Downhole Gauges Research Articles

Interpreting Pressure and Flow-Rate Data From Permanent Downhole Gauges by Use of Data-Mining Approaches

Summary The permanent downhole gauge (PDG) is a promising tool for reservoir testing but has yet to reach its full potential. Generally, conventional well-testing methods are most able to use small sections of constant-flow-rate data. However, data mining, a newly developed technique in computer science, is a tool that can reveal the relationship among variables from large volumes of data. The application of data-mining algorithms to synthetic and field data has been successful in extracting the reservoir model from variable-flow-rate and pressure-transient data. In fact, because of uncertainty in flow-rate measurements, this technique is one of the few ways to make use of the flow-rate data that are now available with some modern PDG tools. The application is conducted in two steps. First, the pressure and flow-rate data from the PDG are used to train a nonparametric data-mining algorithm. The reservoir model is obtained implicitly in the form of polynomials in a high-dimensional Hilbert space defined by kernel functions when the algorithm converges after being trained to the data. Next, a specific flow-rate input (for example, constant rate) is fed into the data-mining algorithm. The data-mining algorithm will make a pressure prediction subject to the input flow rate. Because the data-mining algorithm has already obtained the reservoir model, the pressure prediction is expected to be the reservoir response given the constant flow rate. Therefore, the proposed constant flow rate and the predicted pressure reveal the reservoir model underlying the variable PDG data, without needing to specify in advance which reservoir model is to be used. Three methods (Methods A, B, and C), differing by input vectors, kernel functions, and presence of breakpoints detection, are proposed in the paper. Synthetic noisy data and real field data were used to test this approach. Methods B and C were able to satisfactorily recover the wellbore/reservoir model in most considered cases. Even in extreme cases when the flow-rate data are noisy and changing frequently, and in the absence of any shut-ins, the method was still able to extract the reservoir models.

Unknown Rate History Calculation from Down-hole Transient Pressure Data Using Wavelet Transform

In the oilfield, rate metering is less satisfying compared with pressure measurement. Detailed rate history for individual well is not always available. The common practice is that few of the wells are measured together through manifolds and daily, monthly rate or total cumulative production is measured with surface separation equipments. Rate allocation algorithm is utilized to assign production to each well, but the results are inaccurate due to low measurement frequency. For well testing, another problem is that the rate measured from the surface is very often inconsistent with the pressure measured from down-hole. These problems together make it a very challenging task for engineer to interpret transient pressure from the well down-hole gauges. This article introduced wavelet transform method to calculate unknown rate history from the down-hole transient pressure data. The Haar wavelet was chosen to process transient pressure data, where flow events can be identified with the amplitude of pressure transform. For the reservoir with constant reservoir-well parameters, the amplitude of pressure transforms is proportional to the change of rate. Based on this discovery, an algorithm for calculating unknown rate history from cumulative production has been developed. As this method is independent of the developed reservoir model, reservoir heterogeneity, skin, and wellbore storage have no effect on this method. For other complex reservoirs with variable reservoir-well parameters, such as gas reservoir and multiphase reservoir, this algorithm can also be applied resulting in small errors. In practice, the developed method can identify the offset of the flowing rate and the pressure, so synchronization of the rate and pressure can be achieved, which greatly increased the confidence of the pressure data analysis. Both theory and case studies were tested to demonstrate the robustness of this method in practice.

Processing and analysis of transient pressure measurements from permanent down-hole gauges

With permanent down-hole gauges (PDGs) widely installed in oilfields around the world in recent years, a continuous stream of transient pressure data in real time is now available, which motivates a new round of research interests in further developing pressure transient processing and analysis techniques. Transient pressure measurements from PDG are characterized by long term and high volume data. These data are recorded under unconstrained circumstances, so effects due to noise, rate fluctuation and interference from other wells cannot be avoided. These effects make the measured pressure trends decline or rise and then obscure or distort the actual flow behavior, which makes subsequent analysis difficult. In this paper, the problems encountered in analysis of PDG transient pressure are investigated. A newly developed workflow for processing and analyzing PDG transient pressure data is proposed. Numerical well testing synthetic studies are performed to demonstrate these procedures. The results prove that this new technique works well and the potential for practical application looks very promising.

Transferring Intelligent-Well-System Triple-Gauge Data Into Real-Time Flow Allocation

Summary Knowing the exact flow allocation for each controlled zone is important for well optimization and the management of an intelligent well system (IWS). For two-zone IWS producers, a broadly accepted downhole gauge configuration uses the triple-gauge system, where two gauges give the upstream-side pressure/temperature (P/T) of the two downhole control valves and one gauge gives the P/T inside tubing of the commingled fluid [Baker Hughes IWS installation (2012) and Halliburton-WellDynamics IWS installation (2012) databases]. Theoretically, this configuration gives the P/T boundary conditions between the two valves and the gauge carrier, where flow allocations can be solved numerically, on the basis of the gauge readings and control-valve settings. However, from what we have seen in the past 10 years of IWS applications, only a few have published successful application cases regarding this topic. Is this an indication that a large number of two-zone triple-gauge IWS wells are operating in the low-confidence region of the two zone's production flow allocations? In this work, a comprehensive hydraulic model has been developed to address this topic. This paper will discuss a recent application of such a model to estimate the flow allocations of an existing two-zone deepwater IWS oil producer. The well began production in 2007. A total of 1,362 daily triple-gauge data points are available for this study, where the monitored P/T data indicate that the well was flowed in multiphase conditions at downhole for a large percentage of its production life. Verification was completed by comparing the predicted flow-allocation results with this well's measured total rates and daily-allocation rates. Further comparisons of the zonal allocations, between the model calculated results vs. the zonal-reservoir deliverability-study predicted results, were also provided. These comparisons showed a good match between the predicted results, measured data, and the available reservoir-study results. Descriptions of key factors to address the accuracy of the method have been provided, including compensated differential pressure, multiphase choke model, choke-discharge coefficient, and fluid pressure/volume/temperature (PVT) behavior impact. Sun's modified multiphase choke model was proposed in this study. The authors believe it will be more suitable for downhole valve operating and multiphase-flow conditions. This case study has proven a very promising independent solution for continuous well-rate estimation, with the solution based purely on choke-pressure drops and intelligent well-valve positions. The downhole monitoring P/T is normally based on seconds, which means that intelligent well-flow allocations can be calculated in real time without installing downhole venturi flowmeters that may add completion cost. In addition, a venturi flowmeter provides a smaller ID profile for the completion strings above/below it, which is inconvenient for future potential wellbore interventions. This solution brings measurable benefits for those IWS wells with no downhole flowmeters when taking into account the time and effort spent on periodic production tests, reservoir/well deliverability studies for production allocations, and potential production loss during the production tests.

Wireless Wellbore - The Way Ahead

Technology Update The trend of increasing wellbore complexity for extended reservoir contact and greater reservoir heterogeneity demands improved monitoring and control solutions. Traditionally, the only option has been the deployment of a cabled system, but this limits the application of intelligent well technology to new installations or workovers. In any case, cabled systems are not always possible in new installations, especially where the completion is discontinuous, and slimhole or monobore completions may not allow cables to be deployed along the tubing string. Wireless technology is proving to be a more flexible alternative to addressing the issues of permanent downhole monitoring. Tendeka’s wireless gauge, an interventionless completion technology that has been successfully deployed in the North Sea, allows real-time flowing bottomhole pressure (FBHP) to be efficiently transmitted to the surface, an attractive option for wells, in which the cabled gauge system has failed or was not initially installed. Originally designed to 3.5 in., the company has recently produced a 2.25 in. version. Benefits of Wireless Technology The system transmits data from the lower completion to the surface via pressure pulses. The tool design allows the well’s production to be partially choked for a short time to create a pressure pulse, which is detectable on the surface pressure gauge. The well’s energy is used to transmit data to surface, thereby reducing power consumption, and the system requires no additional surface installation or pickup because an existing tubing head pressure gauge can be used to detect the pulse train. For most operators, the system can be deployed by a single intervention, allowing highly accurate data to be sourced almost instantaneously for a fraction of the cost of a recompletion. Compared with a memory gauge system, it allows data to be collected in real time and provides a continuous confirmation of operation. The gauge can be set in blank pipe, giving optimal freedom for installation depth, and it can be installed as close to the producing interval as required. A benefit of using pressure pulse transmission is the ease of installation. No retrofitting of topside equipment is required, and many of the technical and contractual issues are avoided when introducing a new monitoring system. Successful Deployment A major operator in the North Sea retrofitted the 3.5 in. wireless pressure and temperature gauge at 2200 m in a low-pressure (32 bar) gas well offshore Norway. The existing wellhead pressure sensor was used to capture the wireless signal and extract the data, therefore, no extra infrastructure was required. The application was especially challenging because the well was a marginal producer and the wellhead pressure had large background pressure variations, because of limited well deliverability. Despite these conditions, pressure pulse transmission proved effective. Even if the well starts to significantly deplete while the wireless downhole gauge is installed, the gauge itself will modify its pressure pulsing method to ensure that a detectable pulse train is transmitted to surface.

Pressure-Transient and Production-Data Analysis of an Unconsolidated Formation

This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 147506, ’Pressure-Transient and Production-Data Analysis of a Horizontal Well in an Unconsolidated Formation in Frade, Brazil,’ by Yan Pan, SPE, Russ Ewy, SPE, Don Ringe, SPE, Medhat M. Kamal, SPE, Ralph Affinito, SPE, and Oluwole Sotunde, SPE, Chevron, prepared for the 2011 SPE Annual Technical Conference and Exhibition, Denver, 30 October-2 November. The paper has not been peer reviewed. Frade Asset is a medium-heavy-oil field in the northern Campos basin, approximately 75 miles offshore Rio de Janeiro in 3,500-ft water depth. The structure is a low-relief anticline with two main fault blocks consisting of four stacked unconsolidated reservoirs. The field produces from nine horizontal oil wells with three vertical water-injection wells to maintain reservoir pressure. Continuous well monitoring and reservoir characterization are key to cost-efficient development in this deepwater subsea field. Introduction The development strategy for the field includes horizontal production wells and deviated injection wells to maintain reservoir pressure. The asset-management team realized the challenges of this particular field and made the decision to install permanent downhole gauges in every production and injection well drilled, with a reservoir-surveillance plan in place to monitor well and reservoir performance. Active reservoir surveillance enabled engineers to make sound and quick operating decisions, such as shutting in wells, changing chokes, or planning well interventions on the basis of dynamic data collected continuously at wells. It also provided real-time information for improved reservoir characterization, model forecasts, and optimized development plans. Because data stream in continuously, the cycle from data collection to updating reservoir models to forecasting field performance to optimizing development could be shortened. Example Well: Producer 2 Well Producer 2 is in the upthrown fault block, as shown in Fig. 1, and had an original reservoir pressure of 3,079 psia and a reservoir temperature of 110°F. The net pay thickness is approximately 42 m, and the horizontal well was drilled 30 m above the sealing bottom of the reservoir. The well trajectory was parallel to the fault to the southwest and to the axial fairway edge to the northeast. The well was completed with an openhole gravel pack, and the total completion length was 507 m. The permanent downhole gauge was installed above the top of the gravel-pack completion.

Novel Analytical Methods of Temperature Interpretation in Horizontal Wells

Summary Long (horizontal) completion intervals typically show a wide variation in the inflow distribution along their length because of either formation heterogeneity or (frictional) flow pressure losses. Monitoring of the inflow profiles in such wells is an important step in efficient reservoir management. Accurate temperature measurements [using distributed temperature sensors (DTSs), permanent downhole gauges (PDGs), or other forms of production logging] have become more widely available in recent years. Many published papers describe temperature sensing and its phenomenological interpretation, but few attempts have been made recently to develop a comprehensive mathematical basis for the analysis of downhole temperature behavior. This paper presents a holistic, analytical, mathematical model for calculation of the temperature profile in horizontal wells producing liquids for reservoirs where thermal recovery methods are not being employed. The model presented in this paper rigorously accounts for (1) the Joule-Thomson (JT) effect, (2) convection, (3) transient fluid expansion, and (4) time-dependent heat loss to the surrounding layers. A synthetic horizontal-well model has been built using a commercial, scientific simulator as a test bed to provide the data to allow evaluation of the efficacy of our novel analytical methods. Asymptotic analytical solutions have also been found for transient and steady-state flow. It has also been found possible, in addition to these constant-flow-rate solutions, to apply the well-known pressure-analysis solution techniques for the estimation of (1) thermal properties and (2) inflow profiling. The methods proposed here can be applied to a wide variety of well completion types, flow conditions, and system properties. These methods form the basis for the calculation of oil-and water-flow phase cuts and distributions that are based purely on temperature measurements. Their use will further increase the potential applications of the modern downhole monitoring and control capabilities currently being installed in wells.

Advanced wireless telemetry system for real-time surface readout during drill stem testing

Drill stem testing (DST) provides reservoir information that helps evaluate the potential of a new field. The data includes permeability, total skin (damage) and formation pressure, but these calculations are possible only if the build-up period is sufficiently long to attain middle time regime. The best technique for determining the length of flowing and build-up periods required is to monitor real-time bottomhole pressure (BHP) at surface. Traditionally, BHP and temperature data have been recorded using downhole memory gauges, but the data could only be retrieved after the test had concluded and the DST bottomhole assembly (BHA) was pulled out of hole. Wireline surface read-out (SRO) was used in the next evolution of the applicable technology. This method lowered a wireline retrieval tool into the BHA during the build-up periods to retrieve real-time data from downhole gauges. This technique worked satisfactorily during build-up periods but was difficult to achieve during flowing periods, especially at high rates and with sand or solid production. Now, a real-time downhole data acquisition solution that uses the newest generation of an acoustic wireless telemetry system has been developed. This system allows data transmission by the tubular wall using acoustic energy during flowing and build-up periods, thus providing real-time SRO throughout the test to facilitate quick decisions and troubleshooting solutions. With the acoustic wireless telemetry system, wireline intervention during DST is not required, thus eliminating inherent risks and costs of such operations. A project undertaken by PETRONAS and a major service company using this system was successfully implemented on jack-up rigs in Malaysia. This paper discusses the challenges and step-by-step improvements made to enable these jobs to successfully meet the sought-after goals.

Modeling Reservoir Temperature Transients and Reservoir-Parameter Estimation Constrained to the Model

Summary Permanent downhole gauges (PDGs) provide a continuous source of downhole pressure, temperature, and sometimes flow-rate data. Until recently, the measured temperature data have been largely ignored, although a close observation of the temperature measurements reveals a response to changes in flow rate and pressure. This suggests that the temperature measurements may be a useful source of reservoir information. In this study, reservoir temperature-transient models were developed for single- and multiphase-fluid flows, as functions of formation parameters, fluid properties, and changes in flow rate and pressure. The pressure fields in oil- and gas-bearing formations are usually transient, and this gives rise to pressure/temperature effects appearing as temperature change. The magnitudes of these effects depend on the properties of the formation, flow geometry, time, and other factors and result in a reservoir temperature distribution that is changing in both space and time. In this study, these thermometric effects were modeled as convective, conductive, and transient phenomena with consideration for time and space dependencies. This mechanistic model included the Joule-Thomson effects resulting from fluid compressibility and viscous dissipation in the reservoir during fluid flow. Because of the nature of the models, the semianalytical solution technique known as operator splitting was used to solve them, and the solutions were compared to synthetic and real temperature data. In addition, by matching the models to different temperature-transient histories obtained from PDGs, reservoir parameters such as average porosity, near-well permeabilities, saturation, and some thermal properties of the fluid and formation could be estimated. A key target of this work was to show that temperature measurements, often ignored, can be used to estimate reservoir parameters, as a complement to other more-conventional techniques.

Understanding well performance with surveillance data

This study presents an inception-to-maturity data acquisition philosophy and deriving value from such surveillance. Specifically, translating wellhead pressures (WHP) to bottomhole pressures (BHP) allowed many reservoir-engineering calculations during the flow period. While conversion of WHP to BHP proved feasible during a flow test, measurements showed that shut-in tests do not lend themselves for such treatment because of rapid heat dissipation of a low-heat-capacity fluid, such as gas. Therefore, we relied upon flow-after-flow (FAF) tests that were embedded in monthly variable-rate production measurements to obtain average reservoir pressure and absolute open-flow potential. These average pressures enriched those that were obtained with downhole gauges from shut-in tests for the material-balance analysis. The resultant time-dependent inflow–performance relationship (IPR) and absolute-open-flow potential helped understand well performance. Indeed, evolution of declining IPR slope led to the identification of gradual wellbore blockage in one of the wells completed openhole. Downhole video recording confirmed mechanical issues in two openhole completions. Production logging showed preferential flow from the upper section of the thick carbonate interval in two wells. However, residual doubts remained about possible flow up the annulus in the openhole/slotted liner completions. Analytic modeling confirmed that the notion of preferential flow up the annulus is untenable.

Predicting Flow Profile of Horizontal Well by Downhole Pressure and Distributed-Temperature Data for Waterdrive Reservoir

Summary Downhole pressure and temperature data are important information that helps us understand the bottomhole flow condition. Today, the data are readily available from permanent monitoring systems such as downhole gauges or fiber-optic sensors. In a previous study, we showed that using temperature and pressure data, water entry along a horizontal wellbore can be detected by a semianalytical model. Flow in the wellbore is well-defined, but flow in the reservoir is described by a single-phase, 1D model. The assumptions limited application of the model to mostly a single-phase condition. In this paper, we present an improved model that is more flexible. We use a streamline-simulation method to solve the flow problem in the reservoir for fast tracking of reservoir flow. We developed a transient, 3D, multiphase reservoir thermal model to calculate reservoir temperature. We integrated the reservoir flow model and thermal model with a horizontal-well temperature model to predict the pressure and temperature distribution in a horizontal-well system. We apply the model to a synthetic example. The example is an infinite waterdrive case. The results of simulation show that the temperature features in a horizontal well can detect the location and amount of water breakthrough successfully. Meanwhile, even the pressure trend does not reflect the water entrance as clearly as the temperature curve, the capability of which to indentify the reservoir permeability distribution is very helpful in temperature calculation. We apply the model to a field case: a horizontal well in the Sincor field for heavy-oil production. The results showed that we can successfully identify where and how much water enters the horizontal well in this field example. We use an inversion method to interpret the pressure and temperature data to obtain a flow-rate profile along horizontal wells. The inversion method is the traditional Markov Chain Monte Carlo (MCMC) method. This stochastic method searches for the possible solution in the parameter space and uses the Metropolis-Hastings algorithm to judge the acceptance. We discuss how to reduce the parameters to make the inversion method work more efficiently according to the downhole pressure and temperature data.

Completion Design for a Highly Compacting Deepwater Field

Summary The Magnolia field, located in the deepwater region of the Gulf of Mexico, produces oil and gas from a tension leg platform (TLP) in 4,673 ft of water. The reservoirs comprise several stacked sandstone intervals within the early to mid Pleistocene with some minor production from the Miocene and Pliocene sands. A total of eight wells have been completed, with the majority of the production from the B25 sandstone. The formation-particle size is fine-grained sand to coarse silt and has relatively low K*H compared to other deepwater reservoirs. The reservoirs are significantly overpressured, highly compartmentalized, highly compacted, and have experienced significant pressure declines in excess of 8,000 psi in some cases during production. The wells were completed with cased-hole frac packs and each completion included a permanent downhole gauge, enabling interpretation of the K*H and skin throughout the producing history of the wells to date. The perforating guns, frac fluids, and screens were extensively tested before completion. The perforation-shot size and density was carefully chosen and tested to achieve the required production. Well test results matched inflow analysis predictions. The initial skin values generally met expectations and improved during production because of a combination of well cleanup and reduced reservoir permeability from compaction. Proppant integrity has been maintained under extreme depletion (>8,000 psi) conditions. Productivity was measured using perforation tunnel permeability (Kpt) analysis. The Kpt values were analyzed over the course of production and compared to similar type completions. The Kpt benchmark analysis shows that the completions are among the best in class. Well productivity has met or is above expectations, and the longevity has exceeded expectations in most cases.

Numerical Modeling of Pressure and Temperature Profiles Including Phase Transitions in Carbon Dioxide Wells

This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 115946, "Numerical Modeling of Pressure and Temperature Profiles Including Phase Transitions in Carbon Dioxide Wells," by Lincoln Paterson, SPE, CO2CRC, CSIRO; Meng Lu, SPE, and Luke D. Connell, SPE, CSIRO; and Jonathan Ennis-King, SPE, CO2CRC, CSIRO, prepared for the 2008 SPE Annual Technical Conference and Exhibition, Denver, 21-24 September. The paper has not been peer reviewed. Geological storage of carbon dioxide (CO2) usually is at conditions above the critical temperature and pressure; therefore, the CO2 will exist as a single dense phase. However, conditions in the upper part of a CO2 well with surface temperatures below the critical point of 31°C can lead to boiling and condensation in the well. The consequences of this are most apparent when the flow rate changes. Density profiles have been calculated for wells experiencing different thermal conditions to determine how bottomhole pressures are related to wellhead pressures. Introduction CO2-injection wells are used in enhanced oil recovery (EOR). CO2-production wells, from underground natural accumulations, provide a source of CO2 for EOR and other industrial uses. Interest in CO2 wells has intensified for geological storage as a means of reducing atmospheric greenhouse gases. Accurate determination of downhole pressures is important if pressure is used to monitor the performance of a geological-storage reservoir. Reliable knowledge of bottomhole pressure helps prevent injection above pressures that can damage the formation. While bottomhole pressure can be measured with gauges, it is possible that, over a long period of time, downhole gauges may fail. Hence, calculating downhole pressure from wellhead pressure is desired. CO2 has a critical pressure of 7.38 MPa and critical temperature of 31.0°C, so if the fluid is near the usual surface temperatures, conditions in the upper part of a well can cross the saturation line of CO2, with boiling and condensation in the well if fluid pressures are in the vicinity of the critical pressure. Also, near the saturation line of CO2, fluid properties display severely nonlinear behavior, challenging numerical simulation. This phase-change issue usually is not of concern during injection of CO2 for EOR because EOR normally involves continuous columns of liquid to the surface with the reservoir pressures required for minimum miscibility. Conditions for phase change are more likely in circumstances not involving EOR, including CO2 production from depleted CO2 reservoirs, CO2 injection into pressure-depleted gas reservoirs, and CO2 storage at depths less than 2000 m. The mathematical treatment of well-bore flow has been described extensively. The full-length paper details the interpretation of flow by use of numerical methods. In the rock surrounding the well, phase change accompanying vertical migration of CO2 during hypothetical leakage has been studied. Leakage usually involves smaller flow rates and closer thermal coupling to the surrounding rock compared with wellbore flow.

Through-Tubing-Conveyed ESP Replacement - Live Well Intervention

This article, written by Assistant Technology Editor Karen Bybee, contains highlights of paper SPE 116822, "Thru- Tubing Conveyed ESP Pump Replacement - Live-Well Intervention," by Walter Dinkins, SPE, and Steve Tetzlaff, Baker Hughes; John C. Patterson, SPE, Hai Hunt, SPE, Peter Nezaticky, SPE, and James Rogers, SPE, ConocoPhillips; and Bret Chambers, BP plc, originally prepared for the 2008 SPE Annual Technical Conference and Exhibition, Denver, 21-24 September. The paper has not been peer reviewed. Through-tubing-conveyed (TTC) electrical-submersible-pump (ESP) technology was developed to address the high cost and long lead times associated with North Slope rig workovers to pull and replace worn or plugged pumps. TTC technology allows ESPs to be changed in live wells without the need to kill the well and work it over. When a TTC pump replacement is performed, the pump is pulled and replaced with slickline or coiled tubing while the tubing, seal section, motor, power cable, and downhole gauges remain in place. Introduction The first TTC systems were installed in West Sak development wells on the North Slope of Alaska in 1998. The first systems were TTC electrical submersible progressing-cavity pumps (TTCESPCPs). In 2001, TTC technology was expanded to include centrifugal pumps to achieve higher production rates. The centrifugal TTC pumps were given the designation TTCESP. TTCESP lift systems continue to be the preferred equipment for the West Sak field. TTC technology is particularly applicable in wells with high solids production in which the pump is the primary failure mode. TTC technology also provides a means to upsize, downsize, or add pump components such as rotary gas separators without rig intervention on live wells. TTCESPCP and TTCESP Components From bottom to top, the rig-deployed (tubing-conveyed) components of a TTCESPCP consists of motor centralizer, motor, gear-reduction unit, tandem seal sections, and TTC crossover. A power cable is clamped to the outside of the tubing and is run from the motor to surface, and a separate instrument wire is run for a downhole gauge located in a side-pocket mandrel above the ESP assembly. The TTC crossover (Fig. 1) is what allows pumps to be pulled while the motor, gear-reduction unit, seal section, tubing, instrument wire, and power cable are left downhole. The slickline-deployed TTC components consist of a pump assembly, a packoff assembly, and a slipstop. The pump assembly consists of a pump "eye" (Fig. 2), which couples the pump to the TTC crossover, and pump and discharge assembly, which includes a centralizer and fishing neck.

Individual well flowing rate recovery from PDG transient pressure with either assigned daily rate or total cumulative production of the well or group of wells through wavelet approach

The advent of permanent down-hole gauge (PDG) makes the real-time reservoir monitoring and management possible, where the long term transient data can be processed to distill information about the reservoir through using recently developed wavelet transform algorithm. However, the key in analyzing the PDG data, particularly transient pressure, is to get the flowing rate history right during the pressure draw downs and build ups. In practice, the most available flowing rate data include assigned daily rate, total cumulative production of the well or group of wells with a measurement error tolerance at about ±10%. While multiphase down home rate data is rather expensive to have, the industry is desperately looking for ways to get the flowing rate history right. The second big problem in analyzing long term PDG data is that there is a time shift between the flowing rate and the corresponding transient pressure. In other words, when the rate goes up, the pressure also goes up instead of going down as expected. This caused a big problem in reservoir simulation, history matching and numerical well testing. This paper presents a technique based on the recently developed wavelet approach to recover flowing rate history directly from the measured PDG transient pressure, under the most common practical conditions described above. In this method, the exact timing of the rate change is identified through wavelet high frequency analysis. Then the rate and pressure are synchronized in every identified time intervals. Since the rate and the frequency amplitude of the transformed transient pressure are proportional, the real rate value in each time interval can be derived under the given common practical conditions. Both synthetic and field examples were used to demonstrate and further validate the developed technique, which showed very promising results.

Technology Focus: Hydraulic Fracturing (March 2009)

Technology Focus "Besides black art, there is only automation and mechanization."—Federico Garcia Lorca, Spanish poet and playwright (1898–1936) On this basis, fracture stimulation sits firmly in the realm of mysticism, crystal balls, and tarot. The reason for this is that unlike automation (e.g., car manufacturing) we still are uncertain of what makes fracture stimulation "work" (i.e., the critical components) and of how we evaluate and improve performance (i.e., of what constitutes a "vehicle service"). The car industry understands the components that make a car operate because each is built meticulously and repetitively. The key components that drive fracture stimulation are more difficult to determine because the process is subject to a high degree of variability in subsurface conditions. And what adds more "smoke and mirrors" to stimulation design is that much of the research that forms our basic understanding was developed more than 30 years ago on tight gas reservoirs, which bear no resemblance to the shale, coal, or unconsolidated sands stimulated today. In other words, while we have paid for a Rolls Royce we unwittingly may be driving a DeLorean. The automotive industry assesses the performance of its cars through periodic, thorough checkups. How often do we conduct a multicomponent service on our stimulation treatments? Microseismics, continuous reservoir monitoring (by use of distributed-temperature surveys and permanent downhole gauges), and radioactive-fluid tracers are some of the technologies used to determine the "health" of stimulation treatments. Their use, however, remains the exception not the rule. Usually, expensive stimulation-treatment checkups are avoided; instead, only the oil dipstick continues to be used (i.e., pressure and rate during injection and production). Is it not time that you better understood the key components "under the hood" and gave a complete service to your fracture-stimulation process? Only through better understanding will the "black art" be replaced by science, the performance be measured, and step changes truly be made. Hydraulic Fracturing additional reading available at the SPE eLibrary: www.spe.org SPE 116124 • "Case History of Sequential and Simultaneous Fracturing of the Barnett Shale In Parker County" by P.N. Mutalik, Williams Companies, et al. SPE 118831 • "Optical-Fiber Distributed Temperature for Fracture-Stimulation Diagnostics and Well-Performance Evaluation" by Paul Huckabee, SPE, Shell E&P SPE 119350 • "Stress Amplification and Arch Dimensions in Proppant Beds Deposited by Waterfracs" by N.R. Warpinski, SPE, Pinnacle SPE 111431 • "New Viscoelastic Surfactant Fracturing Fluids Now Compatible With CO2 Drastically Improve Gas Production in Rockies" by K. Hughes, Chevron, et al.

Application of Cationic Surfactant-Based Fluids for Acid Diversion

Summary This paper examines the use of surfactant gels during matrix acid treatments and describes field trials of these fluids. Unlike available viscoelastic surfactants used today in the field, this surfactant is cationic. If used in live acids, the fluid has a relatively low viscosity when pumped. Once the acid is spent, however, the surfactant molecules increase its viscosity significantly. To enhance diversion further, the acidic fluids or brines can be foamed with this surfactant. Rheological measurements were conducted on Hastelloy®- fitted rotational viscometers at temperatures ranging from 70 to 300°F. The effects of surfactant concentration, shear rate, temperature, and acid additives on the apparent viscosity of various surfactant-based fluids were investigated in detail. The surfactant was stable thermally and hydrolytically with most acid additives. While it was compatible (i.e., still formed a viscosifying gel), some additives adversely affected the apparent viscosity of surfactant solutions at a given temperature. The apparent viscosity of surfactant solutions increased with salt concentration and can be predicted by use of the Carreau-Yasuda model. Coreflood tests indicated that the surfactant delayed acid breakthrough in calcite cores. Acceptable corrosion rates were obtained when this surfactant was added to the acid. The performance of this surfactant was validated with field treatments. The surfactant was used in more than 100 matrix acid treatments (oil producers and water injectors). It was used to increase the viscosity of acids in situ and enhance the stability of foams used for diversion. All wells responded positively to these treatments, and no operational problems were encountered. Downhole gauges confirmed the ability of surfactant-based fluids to divert the acid into various zones.

Interference Testing to Characterize the Injection Behaviour of a 20-Acre Pattern in the Court Field

Abstract In the Court Field, the middle Bakken Sand Pool has been operated as a heavy oil waterflood for over 15 years. However, unrecovered oil volumes in the pool remain attractive for improved recovery schemes. Recently, the Court Middle Bakken Reservoir model was updated to evaluate the potential for downspacing and waterflood optimization of the reservoir. The potential for 20-acre downspacing for both infill drilling and additional water injection was identified by this study. As part of the additional development program, an injector producer well pair was drilled to create a new injection pattern with reduced inter-well spacing. Reservoir pressures, water saturation and effective permeability to water in the pattern were determined by RFT and log data. Pattern characterization was complemented by an interference test, including all the wells in the pattern. Analytical and numerical tools were used in the test design. The most comprehensive results were obtained by local grid refinement of the pattern area in the full field simulation model. Unavoidable interference with a neighboring pattern during the test was predicted. In order to account for this effect, it was decided to run the test with the new injector active intermittently. The complete test design and analysis of the results are described. In addition, a comparison of pressure measurements by downhole gauge and acoustic well sounder are presented. Introduction The Court Field, located in west central Saskatchewan, produces 17 ºAPI heavy crude from the Middle Bakken Formation, using vertical wells and a waterflood recovery scheme. The Court Bakken Sand was discovered in November 1981. The Court Bakken Sand Voluntary Unit No. 1 was formed in 1988 and waterflood commenced with only 2% of OOIP produced. There are 39 producing oil wells and 21 water injection wells currently in operation within the main pool. The current recovery factor is approximately 20%, with some wells producing up to 30m3/d oil. Recently, Majcher et al.(1) presented a geological and engineering overview of the reservoir. The Middle Bakken Formation was deposited as NE-SW trending sand ridges. The pool has undergone significant collapse of the Torquay Formation with the subsequent creation of extensive post-depositional sinkholes within the Bakken. This structural deformation interrupts the lateral continuity of the sand ridge and its characterization is the most challenging to further field development and effective waterflood management. Another important Bakken heterogeneity is the change in well log signature that represents the variation in facies at the ridge edges(2). This facies distribution within the Middle Bakken correlates with the waterflood response. Majcher et al.(1) identified the potential for infill drilling of producers and injectors near the edges of the pool. An injector-producer pair was recently drilled in Section 36-033-28W3M on 20-acre spacing. An interference test with four wells was conducted to investigate how the heterogeneities described above affect the waterflood performance of the newly configured pattern.

A New Method for Estimating Average Reservoir Pressure: The Muskat Plot Revisited

Summary This paper describes a new method for estimating average reservoir pressure from long-pressure-buildup data on the basis of the classical Muskat plot. Current methods for estimating average reservoir pressure require a priori information about the reservoir and assume homogeneous reservoir properties or use empirical extrapolation techniques. The new method applies to heterogeneous reservoirs and requires no information about reservoir or fluid properties. The idea of the method is to estimate from the pressure derivative the first few eigenvalues of the pressure-transient decay modes. These values are characteristic of the reservoir and fluid properties, but not of the pressure history or well location in the reservoir. The smallest eigenvalue is used to extrapolate the long-time behavior of the transient to estimate the final reservoir pressure. The second eigenvalue can be used to estimate the quality of the estimate. Numerical tests of the method show that it estimates average reservoir pressure accurately, even when the reservoir is heterogeneous or when partial-flow barriers are present. Examples with real data show that the behavior predicted by the theory is actually observed. We expect the method to have value in reservoir limits testing, in making consistent estimates of average reservoir pressure from permanent downhole gauges, and in characterizing complex reservoirs.

Use of Wavelet Transform in Pressure-Data Treatment

Summary Since the beginning of the 1980s, more downhole pressure gauges (DPGs) were installed in production and injection wells. The main purpose was well monitoring and evaluation of reservoir performance. This kind of gauge provides a large amount of data, but there are various problems that do not allow their complete use. These problems are related to quantity and quality. Most software is not able to handle the main objective for using DPGs with all the data available in a long recording period. Besides that, gauges present noise and strange data (outliers). It becomes necessary to treat the data before its use in the study of reservoir behavior. The concept of wavelet transform (WT) was developed about a century ago, but it was during the 1980s that it received practical application. Now it is used in a wide variety of applications, and, especially in data treatment, it presents two main features that make it attractive: smoothing of the signal and retention of the details. In this paper, we use the WT to overcome the main problems and enhance the reliability of the information contained in the data. We tested different wavelets with several decomposition levels against actual and synthetic data. The outliers must be removed before the wavelet analysis in order to enhance its performance. We show that there is no unique "correct" WT to apply in any flow period. For example, for some data sets the Daubechies 1 wavelet at decomposition Level 6 was used for flow periods, and Level 3 for buildup. It is important to notice that the use of high decomposition levels may cause loss of information, as is shown in some examples. The wavelet analysis was also used to recognize transients from its ability to enhance the details. This is particularly useful to identify flow rate changes when they have not been reported, for example. Finally, we propose a methodology to treat the data before its use in posterior interpretation.