion Options SPE 119635 SPE 110562
Before 1997 the Barnet Shale (USA) was completed with massive fracture designs using cross linked gels and large volumes of propant. The gels at the time resulted in difficulties in clean up and poor well performance. In 1997 gels were dropped and slick water jobs were tested. The result was no difference in well performance but the cost for the stimulation dropped by as much as 65%. In 2002 horizontal wells were tested at near twice the cost of vertical wells but with amazing results of up to 300% Estimate Ultimate Recovery. Once again the value of technology was proven. Today, there are a few new schemes to increase the effective contact volume of the reservoir and increase the EUR still further. Hydraulic Fracture Complexity due to Simultaneous Fracturing The “Simul-Frac” technique is a method in which adjacent sections of a reservoir are hydraulically fractured from at least two well bores at the same time. Most of the time the wells are horizontal with the laterals drilled in the direction of σh and landed at similar, although not always, the same depth. In such wells the toe sections of the laterals will be stimulated at the same time. Subsequent stages are performed concurrently working from the toe back to the heel of the lateral. The objective is to place hydraulic fractures in close proximity to one another by taking advantage of the tensile stress region near the fracture perimeters. A number of variations to the technique are commonly employed: One method to achieve a dense hydraulic fracture system is to drill hydraulically fractured vertical wells on a dense well spacing. To achieve the required dense fracture network requires multiple vertical wells with a well spacing of approximately 15 acres. This is not cost effective as a new vertical borehole is needed for each stimulation. As previously mentioned, a commonly employed alternative is to drill horizontal wells in the direction of σh and to place multiple hydraulic fractures in close proximity to each other. This success of this technique is well documented. A more recent development is the utilization of the pressure alteration due to a stimulation treatment from a horizontal well to alter the hydraulic fracture geometry from a concurrent stimulation treatment being performed on a closely spaced, parallel offset horizontal well. The key to maximizing this is to consider the initial field development plan with the context of multiple well effects as above in the first stage and coupling this with the changes in the stress in the rocks from production to optimize your re frac stages later in life. The next slide is an example of a re frac and simul-frac results. SPE SPE

Fiber Diversion Technology “StimMore”
StimMap technology allows us to monitor the fracture events down hole. These events are a combination of re activation of pre existing fractures and faults and obviously the new fractures induced by the stimulation treatment. The key here is to use the technology to verify the execution of the design and update them model accordingly applying lessons learned. In this case a new fiber diversion technology was used to increase the contact volume with the reservoir. As a reminder, this is a multi stage job requiring a detailed understanding of the containment between the target zones. This required the Sonic Scanner as well as calibration from core. The results are clear. The job went off as designed. You can see here this well had an excellent event distribution and in general an effective far distance event pattern as well. Each color represents a separate stage. Lt Blue, Dk blue red and green. A SLB proprietary fiber diversion technology was used in each stage and managed in real time. The plot on the right demonstrates that in each stage the fiber diversion was effective in extending the fracture growth into the far fields.

Asset Optimization Plan for heterogeneous challenges and include a degree of periodic checks Logs to confirm stress distributions and anisotropy Cluster updates as needed Update seismic scaling of clusters Field Optimization Determine if Simultaneous well treatments will bring improvements. Monitor stress changes with Sonic Scanner and update Visage Model Plan second stage of drilling or refrac based on the Petrel Model Optimization of well placement and completions Exploitation Spot check with side wall cores Test tandem well stimulation approach Monitor with microseismics Spot check resulting stress and anisotropy changes from development and plan re-frack sequence.. Depending on the size of the play several parallel efforts take on from here through the exploit phase or re frac phase. The nature of these shale plays will introduce surprises so planning a periodic check on key data to confirm the compliance to the model is a best practice. Testing various completions techniques of different tandem well treatments and layouts, the number of stages, etc are all in practice today. It is not uncommon to find an early re frac can significantly increase the productivity of a well. Some companies are also treating well simultaneously as they have found the results of the combined induced stresses add complexity to the fracture volume and this increases the reservoir contact. As we mentioned tools like Visage for forward modeling of the coupled geomechanics can help in this design work and planning.

Design with Stress in Mind
The A1 well was initially completed in May,2007 (figure 3) . Microseismic activity indicated that complex fracturing was present in the first two stages at the south end of the lateral (figure 4). The A2, A3 and A4 wells were then drilled. Prior to the completion of these wells the A1 was refraced to provide a pressurized system to counter the hydraulic fractures from the new offset wells. The stimulation treatment on the A1 was again monitored with real time microseismic and again indicated complex fractures in the south end of the lateral and more planar fractures in the heel. A fracture azimuth of N70E was determined from the initial frac and refrac treatments. Initial production rates, based on the first 7 days peak production, are more than double those of the original individually fractured wells….. Buts as you can see not all he zones responded alike suggesting still room for optimization. The good example of interaction between simultaneously pumped fracture treatments is found during the sixth treatment stages. The effects of fracture interference on a fracture initiated in an exterior well,Treatment Well 1, and an interior well, Treatment Well 2, can be seen in Figures 14A through 14D. Figures A and B are omitted as they only show sparse eventing. The entire set of microseismic data acquired during the project is shown in Figure 13. There are two patterns of microseismic activity visible. Most of the stages produced fracture networks that were complex and do not have well defined azimuths. Some stages show well organized patterns of microseismic activity that are oriented east to west. The stages displaying this behavior originate from the two exterior wells and appear to indicate that asymmetric fracture extension towards the previously completed laterals to the east and west of the project area. When you can model the state of stress over the life of the field and predict fracture containment and the direction the frac is likely to propagate you can plan your wells most effectively including the life stages for re drilling or re fracking. Figure 4 SPE

Conclusions Shales are heterogeneous in both reservoir and mechanical properties. This is the most important property to understand. The workflow presented has been proven (in part) to be most effective helping clients increasing their ultimate recovery by %. We continue to evolve this workflow as we learn from new applied technology. Proper characterization requires data and sampling on all prospective zones. Not all zones are good reservoir, not all high resistivities are good reservoir. Containment zones may be hydraulic seals or they may be zones within the shale. Worst case there is not reliable containment. Not all zones react the same way with completion fluids. The core work, log, petrology, Cluster analysis and tie into surface seismic are all proven. The use of Visage is yet to be proven and is under pilot at present. The characterization of the shale as productive includes: Gas in Place, Maturity, Permeability, Containment, Understanding fluid compatibility and the fracture complexity (natural and induced) and the issues around propant embedment. Because there are significant challenges in log interpretation at the nano scale in tight reservoir a multivariate approach is best. Optimization requires a constant updating because the natural heterogeneous nature of shales. Building a common model (in Petrel) to honor all the data and scales from core to seismic, that can be updated with changes in stress from induced fracture treatments and depletion is what we recommend as the most efficient way to manage and optimize your assets.

Conclusions Field Optimization
Use core-to-logs integration (MP2) to define a baseline for testing and also increases sampling efficiency Establish the well placement and completion strategy with an integrated plan of the current and forward modeled stress state Do not assume what works in one shale applies to a different one and be ready to realize this in different sections of a large shale play. The core work, log, petrology, Cluster analysis and tie into surface seismic are all proven. The use of Visage is yet to be proven and is under pilot at present. The characterization of the shale as productive includes: Gas in Place, Maturity, Permeability, Containment, Understanding fluid compatibility and the fracture complexity (natural and induced) and the issues around propant embedment. Because there are significant challenges in log interpretation at the nano scale in tight reservoir a multivariate approach is best. Optimization requires a constant updating because the natural heterogeneous nature of shales. Building a common model (in Petrel) to honor all the data and scales from core to seismic, that can be updated with changes in stress from induced fracture treatments and depletion is what we recommend as the most efficient way to manage and optimize your assets.

The Art of Modeling is in the application Green River Barnett Woodford
Haynesville Wolfcamp Woodford Marcellus Mancos Antrim Niobrara Montney White Specks Green River So there is no one silver Bullet However, there is a proven workflow that when applied to each reservoir will deliver results is in the application

Experiences in the Development of Shale Gas

Similar presentations

Presentation on theme: "Experiences in the Development of Shale Gas"— Presentation transcript:

Similar presentations

About project

Feedback

Log in

Auth with social network:

Experiences in the Development of Shale Gas

Similar presentations

Presentation on theme: "Experiences in the Development of Shale Gas"— Presentation transcript:

Similar presentations

About project

Feedback