Prediction of Water Production in CBM wells

CHAPTER 7 Prediction of Water Production in CBM wells 7.1 Introduction Coal is a complex heterogeneous system with methane gas remaining adsorbed on coal surface by lithostatic and hydrostatic pressure as described earlier. Production of gas is controlled by depletion of pressure in the reservoir. Mostly, coal reservoirs are water saturated, and water develops the reservoir pressure to hold gas in the adsorbed state. As a result, water saturation in CBM reservoir is often nearly 100%, and this water must be produced to lower the reservoir pressure below the saturation pressure of methane to get desorbed and then produced. So, water production is much more important for coalbed methane projects compared to that of conventional oil or gas operations. Moreover, many CBM formations are often in communication with aquifer. As a consequence, it is likely that gas production from CBM formations will result in encroachment of water from the associated aquifers. This additional water must subsequently be pumped to the surface along with the desired methane. A successful production strategy that reduces water production and increases the methane production will depend on a variety of factors including cleat spacing, aquifer strength, efficient dewatering technique and sorption characteristics and variation in cleat permeability with pressure [Sawyer et. al., 1987]. The initial stage of the CBM production is the dewatering process. However, inefficient production may cause damage and changes in coal seams properties, which in turn will reduce the methane production. Thus, water production rate becomes one of the key factors to optimize the methane production from CBM reservoirs. Designing of water production rate thus becomes an important criterion for efficient recovery of gas. Moreover, in Indian field elaborated study on production aspect is yet to be explored. In this investigation, the dewatering is modeled as a function of water level which will help in optimizing the rate 167

and designing of artificial lift technique required to be installed in order to produce methane at the depletion stage. The area of present study is located in the Raniganj coalfield. Elaborations have been made in the present chapter on the dewatering technique of the CBM wells and optimization of water production rate for efficient and effective production of methane from coal beds, which not only optimizes the methane production but can also predicts the performance of the particular well of the basin. In general, water productivity of CBM wells is determined using type curve analysis [Aminian et al., 005], which is time consuming and require a number of data. However, here a simple correlation is developed to predict water production rate from the known water level or vice-versa [Agarwal et al., 013]. The model equation incorporates the variation of rock permeability with variation in pressure also. 7. Designing of well-testing in CBM wells Performance prediction tests are run routinely to physically measure oil, gas and water produced by a particular well under normal producing conditions. From the standpoint of well and reservoir operation, they provide periodic physical evidence of well conditions and unexpected changes if there is any. It is worth mentioning here that coal beds are very much fragile; rubbles and fines are formed during drilling as well as fracturing. These fines generally block the paths of water and gas to flow to the well due to lack of proper precaution. This can drastically reduce the water and gas production rate. Specially designed drilling fluid and fracturing fluids are used to prevent formation damage. Generally underbalanced drilling technology is adopted for drilling of coal bed. Air drilling is used widely for drilling of CBM wells. However, in presence water influx, air cannot be used. Application of light weight foam fluid which can take out the fines from fractures solves this problem. 7..1 Conventional Well For conventional oil well, results are usually reported as oil production rate. The test equipments consist of (i) a gas oil separator, (ii) a stock tank, with appropriate measuring devices such as (iii) an orifice meter for gas (iv) a hand tape for oil and water, and (v) down 168

hole pressure gauges which are run through coiled tubing unit. The tests must be conducted under stabilized producing condition since change in rate often influences the relative quantities of oil, gas and water. For gas wells routine production tests are less common, since gas production is usually metered continuously from individual well. The first problem confronting the petroleum engineer after the completion of an oil or gas well is to determine its capacity (productivity, potential). There are various other physical and mechanical parameters which may affect the delivery rate. These factors are different for conventional wells and CBM wells; thus the testing techniques are changed accordingly. For oil wells, there are a number of well-defined tests performed in the field for the estimation of flow potential. To determine the productivity index (P.I), the well is produced at various rates and the flowing pressures are recorded. The productivity index and flow potential are then determined from the formulae: Q PI. Pws P wf 7.1 Where, P.I. is the productivity index, Q is the liquid flow rate, m3/day, P ws is the Static Bottom hole Pressure, and P wf is the Flowing Bottom hole Pressure, psi. Subsequently many other tests are designed for oil wells because the above test alone may be unable to predict the conditions of the well properly. Similarly, for a conventional gas well, the test is called back pressure test. The relation between the production rate of a well and the respective flowing pressure may be expressed empirically by the formula [Beggs, 008] as given below: Q C P P ws wf, where, 703kh C 7. r TZ ln e r w Where Q is in Standard cubic feet per day, k in Darcy, h thickness of the pay zone in ft, μ in cp, T in R, P in psi and r in ft. z is the gas compressibility factor. 169

7.. CBM Well However, CBM reservoir behaves differently from the conventional oil and gas reservoir. In CBM reservoir, dewatering is essential to facilitate gas production. It is very important that the dewatering is done with immense precaution so that the fragile coal seams will not be damaged and the gas will be produced efficiently. In the present investigation the above guideline has been properly considered and the results were carefully analyzed to generate the model for the evaluation of water rate. The test steps are designed (Fig. 7.1) as follows: (i) (ii) (iii) (iv) First, the well is made to flow at a particular flow rate. At stabilized dynamic water level in the annulus, at different bottom hole pressures, water flow rates are noted. The tests are performed at various rpm of the pump. Flowing bottom hole pressure (FBHP) versus water flow rate are noted. The Following assumptions were made during the test: (i) the shut-in pressure gradient on each well was considered to be according to the geological study conducted in this area and found to be 1.41 psi/m. This gives the static reservoir pressure as the wells have just started the dewatering phase. (ii) The fluid flow was considered single phase as in most of the cases, flowing pressures are above critical desorption pressure of 754. psi, and the gas produced at surface was negligible. 7.3 Model to evaluate the productivity for a CBM well The CBM water productivity analysis is normally carried out using type curves but these methods are very time consuming. So in the present investigation, a model has been proposed which can estimate the water flow potential of the similar regions in the block from the dynamic water level only. The tests discussed above were conducted on a number of wells of the field and the results were carefully studied. Various empirical relations were made which could describe the flow property of the water in the initial dewatering phase. 170

Finally, a successful equation was derived which satisfied the flow conditions at the bottom hole. This model is very similar to the model used for the gas wells to evaluate the absolute open hole flow potential of gas and different from the conventional Darcy s equation. Water Flowing Pressure, P dynamic 30 0 P s P DY1 P DY T 1 T 10 0 0 40 60 80 100 10 140 Time, hr T 3 P DY3 T 4 Bottom hole water flowrate, Q w 30 0 10 Q w1 Q w4 Qw3 Q w T 1 T T 3 T 4 0 0 40 60 80 100 10 140 Time, hr Fig. 7.1: Test designed for water influx of the CBM well In general, we use Darcy s equation to describe fluid flow through a porous media with constant permeability. However, the situation is different for the coalbeds. Here, absolute permeability of coal cleats is stress dependent. Assuming the vertical lithostatic load is unchanged during depletion of pressure, the change in stress can be represented in terms of change in the reservoir pressure. As per Palmer-Monsoori model [Palmer and Monsoori, 1998] and IMC model [Shi and Durucan, 003], there is a continuous change in porosity 171

and permeability of coalbed with change in pressure. The equation used in Palmer- Monsoori model is given below: k k i 1 v exp c p p f 1 v i 7.3 Assuming a uniaxial stress regime with permeability controlled by horizontal stresses, the IMC model of Shi and Durucan equation is as follows: k k i v exp 3c p p f 1 v i 7.4 Where, k is the cleat permeability, is the initial permeability, is the cleat compressibility, psia -1, v is the poisson s ratio, is the initial pressure (psia) and p is the pressure (psia). According to IMC model, the permeability ratio (ratio of permeability at any pressure P to that at unstressed condition) increases exponentially with depletion in pressure. Incorporating the permeability variation with pressure, the flow equation is expressed as n Q C P P static dynamic 7.5 Where Q is the liquid flow rate, m 3 /day, P static is shut in water pressure at psi, P dynamic is the bottom hole flowing pressure at psi and n is the constant derived from the test plot. Analysis of these data also shows that the water flow rate varies exponentially with the dynamic water level. 17

The equation derived from the tests on CBM well was finally concluded to equation 7.5a. 7.5a Where Q w is the water flow rate at surface conditions, m 3 /day and C is the constant. The above equation may be expressed in terms of the water level as the density of formation water remains almost constant. Hence, n1 Q C1 WL WL w static 7.6 dynamic Where C1 is constant derived from the test plots, WL static is the static water level, m and WL dynamic is the dynamic water level in the well, m. As the static flow water level is generally known or constant, the production rate Q could be expressed as a function of dynamic water level only. Once a number of data s are available, the constants can be estimated and hence the water flow rate can be modified to optimize the dewatering phase of the CBM production well. Once the flow equation is known the well s current flow water potential (FWP) can also be estimated using the formula given below. n FWP C3 L 7.7 dynamic The above equation may be expressed in terms of the water level as the density of formation water remains almost constant. Hence n3 FWP C3 L 7.8 dynamic Using the above equation water flow potential can be determined easily with known dynamic water level. Hence, the pump rpm can be carefully monitored to change the water flow potential (Water Influx) of a well for optimizing the well conditions. Subsequent 173

Flow rate (m 3 /hr) CHAPTER-7 tests can also give an idea of the economic aspect of the well i.e. duration of dewatering period with total disposed water volume and starting of gas production. In Fig. 7., the water production rate (m 3 /h) is plotted against the dynamic water level (m) for the above mentioned field. Now using the production decline curve the water potential can be plotted to understand the dewatering profile and also the performance behavior of the well. Fig. 7.3 shows the way the water potential can be used to model a well and also to find the well behavior and the corresponding surface facility. This figure is a general decline curve, and no field data are plotted here. 5 4 3 well 6 well 5 well 4 well 3 well well 1 1 0 0 30 60 90 10 150 180 Dynamic Water level (m) Fig. 7.: Variation of flow rate with water level 174

Fig. 7.3: Water flow potential versus time of the CBM well 7.4 Results and discussion Petrophysical properties and coal characteristics are very important for analyzing the performance of the CBM reservoir. The important properties of the reservoir under study are described in Table 7.1 Well testing was conducted on a number of wells for characterization of the reservoir. The input data for the model equation were obtained from the various tests conducted on the 17 wells of the blocks as mentioned earlier. Fig. 7.4 shows the bottom hole pressures of different wells at the starting of test. It could be observed clearly that pressure of the reservoir is not unique and the initial bottom-hole pressure varies from 73 psi to 1390 psi depending on the position of the wells. As bottom hole pressures of most of the wells are near or above the critical desorption pressure of the reservoir, these are initially under single phase flow conditions. The gas production starts when pressure falls below the critical desorption pressure as well as when the gas saturation attains a minimum value of 175

critical saturation. For the present study, it was observed (Fig. 7.5) that the number of days required for gas to start gas flow varies almost linearly with bottom hole flowing pressure. This is expected because as the days of water production increases, the reservoir pressure is being reduced. As soon as the free gas saturation reaches critical gas saturation, it starts to flow. However, as the gas flow rate was very less compared to the water flow rate, single phase flow was assumed in developing the model equation. Table 7.1: Reservoir properties and coal properties of the study area parameter Value Average porosity, (%).84 Average permeability, (md).4 Density of the coal, (gm/cc) 1.4 Gas content, (scf/ton) 49 Langmuir volume (scf/ton) 801 Langmuir pressure, (psi)/kpa 353.6/437.90 Critical desorption pressure, (psi)/kpa 754./500.0 Initial water saturation, (%) 100 Maximum depth, (m) 980 Maximum seam thickness, (m) 4.5 Sorption time constant, (days) 0.5181 176

Fig. 7.4: Static bottom hole pressure of different wells Fig. 7.5: Time required for two phase flow as a function of time 177

Variation in water flow rate as a function of potential difference (P ws - P wf ) is plotted in Fig. 7.6 for different wells. Straight line is fitted to the data from each and every well. Average slope and intercept are determined using least squares method. Slope and intercept of the plot of Log (Q) vs. Log (P ws -P wf ) are 5.1067 and 1.096 respectively. Fig. 7.6: Variation of water production rate with pressure (Q in m 3 /day and P in psi) Coal matrix in the CBM reservoir is very much heterogeneous and stress dependent as mentioned earlier. Permeability of coal matrix varies largely from well to well (space to space); even in a same well it may vary depending on pressure changes. The constant value of C 3 incorporates the viscosity & density of water, permeability of matrix at unstressed condition, and cleat porosity [Saulsberry et al., 1996]. The standard deviation was determined using the formula S Q Q model field n 1 Where, number of data points, n=63. The calculated standard deviation, S=0.8849. 7.8 178

Fig. 7.7 shows the results of the test conducted on a number of wells. It may be observed from the figure that the water production rate increases with increase in the dynamic water level for each well. Fig. 7.7: Variation of water production rate with dynamic water level The relation between the water production rate and dynamic water level follows a power law model (Q α L dynamic ), which is mentioned earlier. The values of constant C 3 and n 3 are determined from the equation of trend line as 1.859 and 0.4799 respectively using data from seven wells. The equation becomes: L 0.4799 Q 1.85 7.9 179

Q model, m 3 /day CHAPTER-7 The Eq. (7.9) is now validated with three other wells as shown in Fig. 7.8. Production rate obtained from the model equation are plotted against the actual production rate of well no., 4 and 5 respectively for the same dynamic water levels. From the results it could be observed that except for one data, deviation of the test data from the model results are within the tolerable limit with a regression coefficient of 0.7346. 6.0 5.7 : Well Well 5 Well 4 5.4 5.1 4.8 4.8 5.1 5.4 5.7 6.0 Q test, m 3 /day Fig. 7.8: Validation of model equation (predicted versus test production rate, m 3 /day) 7.5 Conclusions The developed model can be used directly in the region to find the water potential of the pay zones and thus it can be used to design the artificial lift facility. The developed model is much faster and provides more accurate results compared to that of the conventional methods of CBM well test analysis. The water influx at a particular time can be formulated 180

from the above mentioned method using the correlation of Q with dynamic water level, L at any time and thus the capacity of the wells (water influx) has to be formulated for different wells at equal time interval, the graph is plotted with water flow potential versus time. This plot will give the general decline of the influx of the well. Once the graph is extracted, it can be extrapolated to find the water influx at the end of future time periods and finally the dewatering period of the well. So we can use the time parameter and find the maximum flow rate of the gas from the well. Thus, the developed model is a helpful mathematical tool in predicting the water production rate and designing of artificial lift for efficient production of methane from coal bed. 181