Rivera, Nestor (Chevron Corp.) | Meza, Nestor Saul (Chevron Energy Technology Co) | Kim, Jeoung Soo (Chevron Energy Technology Co) | Clark, Peter Andrew (Chevron Corp.) | Garber, Ray (Chevron Corp.) | Fajardo, Andres | Pena, Victoria
Structural, stratigraphic, and petrophysical uncertainties result in a wide range of geologic interpretations. For fields with long production and pressure history, 3D-dynamic simulations have been very useful in providing feedback to geologic modelers, which results in improved static models.
The Chuchupa Field has produced 1.9 Tscf of dry gas, or approximately 40% of the Original Gas in Place (OGIP). At the time of this study, 3 new horizontal wells were being planned, and new gas sales agreements were being considered. We developed a dynamic workflow to create a range of probabilistic simulation models to forecast dry-gas production under several production scenarios in the Chuchupa field. Recent seismic re-interpretation, a new stratigraphic study and a revision of the petrophysical model resulted in new probabilistic static models for the field.
While these static models were being built, a parallel numerical simulation study was conducted to determine the range of OGIP values that could be successfully history-matched. Nine numerical reservoir models were generated by applying pore volume multipliers to the prior-generation reservoir model, yielding a range of OGIP from 3.8 to 6.6 Tscf. We attempted to history match each of these nine models by using an optimization routine to adjust aquifer support, vertical transmissibility across a potential seal, and rock compressibility. The optimization routine proved to be a very useful and efficient tool to attain good quality history matches in short periods of time. Good matches were obtained for models with OGIP ranging from 4.3 to 5.8 Tscf.
Based on this information, the geologic modelers revised petrophysical parameters and generated 27 static models. These models encompassed 3 structural interpretations, 3 porosity distributions, and 3 possible positions of gas/water contact (GWC). From experimental design we obtained the P10, P50, and P90 OGIP values of 4.1, 4.7, and 5.3 Tscf respectively.
We scaled up and built reservoir simulation models for 8 geologic interpretations to represent the range of OGIP and reservoir geometries. Again, these models were history matched using the optimization routine. The match parameters were static well pressures and the absence of water production. Six out of the eight the models could be satisfactorily history-matched with reasonable adjustments to aquifer strength, vertical transmissibility, and rock compressibility. The OGIP range for these models was 4.1 to 5.6 Tscf.
We selected 3 models to forecast future gas production. These models match the P10, P50, and P90 OGIP values determined in the probabilistic static model, and combine the low, mid, and high structures, porosity and Swi distributions, and the range of GWC positions. We also calibrated the various models with historical bottomhole and tubinghead flowing pressures, and coupled the reservoir model with a network consisting of surface lines and equipment; pipelines from two platforms to the onshore sale-point station; and multi-stage compression to 1,215 psia. The model is currently used to evaluate various production and market scenarios.
Modern computing power has enabled very high accuracy and efficiency in complex calculations. Thus, it follows that reservoir engineering formulations need not be approximate solutions, as was sometimes historically the case. Being one of the most widely used techniques in reservoir engineering, the material balance equation (MBE) for gas is an excellent example of this. The MBE is used not only for estimating the original gas-in-place (OGIP), but also for calculating the decline in average reservoir pressure with depletion. In the majority of cases, the conventional p/Z formulation of the gas material balance is satisfactory. However, certain circumstances, which are sometimes unpredictable, demand formulations with greater accuracy. Although modifications to the standard approach have been presented, to the authors' knowledge, there is no published gas material balance formulation that is completely rigorous. This study presents a new, rigorous MBE for gas flow in the presence of a compressible formation and residual fluid saturation. Examples will be presented to highlight the capabilities of the new MBE.
Vibration of drillstring was found responsible for the severe damage and premature failure of drillstrings during drilling the gas-bearing igneous formations in the Songliao Basin, China. The vibration significantly shortened the life of drillstrings and had a great impact on drilling performance in the area. The objective of this study was to identify the key factors affecting drillstring vibration and develop a control-mechanism to reduce the failure rate of drillstring.
This study investigated the combined effect of axial and torsional vibrations on the damage of drillstring. A computerized model was built to simulate loads from axial and torsional vibrations. An analytical method for predicting the fatigue life of drillstring was developed. The method uses the output from the computerized model. Engineering charts were also generated for typical drilling conditions. These charts have been adapted in a Drillstring Damage Control Program implemented in the Songliao Basin, China.
Gas hydrates are a significant resource of natural gas exist both on-shore buried under the permafrost and off-shore buried under oceanic and deep lake sediments. Recent investigations consider the possibility of sequestering carbon dioxide (CO2), a greenhouse gas (GHG), in gas hydrate reservoirs and at the same time recovering the methane (CH4) from the hydrates. Numerical studies often provide an integrated understanding of the process mechanisms in predicting the potential and economic viability of CH4 gas production and CO2 gas sequestration in a geological reservoir.
This work describes a new unified kinetic model which, when coupled with a compositional thermal reservoir simulator, can simulate the dynamics of CH4 and CO2 hydrates formation and decomposition in a geological formation. The kinetic model contains two mass transfer equations: one formation equation transfers gas and water into hydrate and one decomposition equation transfers hydrate into gas and water. The model structure and parameters were investigated in comparison with a previously published model.
The proposed kinetic model was evaluated in two case studies. Case 1 was a single well natural hydrate reservoir for studying the kinetics of CH4 and CO2 hydrates decomposition and formation. Case 2 was a multi-well reservoir for studying the unified kinetic model to demonstrate the flexibility of CO2 sequestration in a natural hydrate reservoir with potential enhancement of CH4 recovery. A close agreement was achieved between the present numerical simulation and the published results. The model can be applied in the field scale simulation to predict the dynamics of gas hydrates formation and decomposition processes in a geological reservoir.
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.
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.
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.
In conventional gel fracturing treatments, the damage induced by the gel can have a significant impact on well performance, particularly in low permeability gas formations. Slick-water fracs have been shown to be more successful in some tight gas formations because of reduced gel damage and limited height growth. Proppant placement is a major concern in water fracs. Hybrid water-fracs (using slick water as the pad fluid and gel to place the proppant) provide some improvements to the performance of water-fracs.
This paper proposes a new method, reverse-hybrid fracs (RHF), for the efficient placement of proppant deep into created fractures while minimizing gel induced damage. Experiments were conducted in a simulated fracture (slot cell) to study the transport of proppant. Slick-water was injected first into the slot, followed by gel. Finally slick water containing proppant was injected to displace the gel. The water that carried the proppant, quickly formed viscous fingers through the gel. The gel was observed to form long thin layers which effectively hindered proppant settling and helped transport the proppant further into the slot. This resulted in the formation of proppant packs above the gel layers.
In this paper, experimental results are presented to show how the gel layers distribute in the slot and how proppant distribution is affected by the gel layers. A transparent cell made up of rough walls was set up to investigate the effect of fracture wall roughness. The effects of fluid viscosity ratio, fracture wall roughness and gel pad volume were investigated. Based on the experiments and scaling relations, recommendations are made for the pumping sequence and the size of the gel and slick water stages in reverse hybrid fracture treatments.
This method of proppant placement requires less gel than conventional gel-fracs and smaller pump horsepower than water-fracs. Other advantages include: less gel damage to the proppant pack and less penetration of the pad fluid into the formation resulting in shorter cleanup time following fracture treatment.
In a fracturing treatment, the effective fracture lengths achieved (as measured by matching the production response or from pressure transient tests) can quite often be significantly smaller than the created fracture lengths (as measured by fracture mapping techniques). This difference can be attributed to inadequate proppant transport and / or insufficient fracture cleanup.
In hybrid-fracs, low-viscosity, slick-water is used to create the fracture, while a high-viscosity gelled fluid is used in the proppant stage. In some fields, the use of hybrid-fracs has resulted in a significant increase in effective fracture lengths and well productivity (Ref 1). The use of hybrid-fracs can, under certain conditions, result in the increased possibility of tip screenout. Since the fracture is being created with a high leak-off, low-viscosity fluid, the smaller fracture widths can result in premature tip screenout.
This is the primary motivation for using reverse-hybrid fracs. As the name suggests, the sequence of fluid injection is the reverse of what is used in hybrid fractures, a high viscosity polymer (linear or cross-linked) fluid is used to create the fracture while the proppant is pumped, behind this high viscosity pad, in a low viscosity fluid. This kind of treatment is referred to as Reverse-Hybrid Fracs (RHF) in this paper
The unfavorable viscosity contrast results in viscous fingering of the proppant-laden slick-water through the viscous fluid. Vertical settling of the proppant is hindered by the layers of high viscosity gel that are created by the viscous fingers. This also allows the proppant to be placed deeper in the fracture, than if the displacement were stable. The proppant horizontal flow velocity will be much higher than proppant carried by the gel due to the much higher fingering velocity of the proppant laden water. Proppant particles accumulate above the gel layers and form a proppant-pack. This proppant pack can keep more proppant from settling and increases the propped area of the fracture. This paper investigates factors that affect the formation of viscous fingers and gel layers experimentally and describes how various factors affect the proppant distribution in the fracture.
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.