Slug to annular flow pattern transition (SAT) taking place during the upward gas-liquid well transportation is a source of flow instabilities often experienced with conventional gas lifting as well as with unloading operations of water accumulated at the bottom level of gas wells in low-pressure gas or coalbed reservoirs. In order to minimize the pressure drop and gas compression work, gas lifting of relatively large volumes of fluid (oil and water) uses mainly a slug flow pattern while the production of gas with relatively small amounts of condensate or water (unloading operation) uses an annular flow pattern. In both situations, significant decreasing of tubing pressure from perforation to wellhead levels, is associated to significant increase of superficial gas velocity, may induce flow pattern transitions (usually from bubble to slugs and, further from slugs to annular).
This paper uses field data and laboratory measurements to suggest that SAT can be a source of flow instabilities and should be avoided.
Understanding and proper prediction of SAT is particularly essential for developing suitable production operations and for designing effective gas lifting or unloading strategies from low-pressure gas and oil reservoirs (including upward transportation of hot fluids resulting from steam-assisted heavy oil operations).
With depletion of existing gas reservoirs trend the need for effective gas well deliquification is in great demand. Transportation of water produced at the perforation level (usually between 10-60 m3/d) over a vertical depth of 200 to 2000 m under low (often variable) reservoir pressure (< 50 m of water) ask for finding un-conventional and effective artificial lifting strategies. Improving the understanding of gas-liquid upward transportation mechanisms including the avoidance of instabilities induced by flow pattern transitions is essential.
This paper addresses this problem through laboratory measurements of steady and oscillatory components of flow-pressure under a broad range of gas injected rate and simulated reservoir pressures. Comparison of laboratory data with existing STA models is performed first; selected models are then tested for field situations.
Effective field strategies for avoiding the SAT occurrence using either a slug or an annular flow pattern regime under low-pressure and standard (IPR) reservoir conditions are discussed in view of practical field applications and selection of a suitable gas lifting strategy.
The Oligocene Vicksburg formation in South Texas has been a prolific play for many years with targets of thick and stacked sand bodies. These thick sections have been primarily exploited and produced. Still existing are many previously considered uneconomical sequences. These marginal sections consist of highly laminated sand shale sequences along with disbursed clay in sand. Standard cutoffs from basic log evaluation work correctly for the disbursed clay sections. But the cutoffs are inadequate for the highly laminated sequences; many thin, high-quality sands have been overlooked. These sections can now be discerned using microresistivity measurements in oil-based mud systems and new high-resolution cutoffs can be employed.
A production prediction model is critical to enhance the chance of success. The model used here employs a petrophysically consistent high-resolution permeability estimate, fracture geometry prediction, and formation pressure. The methodology identified several sands as commercial that have been bypassed in offsets with the old cutoffs.
Over a two-year drilling program, data gathered from several field example wells were analyzed. These are presented here to illustrate how production data was utilized to continuously adjust and calibrate the high-resolution petrophysical model. The incremental revenue from the added pay exceeded the cost of this new methodology and enhanced the economic viability of the field.
This integrated process of measurement, analysis, prediction, evaluation, and model adjustment enables the operator in South Texas to make timely completion decisions as well as set-pipe decisions. This process is becoming a useful tool for further exploitation of the mature Oligocene Vicksburg formation of South Texas.
The Vicksburg formation in South Texas has been exploited since the 1920s and is still a prolific producer with over 20 Bcf per year average rate (Fig. 1). The play has seen both productivity increases and declines depending on gas prices and technology drivers. Since the mid-1990s, however, the trend has been ever-decreasing productivity and faster rate declines. At the same time, only 12% of the estimated 3,860 Bcf ultimate recoverable designated tight gas in Vicksburg has been produced, leaving much to be recovered. Some of this recovery can be enhanced with recently developed high-resolution technology.
The decision on whether to set pipe or complete a particular zone usually is made once the logging run is complete. During the standard logging run, the analyst will view the density porosity output and question the economics. "What is the porosity cutoff to make a well here??? The answer is found over years of experience and the school of hard knocks. Typically a "Rule of Thumb?? is used and a line is drawn (Fig. 2). Many South Texas partners make their decisions based on these cutoffs and individual experience. Worthington gives a comprehensive perspective on the use of these cutoffs. The cutoff number most often used in the Oligocene Vicksburg trend of South Texas is 15-16% porosity (Fig. 2). More recently there has been success at much lower porosity in the range of 8-10%. Obviously, if a 16% porosity cutoff was applied routinely, then somewhere in the thousands of wells drilled, some pay has been bypassed.
One solution that has been used primarily in water-based systems has been laminated sand analysis. This type of analysis has been applied since the early 1990s primarily in turbidite plays and not verified with production. The analysis used here verified with production data, provides a better answer for the less obvious and often bypassed pay sands.
Coalbed methane (CBM) reservoirs commonly exhibit two-phase flow (gas+water) characteristics, however commercial CBM production is also possible from single-phase (gas) coal reservoirs, as demonstrated by the recent development of the Horseshoe Canyon coals of western Canada. Commercial single-phase CBM production also occurs in some areas of the low-productivity Fruitland Coal, south-southwest of the high-productivity Fruitland Coal Fairway in the San Juan Basin, and in other CBM-producing basins of the continental United States. Production data of single-phase coal reservoirs may be analyzed using traditional techniques commonly used for conventional reservoirs. Complicating application, however, is the complex nature of coal reservoirs; coal gas storage and transport mechanisms differ substantially from conventional reservoirs. In addition, single-phase coal reservoirs may display multi-layer characteristics, dual porosity behavior, permeability anisotropy etc.
The current work illustrates how traditional single-well analysis techniques, such as type-curve and pressure transient analysis, may be altered to analyze single-phase (un-stimulated and hydraulically-fractured) CBM wells. Examples of how reservoir inputs to the type-curves and subsequent calculations are modified to account for CBM reservoir behavior are given. This paper demonstrates, using simulated and field examples, that reasonable reservoir and stimulation estimates can be obtained from production data analysis of coal reservoirs only if appropriate reservoir inputs (i.e. desorption compressibility, fracture porosity) are used in the analysis. As the field examples demonstrate, type-curve and pressure-transient analysis methods for production data analysis are not used in isolation for reservoir property estimation, but rather as a starting point for single- and multi-well reservoir simulation, which is then used to history-match and forecast coal well production (ex. reserves assignment).
Coal reservoirs have the potential for permeability anisotropy because of their naturally-fractured nature, which may complicate production data analysis. To study the effects of permeability anisotropy upon production, a 2-D, single-phase, numerical CBM reservoir simulator was constructed to simulate single-well production assuming various permeability anisotropy ratios. Only large permeability ratios (>16:1) appear to have a significant effect upon single-well production characteristics.
Multi-layer reservoir characteristics may also be observed with coal reservoirs because of vertical heterogeneity, or in cases where the coals are commingled with conventional (sandstone) reservoirs. In these cases, the type-curve and pressure transient analysis techniques are difficult to apply with confidence. Methods and tools for analyzing multi-layer CBM (+sand) reservoirs are presented. Using simulated and field examples, it is demonstrated that unique reservoir properties may be assigned to individual layers from commingled (multi-layer) production in the simple 2-layer case.
Hernandez, Gonzalo (Texas A&M University) | Bello, Rasheed Olusehun (Texas A&M University) | McVay, Duane Allen (Anadarko Petroleum Corp.) | Ayers, Walter Barton (Anadarko Petroleum Corp.) | Rushing, Jay Alan (Anadarko Petroleum Corp.) | Ruhl, Stephen K. (Texas A&M University) | Hoffmann, Michael F. | Ramazanova, Rahila I.
Carbon dioxide (CO2) from energy consumption is a primary source of anthropogenic greenhouse gas. Injection of CO2 in coalbeds is a plausible method of reducing atmospheric emissions, and it can have the additional benefit of enhancing methane recovery from coal. Most previous studies have evaluated the merits of CO2 disposal in high-rank coals. The objective of this research is to determine the technical and economic feasibility of CO2 sequestration in, and enhanced coalbed methane (ECBM) recovery from, low-rank coals in the Texas Gulf Coast area. Our research included an extensive coal characterization program, deterministic and probabilistic simulation studies, and economic evaluations. We evaluated both CO2 and flue gas injection scenarios.
In this study coal core samples and well transient test data were obtained for characterization of Texas low-rank coals. Simulation studies evaluated the effects of well spacing, injectant fluid composition, injection rate, and dewatering on CO2 sequestration and ECBM recovery.
Probabilistic simulation of 100% CO2 injection in an 80-acre 5-spot pattern indicate that these coals can store 1.27 to 2.25 Bcf of CO2 with an ECBM recovery of 0.48 to 0.85 Bcf. Simulation results of 50% CO2 - 50% N2 injection in the same 80-acre 5-spot pattern indicate that these coals can store 0.86 to 1.52 Bcf of CO2, with an ECBM recovery of 0.62 to 1.10 Bcf. Simulation results of flue gas injection (87% N2 - 13% CO2) indicate that these same coals can store 0.34 to 0.59 Bcf of CO2 at depths of 6,200 ft, with an ECBM recovery of 0.68 to 1.20 Bcf.
Economic modeling of CO2 sequestration and ECBM recovery for 100% CO2 injection indicates predominately negative economic indicators for the reservoir depths and well spacings investigated, using natural gas prices ranging from $2 to $12 per Mscf and CO2 credits based on carbon market prices ranging from $0.05 to $1.58 per Mscf CO2 ($1.00 to $30.00 per ton CO2). Injection of flue gas (87% N2 - 13% CO2) results in better economic performance than injection of 100% CO2.
Moderate increases in either gas prices or carbon credits could generate attractive economic conditions that, combined with the close proximity of many CO2 point sources near unmineable coalbeds, could generate significant CO2 sequestration and ECBM potential in Texas low-rank coals.
Low permeability, or "tight??, gas reservoirs are being developed at an ever increasing rate in the U.S. The amazing increase in activity in the Rocky Mountain region over the past decade is a testament to this. Currently, there are several "tight?? gas plays in the U.S. that involve the commingling of multiple intervals in order to gain economic viability. The Pinedale Anticline of southwestern Wyoming is one of these areas. The Pinedale Anticline completions pose a particularly complex problem when attempting to evaluate the "best?? method of stimulation because as many as twenty-two separate stimulation treatments are placed in up to 70 discrete sand intervals over a gross interval up to 6,000 feet thick. Evaluations are further complicated by variation in permeability exceeding two orders of magnitude and pore pressures increasing from 0.44 psi/ft to 0.83 psi/ft.
The analysis of "tight?? gas reservoirs has been the topic of many SPE papers over the past twenty years. Several have presented data indicating the broadness of the permeability distribution which may be encountered when developing these reservoirs.[1,2,3] The broadness of the permeability distribution, often over two orders of magnitude in breadth, poses a statistical problem when trying to simply compare production response of one set of data to another in a given field. We will quantify the significance of this and present statistical evaluations documenting the probability of obtaining two similar data sets with respect to permeability when broad distributions exist. We then compare the size of the sample set necessary to quantify stimulation effectiveness using production alone with the sample size required when using reservoir simulation.
The reservoir simulation analysis presented in the paper demonstrates a process for use in multiple layered reservoirs for evaluating stimulation effectiveness. The process requires significantly fewer field tests than if production rates were used alone. Multiple production logs were utilized over several producing months in selected wells and are crucial to the production history match process. A wide variety of proppant products are investigated and compared to expected performance from published specifications. This paper will aid engineers working in multi-layered reservoirs understand the complexity of the evaluation process and give them a process for evaluating stimulation effectiveness in their reservoirs.
Permeability, a major reservoir property that reservoir engineers strive to measure as accurately as possible, is nevertheless always measured indirectly, by estimation, either through well-testing or specific logging tools and techniques. Permeability measurement utilizing reservoir rock samples does not necessarily guarantee accurate results, as fluid saturation of rock samples may change dramatically due to stresses and pore pressure changes take place during coring and transportation of samples to the laboratory for testing. In attempting to extrapolate fluid flow behavior in the reservoir from such samples, tremendous efforts have been directed up to now towards producing useful meanings of horizontal, vertical and directional permeabilities.
This paper introduces a new permeability measurement approach that brings fresh understanding to reservoir permeability and a truer reflection of fluid flow behavior around producing wells. The traditional use of horizontal, vertical and directional permeabilities to reflect the conductivity of a formation to fluid flow is often misleading. Actually, the flow comes from everywhere in the reservoir and reduces to the wellbore, and in many cases ended at the perforations. The flow pattern takes a shape of a cone where the base is at the boundary and the head is at the wellbore or the perforation opening. This flow pattern produces a conical or "tapering?? permeability. This new 3-D permeability term should enhance the accuracy of the models used to represent fluid flow in porous media.
A three-dimensional permeability term is newly introduced here. A three-dimensional spot gas permeameter device and techniques for measuring this term have been constructed in the laboratory. This device is intended to enable direct measurement of gas permeability at any spot on the surface of the sample, regardless of sample shape or size.
The issues of probe sealing and gas slippage have been resolved by introduction of a rubber baker at the tip of the probe, and by allowing low-pressure injection. A new mathematical model has been derived to describe the flow pattern associated with measuring gas permeability using the proposed device. The proposed mathematical model along with numerical solution presented is expected to find application beyond the gas permeameter case, as its usefulness is proven more relevant to reservoir behavior.
To exploit the substantial tight-gas resources worldwide, hydraulic fracturing is, for many cases, economically a viable option. However, despite the state of the art techniques such as multiple fracturing of horizontal wellbores, the gas recovery from these reservoirs is frequently unsatisfactory. Poor reservoir rock quality, strong stress dependency in permeability, hydraulic and mechanical damage caused by the fracturing process and inertial non-Darcy flow effects were considered to be key parameters for poor performance in previous studies. A further one, related to the cleanup of the cross-linked fracturing fluid with its non-Newtonian characteristics, was rarely taken into account before and is the subject of the current paper.
For this purpose, an enhanced three-phase cleanup numerical model is developed. A generalised non-Newtonian fluid flow model for porous media is derived and implemented in a reservoir simulator, capturing the yield stress of common polymer gel.
The model is applied to typical cleanup scenarios. Using the model, it can be shown that the residing, non-recoverable gel (typically 50%) decreases the fracture conductivity and, hence, the production potential of a fractured gas well. This coincides with experiences in the field where these parameters are frequently lower than anticipated. Results of the study further indicate that within the fracture, gel saturations gradually increase towards the fracture tips. Contrary to the assumption made in analytical studies, there is no sharp interface between the residual gel and the reservoir fluids after the cleanup.
The new non-Newtonian fluid flow implementation allows for more detailed investigations of fracture cleanup processes and, hence, an improved understanding of formation damage processes in fractured wells. Furthermore, the model enables the design of more successful fracture treatments in tight-gas reservoirs.
This paper illustrates a practical systematic approach to determine the reservoir flow characteristics and reserves for both conventional and unconventional gas wells. Currently, there is an industry assortment of production analysis methods ranging from exponential decline and typecurve matching to rate-pressure normalization techniques and detailed production history matching. Through real life cases studies it will be shown that it is possible that a simpler reservoir model, such as a single well completed in the center of a circular reservoir, could be used to represent far more complex reservoirs, and still provide some representative reservoir characterization, as well as accurate reserves analysis and production forecasting. As a result, it possible that engineers and the like can avoid some of the more labor intensive production data analysis (PDA) techniques, and use more a methodology similar in operation to traditional decline.
Case studies and experience presented in this paper will demonstrate that a simple approach of production analysis methods will allow for a) proper identification of flow regimes, b) reliable evaluation of drainage area and OGIP, and c) the prediction of future deliverability and depletion. Case studies will also show that up-scaled and aggregate reservoir properties can provide a real measure of gas well deliverability (therefore a simpler, time-efficient model analysis can be used). Data uncertainty, unconventional gas (i.e. coal bed methane, tight gas, shale gas), stimulation appraisal, and other factors will be discussed in the context of the case studies.
A new fracture-injection/falloff type-curve analysis method is presented for reservoirs containing slightly compressible and compressible fluids. Type-curve analysis augments conventional before- and after-closure methods, which are also reformulated in terms of adjusted pseudopressure and adjusted pseudotime to account for compressible reservoir fluids. Unlike before- and after-closure methods which only apply to specific (i.e., small) portions of the falloff data, the new type-curve method allows for analyzing all falloff data from the end of the injection through fracture closure, pseudolinear flow, and pseudoradial flow. Similar to conventional well test analysis, a satisfactory interpretation requires comparable and consistent results between the special analysis methods, before- and after-closure, and type-curve analysis.
Accuracy in hydrocarbon reserves estimates affects virtually every phase of the oil and gas business. Unfortunately, reserves estimates are uncertain, since perfect information is seldom available from the reservoir, and uncertainty can complicate the decision-making process. Managers have to make many important decisions early (e.g., facilities expansions, development drilling, etc.) without reliable knowledge of reserves. Thus, it is probably more important to quantify reserves uncertainty early than any other time in the life of a reservoir.
Reserves are closely related to original hydrocarbons in place (OHIP). Two methods for estimating OHIP are volumetric and material balance methods. The volumetric method is convenient to calculate OHIP during the early development period, while the material balance method can be used later, after some performance data, particularly pressure and production information, are available. Both methods may have substantial uncertainty.
In this paper, we present a methodology that uses a Bayesian approach to quantify the uncertainty of original gas in place (G), aquifer productivity index (J), and the volume of the aquifer (Wi) by combining volumetric and material balance analyses in a water-driven gas reservoir.
The results show that we potentially have large uncertainty in OGIP estimates when we consider only volumetric analyses or only material balance analyses. However, by combining the results from both analyses, the uncertainty can be reduced. This reduction in uncertainty should lead to better management decisions in many cases.
The volumetric method is useful in calculating hydrocarbon reserves prior to availability of representative pressure and production data. This method uses static reservoir properties such as area of accumulation, pay thickness, porosity, and initial saturation distribution. Given the often large uncertainty due to paucity of well data early in the reservoir life, it is common to quantify the uncertainty of volumetric estimates of OHIP using statistical methods such as Monte Carlo analysis.
The material balance method can be used later when sufficient amounts of pressure and production data are available. The material balance method is simply an inventory of all materials entering, leaving, and accumulating in the reservoir. Since it relies on different data from the volumetric method, the method can be used as an independent check of volumetric estimates of initial hydrocarbon volumes in place in a reservoir. If the material balance method is properly applied, it can be used to estimate initial hydrocarbon volumes in place, predict future reservoir performance, and predict ultimate hydrocarbon recovery under various types of primary-drive mechanisms. Although uncertainties in material balance methods have been long recognized, they are often considered more accurate than volumetric methods, since they are based on observed performance data. It is not common practice to formally quantify the uncertainty in material balance estimates of OHIP.
Bayes' theorem[2-4] provides a mathematical basis for revising preliminary estimates of reservoir characteristics and their uncertainties when additional information becomes available. Floris et al. applied Bayes' theorem to quantify uncertainty in production forecasts from reservoir models conditioned to both static and dynamic reservoir data. Glimm et al. showed that the Bayesian approach can reduce the uncertainty in the prediction of unknown geological parameters in the simulation of an oil field. Galli et al. used the Bayesian approach to evaluate new information for choosing between different exploitation scenarios for a gas field. Ogele et al. used the Bayesian approach to combine volumetric and material balance methods and quantify uncertainty of OHIP estimates in gas-cap driven oil reservoir. They quantified the uncertainty of two parameters, original oil in place and relative gas-cap size, estimated using the Havlena and Odeh form of the material balance equation.