Bottom Hole Pressure Calculation Research Articles

Experimental Investigation of Spherical Particles Settling in Annulus Filled with Rising-Bubble-Containing Newtonian Fluids

During the drilling of ultra-deep wells, gas kick often occurs, influenced by the complex void pressure profile. The accurate description of particle settling behavior in the gas–liquid mixture is of great significance to effectively deal with gas kicks and ensure drilling safety. In this study, the gas–liquid two-phase annulus flow with different gas volume fractions is created through the transparent annular pipe, constant pressure air pump, and gas flowmeter. High-speed photography is used to record and analyze the sedimentation of particles in gas–liquid mixtures. This study is based on 288 tests. The main parameters in this experiment include the particle Reynolds number, the gas fraction, and liquid viscosity. The effects of wall and gas fraction on the drag coefficient were analyzed. The correlation of particle terminal settling velocity was established. The results obtained show a correlation with average absolute errors (AAE) of 10.7%. This study reveals the settling characteristics of particles in the annular gas–liquid mixed flow, provides an accurate terminal settling velocity prediction explicit formula, and provides guidance for the calculation of bottom hole pressure under the condition of gas kick.

Devon Energy and Software Partners Enable Automatic Bottomhole Pressure Calculations

_ More than a decade ago, Devon Energy made it a priority to enhance its digital infrastructure which has led to a step change in internal data access along with how the company securely works with its third-party vendors. Easy access to relevant, trustworthy, and value-adding data has become the norm, not the exception, for the US oil and gas producer’s subsurface engineering teams. The upside extends beyond mere convenience, however, and translates directly into faster decision making which is one of the keys to success in the dynamic landscape of unconventional developments. When data is seamlessly connected for daily consumption, engineers engage with it regularly, integrating it into their daily workflows. Additionally, we see that the frequency of use is directly correlated with accessibility. The emphasis on accessibility reflects Devon’s proactive efforts to treat its data more and more as a valuable asset. By democratizing data and analysis tools, business-impacting insights are more readily available to engineers and decision-makers throughout the organization. This case study outlines one of the most recent and tangible outcomes of this collaborative philosophy: automatic calculation of bottomhole pressure (BHP). Solving for Bottomhole Pressures As shown in Fig. 1, accurate and reliable flowing BHP data is a critical input for a number of important engineering applications in both conventional and unconventional settings: reservoir simulation, production diagnostics, nodal analysis, rate transient analysis, pressure transient analysis, and material balance. The list goes on, but the overarching point is that BHP data allows engineers to make informed decisions, i.e., high-confidence estimations on future well production, reservoir management, and optimization strategies. The rub is that acquiring accurate BHP measurements has historically been a luxury service that is too costly to scale up beyond a few science projects. Operators that desire such critical data often turn to BHP gauges, which are positioned down in the wellbore to measure pressure at a specific depth. But given an average cost of $50,000 per installation, it is estimated that less than 5% of all horizontal wells drilled during the North American shale revolution have benefited from the use of downhole gauges. Without a downhole gauge, operators must calculate the pressures from surface pressure. The problem here is again one of scale. Using surface pressure has traditionally required the manual gathering of the proper data sets and calculating BHP. From there, the process is not only time consuming but considered to be error prone. Applying any of the published methods may take a reasonably experienced engineer half an hour to complete a BHP calculation and the odds of a miscalculation rise as the data set grows in size and complexity.

Improvement of Gas Compressibility Factor and Bottom-Hole Pressure Calculation Method for HTHP Reservoirs: A Field Case in Junggar Basin, China

Gas reservoirs discovered in the southern margin of the Junggar Basin generally have high temperatures (up to 172.22 °C) and high pressures (up to 171.74 MPa). If using the PVT laboratory to get the gas compressibility factor, data from the laboratory are so little that it will not satisfy the demands of reservoir engineering calculations. There are many empirical correlations for calculating the Z-factor; however, these correlations give large errors at high gas reservoir pressures. The errors in estimating the Z-factor will lead to large errors in estimating all the other gas properties such as gas formation volume factor, gas compressibility, and gas in place. In this paper, a new accurate Z-factor correlation has been developed based on PVT data by correcting the high-pressure part of the most commonly used Dranchuk-Purvis-Robinson Correlation. Multivariate nonlinear regression is used to establish the independent variable function of pseudo-critical temperatures and pressures. By comparing it with the PVT data, the DPR correlation is continuously corrected to be suitable for ultra-deep gas reservoirs with HTHP. The new correlation can be used to determine the Z-factor at any pressure range, especially for high pressures, and the error is less than 1% compared to the PVT data. Then, based on the corrected Z-factor, the Cullender-Smith method is used to calculate the bottom hole pressure in the middle of the reservoir. Finally, the Z-factor under reservoir conditions of well H2 is predicted and the Z-factor chart at different temperatures is provided.

Flow regulation and bottom hole pressure control under gas influx condition based on RMR system

During the drilling process of RMR system, when the gas reservoir is drilled, the bottom hole pressure and formation pressure are in an unbalanced state, and the formation fluid invades the bottom hole under the action of pressure difference, further causing complex situation such as overflow and kick. In order to effectively control the bottom hole pressure during drilling and ensure drilling safety, a bottom hole pressure calculation model of RMR system under gas influx condition is established based on the gas-liquid two-phase flow theory. Three flow regulation methods of increasing the outlet flow of drilling pump and subsea pump at the same time, reducing the outlet flow of subsea pump while the outlet flow of drilling pump remains unchanged, and increasing the outlet flow of drilling pump while reducing the outlet flow of subsea pump are selected to dynamically simulate the change process of bottom hole pressure after flow regulation. Through data fitting, The relationship equation between them and bottom hole pressure is obtained, and the flow regulation method of RMR system when controlling bottom hole pressure under gas influx condition is formed.

Analysis of sulfur deposition for high-sulfur gas reservoirs

Wellbore sulfur deposition is one of the most common problems during the development of high-sulfur gas reservoirs, which also affects the accuracy of bottomhole pressure(BHP) calculations. However, the existing BHP calculation methods have poor applicability to high-sulfur and water-producing gas wells. In this study, a model for calculating bottomhole pressure suitable for high-sulfur and water-producing gas wells was established. The model was solved by finite difference and iterative methods, and its accuracy was verified by a typical high-sulfur gas well in China. The results show: The pressure prediction errors are mainly distributed within −1%∼5%; As the well depth decreases, the precipitation trend of sulfur gradually increases due to the decrease in solubility; Affected by temperature and pressure distribution, liquid sulfur is often deposited in the lower part of wellbore, while solid sulfur is deposited in the middle-upper section, which will increase the pressure loss and the occurrence of production accidents. Controlling production pressure difference, adopting production system, and injecting sulfur dissolving agents can help prevent sulfur deposits and ensure the safe-efficient production. The findings of this study can help to more clearly reveal the wellbore sulfur deposits characteristics and more accurately calculate the bottom hole pressure of high-sulfur gas wells.

Dynamic prediction and influencing factors analysis of gas and water co-production stage in tight sandstone reservoir

Tight gas reserves account for a large portion of unconventional gas resources. At the stage of multiphase production of gas and water, gas productivity can be severely reduced because of water accumulation at the bottom of wellbore. This study investigates the effects of multiphase flow on bottomhole-pressure (BHP) estimation and productivity forecast for tight gas wells. The Beggs-Brill method is modified to calculate BHP by considering the phase changes of water in wellbore. The modified Beggs-Brill method is demonstrated with a relatively high accuracy (relative error <5%) in BHP calculation though comparing it against measured values. This study also establishes a new productivity model which mainly combines the water blockage effect caused by multiphase flow in the reservoir. The new model is further validated against field measurements. The results also suggest the relative permeability of gas and the mass ratio of gas and water follows a power-law relationship in the water-blockage area, and the gas productivity can be severely reduced once water blockage occurs for the tight gas wells.

Bottom Hole Pressure Calculation of Fractured Carbonate Formation

Carbonate formation is widely distributed in China, mainly showing the sensitivity of the target formation and the development of fracture and cavity types and narrow pressure window. Drilling complicated conditions such as formation leakage or bottom hole pressure less than formation pressure due to gas entering wellbore occur from time to time. To solve these problems, calculating the bottom hole pressure accurately and conducting managed pressure drilling (MPD) for fractured carbonate formation are necessary. In this study, the single-phase hydraulic model based on H-B rheological model is calculated. According to the characteristics of fractured carbonate formation, the drilling fluid leakage model is obtained. By coupling the leakage model with the single-phase wellbore hydraulic model, the bottom hole pressure calculation method is suitable for fractured carbonate formation, which can provide reference for managed pressure control drilling technology. Such a technology is verified by Bozhong X well through the above calculation method of bottom hole pressure. The model is used to simulate the leakage behavior of transverse and longitudinal fractures. Moreover, the variation characteristics of the leakage rate and cumulative leakage amount of the drilling fluid in the fracture are investigated. By comparing the loss control with conventional drilling and MPD, the advantages of controlled pressure drilling operation in the loss control are described.

A new method for assessing stage-based hydraulic fracturing quality in Wolfcamp formation of Permian Basin

In 2018 US Geological Survey assessed Wolfcamp formation in Permian Basin at west Texas and southwest New Mexico, USA as the world's largest tight oil play that has the most technically recoverable reserves. This is the result of favorable combination of tectonic activities and the depositional environments in the Paleozoic period. Three major cycles of tectonic movements controlled the creation of Permian Basin and its sub-basins. Frequent seawater inundations and retreats caused cyclic changes in depositional environments from Pennsylvania to early Permian ages, leading to the formation of an organic rich, tight and thick formation, the highly heterogeneous Wolfcamp play. Advanced completion technology of combining horizontal drilling with multi-stage massive hydraulic fracturing is needed for the commercial development of Wolfcamp play. Successful application of advanced completion technology in Wolfcamp faces two challenges: stage-after-stage cumulative stress-shadow effects and localized heterogeneity in lithofacies and reservoir quality. The “one-for-all” fracturing design needs to be able to fine-tune stage-by-stage based on real-time feedback from fracturing quality of previous stage. Existing methods, from production logging to micro-seismic mapping, cannot provide real-time feedback of stage-based treatment quality. We propose a new method in this paper. The new method is based on the assumption that constant density of slick-water at shut-in intervals during hydraulic fracturing allows an accurate calculation of bottom-hole pressure from surface treatment pressure and true vertical depth at each stage. Using real-time on-site monitored surface treatment pressures during shut-in intervals at the end of pad and flush injections, stage-by-stage fracturing quality are calculated. Two Wolfcamp case studies in Midland Basin at Reagan County, Texas show that the new method can be used to quantify stage-based treatment qualities. Stage-based fracturing qualities from this new method are consistent with stage-based treatment results evaluated using other methods.

P.410 Searching for predictive validity in animal tests for mania-like behaviour

The precise and convenient calculation of bottom hole pressure can provide a guarantee for safe drilling. Most of the existing models for determining the downhole pressure or annular pressure gradient (PG) are applied only to the circular wellbore. Due to the nonuniform in situ stress and the anisotropism of formation rock, the borehole formed by rotary drilling is the closest to the ellipse, that is, the irregular circular borehole. Therefore, it is of importance to research YPL fluid flow through the eccentric elliptical annulus (EEA) for the accurate prediction of bottom hole pressure. In this paper, a numerical model for determining the PG of YPL fluid flow in the EEA is developed on the basis of fluid mechanics. Then, through parameter studies, a new regression model (RM) of the pressure ratio in the EEA is established. The commercial software ANSYS was used to research the laminar flow of yield-power-law fluids through the EEA, and the simulation results are used to verify the numerical model and new regression model. The main conclusions are as follows. (1) The PG increases quasi-linearly or linearly with the mean velocity, fluid consistency index and yield stress and hardly changes with the azimuth of the inner pipe center. The PG decreases with a/b (η) and eccentricity (ε) when the mean velocity is constant. (2) The new regression model is valid for the ranges 0.2≤Kd ≤ 0.8, 0≤ε ≤ 0.95, 0.2 ≤ n ≤ 1.0, and 1.0≤η ≤ 1.2 and shows excellent agreement with existing model and computational fluid dynamics (CFD) simulations, within ±5% error bars. (3) The maximum velocity first increases and then decreases with ε. The results of axial velocity and PG using CFD software are found to be in excellent agreement with the numerical model solutions. (4) Predicting the PG in the EEA using the new regression model has high precision and without complicated numerical computation.

Application of the bottomhole pressure calculation method to operate an oil well

The aim of the study is to obtain reliable values of bottomhole pressure calculation method in oil wells of PJSC «Tatneft» due to technical difficulties emerged when performing deep measurements of producing wells at the Romashkino oil field.We have performed calculations of bottomhole pressure in wells according to Hasan — Kabir method and the RD 153-39.0-920-15 method. The comparison of the obtained values revealed that the average relative error of Hasan — Kabir method is 5,33 % (not more than 10 %), in contrast to the RD method.Also, we have created the model of the process control system of oil production in the program MATLAB/Simulink. This program includes the algorithm of regulation the liquid rate. In modeling the control system, a transient process is observed, in which the value of the liquid rate increases and stabilizes. Thus, the application of Hasan — Kabir method in the proposed process control system of oil production is possible in all wells at the Romashkino oil field.

Interference test simulation of Geothermal two phase field using PTA software and TOUGH2

Interference test simulation is conducted to find out the relationship between active well and observation well in a reservoir system through Bottom hole pressure (BHP) Transient analysis of interference test pressure data was performed using PTA software, while interference test simulation was performed using TOUGH2. The main parameters that become input data for transient pressure analysis are Bottom Hole Pressure and flow rate during interference test. Transient pressure analysis is used to determine the condition of wells, reservoir characteristic and the reservoir boundary conditions during the interference test. The research method are calculation of Bottom Hole Pressure with hydrostatic method, transient pressure analysis and reservoir simulation. The results are an interference indication between the WWA-4 and WWA-6 wells in the simulation model of interference test with the transmissivity value 4.7E3 Darcy-meter and storativity value 23.4 m at aquifer thickness value 100 m.

Modeling of laminar flow in an eccentric elliptical annulus for YPL fluid

The precise and convenient calculation of bottom hole pressure can provide a guarantee for safe drilling. Most of the existing models for determining the downhole pressure or annular pressure gradient (PG) are applied only to the circular wellbore. Due to the nonuniform in situ stress and the anisotropism of formation rock, the borehole formed by rotary drilling is the closest to the ellipse, that is, the irregular circular borehole. Therefore, it is of importance to research YPL fluid flow through the eccentric elliptical annulus (EEA) for the accurate prediction of bottom hole pressure. In this paper, a numerical model for determining the PG of YPL fluid flow in the EEA is developed on the basis of fluid mechanics. Then, through parameter studies, a new regression model (RM) of the pressure ratio in the EEA is established. The commercial software ANSYS was used to research the laminar flow of yield-power-law fluids through the EEA, and the simulation results are used to verify the numerical model and new regression model. The main conclusions are as follows. (1) The PG increases quasi-linearly or linearly with the mean velocity, fluid consistency index and yield stress and hardly changes with the azimuth of the inner pipe center. The PG decreases with a/b (η) and eccentricity (ε) when the mean velocity is constant. (2) The new regression model is valid for the ranges 0.2≤Kd ≤ 0.8, 0≤ε ≤ 0.95, 0.2 ≤ n ≤ 1.0, and 1.0≤η ≤ 1.2 and shows excellent agreement with existing model and computational fluid dynamics (CFD) simulations, within ±5% error bars. (3) The maximum velocity first increases and then decreases with ε. The results of axial velocity and PG using CFD software are found to be in excellent agreement with the numerical model solutions. (4) Predicting the PG in the EEA using the new regression model has high precision and without complicated numerical computation.

The method of calculation the pressure gradient in multiphase flow in the pipe segment based on the machine learning algorithms

Engineering tools allowing pressure gradient calculation in the pipe segment commonly use stationary correlation and mechanistic models such as Beggs and Brill, Ansary, etc. This is well known and convenient way which gives rough estimate of pressure gradient due to friction losses and liquid phase interference. It avoids solving complex dynamic pressure equation and derives quick results with comfortable precision margin for large scale systems, such as horizontal pipes and wells. In order to enlarge the applicability zone and accuracy of existing methods, a new method of pressure gradient definition is evolved. It is included three surrogate models that are based on Machine Learning (ML) algorithms. The first model predicts liquid holdup in the segment, the second defines flow pattern and the third predicts pressure gradient. In order to create these models, several ML algorithms are applied such as Random Forest, Gradient Boosting, Support Vector Machine and Artificial Neuron Network.Involvement of the latest machine learning algorithms will allow applying this method to wider range of input data compared with standard multiphase flow correlations and mechanistic models. The proposed method demonstrates high accuracy – on the collected experimental data set it gives R2 = 0.985 for pressure gradient prediction. That is why it could help to carry out correct calculation of bottom hole pressure and pressure distribution along the length of the pipeline.

Implement intelligent dynamic analysis of bottom-hole pressure with naive Bayesian models

During the drilling process, measured bottom-hole pressure data were prone to distortion and even no data are fed back, besides, the bottom-hole pressure calculation model could not reflect the live measured values. As a consequence, inaccurate bottom-hole pressure monitoring would bring enormous safety risks to drilling operations. Data mining was an advanced method used to sort out, discover and set up models from large relevant data sets. In the monitoring of bottom-hole pressures, it was necessary to conduct an effective and overall monitoring during the drilling process. Therefore, this paper proposed the k-means clustering method to optimize Naive Bayesian models in combination with the bottom-hole pressure monitoring theory, a k-means clustering optimized Naive Bayesian model for implementation of intelligent dynamic analysis of bottom-hole pressure was established. Such model could be utilized for correcting bottom-hole pressures calculated by the traditional hydraulic model, and then the corrections were taken for comparison with measured bottom-hole pressures so as to make calculations be of minimal errors. Field data were also taken for analysis, and the results suggested that the k-means based Naive Bayesian models for correction to calculated bottom-hole pressures had smaller deviations which fell within safe deviation monitoring range of drilling pressures, and could meet the requirements of normal drilling operation.

Rock mechanics of shear rupture in shale gas reservoirs

Hydraulic fracturing is an effective technology to improve shale gas wells production. The key problem in shale gas well hydraulic fracturing is opening hydraulic fractures to connect natural fractures and weak planes, in turn, creates the fracture network. The shear failure of matrix, natural fracture and weak plane are the main rock rupture models used in shale gas reservoirs. In this paper, firstly, a bottom hole pressure calculation model is built to show that large hole perforations and big pipeline diameters should be used to decrease perforation friction. Secondly, shale rock, natural fracture and weak plane shear failure models, based on rock mechanics theory, are presented. The calculated results show that horizontal differential principal stress has a significant influence on shear failure and the slippage of natural fracture and weak plane. A higher value of differential principal stress indicates a lower shale rock shear failure pressure, which brings benefits to weak plane slippage. Elastic modulus and Poisson's ratio all have effects on weak plane shear slippage. The influences of elastic modulus on shear slippage have a greater impact than Poisson's ratio. A reasonable dip angle of weak plane is also provided to enhance weak plane slippage. The practical-approach built in the paper does not require more rock mechanics parameters. The results have potential to enrich shale rock shear rupture theory and benefit fracture mesh system research.

Study of early dynamic evaluation methods in complex small fault-block reservoirs

Based on oil test and production test data of Sagizski complex small fault-block reservoir in Kazakhstan, this paper proposes systematic evaluation of reservoir dynamic characteristics and stable-development productivity equations, in view of reservoir early dynamic evaluation systems with oil test and production test materials. In association with dynamic production analysis, these paper studies convenient and feasible methods on the correction of calculation of bottom-hole pressure and test oil yield and determination of drive types of formation energy. In addition, this paper utilizes dynamic pressure data to more accurately estimate reserves, with the aim of providing a valid method for similar reservoirs early dynamic evaluation, which can effectively direct the setting of development programs and deployments.

The Effect of Pressure Gauge Placement on Well Testing Analysis Accuracy

The main assumption in well test analysis is that the pressure at the perforation zone is known, although transient pressure data may often be recorded at points above the perforation zone in the wellbore. Conversion of recorded data to bottomhole pressure can be affected by wellbore-related phenomena. In this article we develop a nonisothermal transient multiphase wellbore simulator, coupled to a compositional reservoir simulator, to model fluid flow and pressure during well testing. We show that neglecting multiphase flow effects in wellbores for the calculation of bottomhole pressure may make well test results unreliable. We also develop a method to use our simulator to calculate bottomhole pressure from measured pressure data when gauges are placed far from the perforations due to downhole restrictions.

A Simple Mechanistic Model for Void-Fraction and Pressure-Gradient Prediction in Vertical and Inclined Gas/Liquid Flow

Summary A new mechanistic model for two-phase flow in vertical and inclined pipes was proposed on the basis of the drift-flux approach. The proposed model, unlike the other mechanistic models [Ansari et al. (1994); Xiao et al. (1990); Zhang et al.(2003)] that incorporate a system of nonlinear equations to solve, uses an explicit equation for liquid-holdup prediction, thus reducing computation time significantly. Coupled with some simplified assumptions on pressure/volume/temperature (PVT), such a simple form of a liquid-holdup-prediction formula enables an analytical integration of the pressure gradient in two-phase flow along the pipe. This procedure is used usually to speed up the calculation of bottomhole pressure (BHP) for a large number of wells for oil-production-optimization purposes (Khasanov et al. 2006). The drift-flux approach can predict liquid holdup for bubbly flow quite accurately. However, for slug flow, it usually underestimates the void fraction. Because slug flow is the most common flow in producing wells, this leads to the pressure drop being overestimated significantly; this can be proved by comparing computational results to the experimental data and mechanistic models. Small gas bubbles in liquid slugs should be accounted for when predicting liquid holdup for slug flow more accurately. Gas in the slug body is considered by adding a proper term to the void-fraction expression. This term is based on the correlation for liquid holdup in the slug body. The model was evaluated with Rosneft's field data and the Tulsa University Fluid Flow Projects (TUFFP) databank. The model was evaluated by comparing it with three mechanistic models for multiphase flow.

New Procedure for Wellbore Flash Calculations

Summary This paper describes a new wellbore flash procedure implemented in a compositional reservoir simulator. It is used for calculations of bottomhole pressure (BHP), surface rates, and fluid compositions of a production well from specified well boundary conditions. Coupled wellbore, well tubing, and surface separator models are considered. The procedure for the solution of the wellbore flash problems with specified production rate at stock-tank conditions and with specified tubing-head pressure is developed. The new procedure has several advantageous features. Wellbore equations and separator flash equations are solved simultaneously. A new iterative technique is applied for the solution of phase-equilibrium and mass-conservation equations for each stage of a separator battery. Material-balance conditions are satisfied exactly in each iteration. A new rigorous algorithm is developed for the calculation of BHP if tubing-head pressure is specified. Phase-equilibrium computations in surface separator stages consume a large part of CPU time, required for some large compositional reservoir models (about 50%). In the new procedure, K values are calculated by minimizing Gibbs free energy, and mass-conservation equations are exactly solved in each iteration. This approach provides significant computational improvement (by a factor of four) over previous wellbore flash computations in compositional reservoir simulators with a Cray XMP-416.

Afterflows and Buildup Interpretation on Pumping Wells

Summary Afterflow measurement identifies downhole problems as indicated by the presence of (1) a long fluid column, (2) U-tubing of liquid from the tubing to the annulus, (3) gas coning, and (4) stratification, as evidenced by highpressure gas stringers or high-pressure liquid stringers. Introduction Pumping wells are generally older wells with declining production. They are prime candidates for estimation of skin damage, fracture length, reservoir pressure, effective permeability, and other diagnostic information provided by pressure buildup curves. However, the necessity of removing the rods and pumps to place the conventional pressure bomb and then temporarily replacing the rods and pumps to restabilize the well and get the flowing bottomhole pressure, which is essential to well damage estimates, has meant that buildup curves practically never were run on pumping wells.We have been getting buildup curves on pumping wells by determining the liquid level in the annulus acoustically, measuring the surface annulus pressure, and calculating the sandface pressure. This permits following the liquid level and bottomhole pressure before shut-in to check pump operation or well stabilization and then following the buildup from the moment of shut-in. This also gives direct measures of the well storage factor and the afterflows of gas and liquid during buildup. Calculation of Bottomhole Pressure, Afterflows, and Well Storage A schematic of a typical well configuration is shown in Fig. 1. There is no packer. The gas and liquid entering the well separate in the annulus, the gas rising up through the fluid column to be produced out of the wing valve and the liquid being pumped out through the tubing.Our well sounder has a three-way valve that maintains a pressure above the annulus pressure in an expansion chamber. Upon signal from a preprogrammed self-contained monitor, a pulse of nitrogen from the expansion chamber enters, the annulus, starting a counter. The returning echo from the fluid stops the counter. The speed of the counter is adjusted by a dial calibrated in acoustic velocity. When setting up, we measure the liquid depth with a collar counting device and adjust the counter speed to give feet depth to liquid directly. Under favorable conditions, our reproducibility is about 1 ft. The setting on the acoustic velocity dial gives the acoustic velocity of the gas in the annulus. Knowing the acoustic velocity, we calculate the specific gravity of the gas in the annulus and its Z factor. Knowing the surface pressure, the annulus area, the depth to liquid, and the Z factor at each point along the curve, we can calculate the gas column weight to get the average pressure in the gas and the standard cubic feet of gas in the annulus at each point. The increase in this gas between successive points directly gives the Mcf/D flowing into the gas space during each time intervalthe gas afterflow.The sandface pressure is calculated starting with the measured surface pressure. The weight of the gas column is calculated by integration knowing the gas gravity, temperature, and average Z factor. This gives the pressure at the top of the fluid column.The weight of the fluid column is calculated stepwise. starting at the top, a depth interval is taken such that the pressure at the bottom of the interval will be 1.2 times the pressure at the top of the interval. The average pressure is 1.1 times the pressure at the top of the interval, the annulus area is known, and the rate of gas flow is the previously measured gas afterflow. From these three data, published correlations give the fraction of liquid in the interval. JPT P. 397^